eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-01-13 21 5698 article Table of Contents for Volume 21, 2026, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/5698 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-01-13 21 5671 article Mohamed Badouch mohamed.badouch@edu.uiz.ac.ma Mehdi Boutaounte mehdi.boutaounte@gmail.com Aim/Purpose: This study addresses the challenge of understanding and predicting tourist decision-making in the AI era by integrating sentiment, credibility, and contextual signals from social media into a unified and actionable framework. It seeks to move beyond raw user-generated content toward trustworthy, decision-ready insights that can guide destinations, platforms, and travelers. Background: Tourism analytics often treat online sentiment at a surface level, overlooking emotional nuance, content credibility, and real-world context. To bridge this gap, the Affective Understanding, Reliability, and Outcome-driven Recommendation Architecture (AURORA) offers a sentiment-driven, context-aware system that captures emotions, filters unreliable information, and models how travelers make choices across different decision stages. Methodology: AURORA processes multimodal public data such as reviews, social posts, and event feeds. It combines aspect-based sentiment and emotion analysis with credibility assessment and contextual modeling. A Bayesian state-space model tracks traveler decision stages, while uplift modeling identifies when and where interventions are most effective. The analysis tested AURORA on a large-scale Booking.com dataset spanning 18–24 months, which captured seasonal variation. Contribution: AURORA introduces a next-generation, sentiment-based decision framework that unites emotional understanding, trust evaluation, and context sensitivity in tourism analytics. The paper demonstrates how combining textual and behavioral data yields measurable insights that are both theoretically grounded and practically deployable for decision support. Findings: Aspect‑level sentiment on core attributes – particularly safety, cleanliness, and value – emerges as the strongest predictor of traveler attitudes and booking propensity, with emotional intensity amplifying these effects and social proof showing diminishing marginal returns at high volumes. Credibility and provenance filters materially reduce noise from low‑quality or manipulated content, and hybrid models that combine textual embeddings with structured metadata outperform polarity‑only baselines for predicting high‑intent behaviors. Practitioners should therefore prioritize real‑time monitoring of high‑elasticity aspects, elevate aspect‑rich, high‑credibility content in ranking and messaging, and time interventions to the traveler’s decision stage to maximize incremental lift rather than mere engagement. Recommendations for Practitioners: Prioritize real-time monitoring of high-elasticity aspects (e.g., safety, crowding) to inform campaigns. Elevate high-quality, aspect-rich user content in ranking algorithms. Time interventions to decision-journey stages when cues are most impactful. Recommendation for Researchers: Extend the framework to non-English, multilingual contexts with localized aspect taxonomies. Investigate causal pathways between exposure to specific sentiment cues and actual booking behavior. Explore the integration of multimedia sentiment (image/video emotion) in tourism decision models. Impact on Society: Enables more transparent and trustworthy tourism information ecosystems, empowering travelers to make better decisions and helping destinations manage perception during crises. Fosters healthier digital tourism discourse by amplifying authentic, credible voices. Future Research: Building on AURORA, the next phase should validate and extend the architecture across languages, cultures, and media. This includes developing localized aspect taxonomies and multilingual encoders, running causal field experiments that link exposure to specific sentiment cues with booking behavior, and integrating multimedia emotion signals (images and video) alongside privacy‑preserving, on‑device analytics. Together, these steps will make AURORA more robust to cross‑cultural expression, resilient under distribution shifts, and practical for real‑time, privacy‑aware deployment in diverse tourism ecosystems. http://www.informingscience.org/Publications/5671 tourist decision-making sentiment analysis social media analytics credibility modeling destination marketing AI in tourism eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-01-17 21 5690 article Cris Norman P. Olipas olipas.cris@gmail.com Aim/Purpose: This study aims to analyze and predict the employability outcomes of higher education students in the Philippines using data-driven predictive modeling. It aims to identify the student attributes that most strongly influence employability, thereby supporting evidence-based curriculum development and workforce alignment initiatives. Background: Graduate employability remains a challenge in the Philippines due to persistent gaps between higher education outcomes and labor market expectations. While prior studies emphasize technical competencies, there is limited evidence on the role of non-academic student attributes in predicting employability, particularly through interpretable predictive approaches. This study addresses this gap by examining employability-related traits using machine learning techniques. Methodology: A publicly available dataset of 2,982 anonymized student records from mock interviews conducted across Philippine higher education institutions was analyzed. Employability was treated as a binary outcome variable. Predictive models were developed with Random Forest selected as the primary model based on overall performance. Model interpretation was conducted using Shapley Additive Explanations (SHAP) analysis to identify the most influential student attributes. Contribution: The study demonstrates how interpretable machine learning can be used to evaluate graduate employability and identify key attributes shaping workforce readiness. The findings offer practical value for higher education institutions and policymakers seeking data-driven approaches to curriculum design and student development. Findings: The Random Forest model showed strong predictive performance in classifying employability outcomes. SHAP analysis revealed that mental alertness, general appearance, and the ability to present ideas were the most influential factors affecting employability, indicating the importance of cognitive and professional presentation skills. Recommendations for Practitioners: Higher education institutions should strengthen instructional strategies and student development programs that enhance cognitive readiness, professional presentation, and communication-related competencies. Career services and industry partners are encouraged to collaborate in aligning training initiatives with employability needs. Recommendation for Researchers: Future studies should explore additional predictive models and incorporate broader datasets to further validate the determinants of employability. Including demographic and academic variables may deepen understanding of employability dynamics. Impact on Society: By identifying critical employability attributes, this study supports more responsive and inclusive higher education practices. Data-driven employability strategies can contribute to improved workforce readiness and reduced graduate unemployment in the Philippines. Future Research: Future research may examine longitudinal employability outcomes and assess the application of predictive analytics in institutional decision-making contexts. Attention to ethical considerations, including transparency and fairness, is also recommended. http://www.informingscience.org/Publications/5690 machine learning predictive modeling random forest SHAP student employability eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-01-26 21 5696 article Rita Rismala ritaris@telkomuniversity.ac.id Untari Novia Wisesty untarinw@telkomuniversity.ac.id Febryanti Sthevanie sthevanie@telkomuniversity.ac.id Aim/Purpose: This study aims to address the issue of partial preference, which causes incomplete criteria-level ratings and limits the accuracy of recommendations in multi-criteria recommender systems (MCRS). The primary focus of this study is to develop an imputation method that treats the imputation process as a sequential prediction task in which each missing criterion is predicted based not only on the known ratings but also on the previously imputed values. These preceding ratings serve as contextual input for the next prediction step, enabling the model to dynamically capture inter-criteria dependencies and thereby improve the overall imputation quality. Background: A key challenge faced by MCRS is the issue of partial preference, which arises when users fail to provide ratings for all criteria. This results in incomplete criteria-level data, ultimately undermining the accuracy and effectiveness of MCRS in generating relevant recommendations. While most studies have primarily focused on improving the recommendation algorithms themselves, the pre-recommendation phase, which involves preparing high-quality and comprehensive input data, has often been overlooked. Yet, ensuring that multi-criteria data is as complete and accurate as possible is crucial for producing high-quality recommendations. This highlights the importance of a preprocessing step, particularly the imputation process to handle incomplete criteria ratings, applied prior to the recommendation generation process. Rating-based imputation offers efficiency, while machine learning-based imputation offers accuracy. To leverage those advantages, this study employed rating-based imputation using a simple yet effective machine learning technique, Naive Bayes (NB). NB operates under the assumption of conditional independence among features, which may lead to suboptimal performance in contexts where semantic or perceptual correlations exist among criteria. In response to this limitation, this study introduces a sequential imputation approach, where each prediction of a missing criterion is informed by previously known or imputed ratings that are used as contextual input for the next prediction. Methodology: This study introduces a new imputation method called Recurrent Naive Bayes (RNB), designed to estimate missing criteria ratings. Unlike traditional approaches, RNB models the imputation as a sequential prediction process, where each known or already imputed criterion Rc serves as contextual information for predicting the subsequent missing criterion Rc+1. The core of RNB involves a recurrent process that includes prediction using NB, conditional imputation for the missing values, and updating the set of completed criteria. At each step, the model uses more features, starting with the overall rating and adding each newly predicted criterion one by one until all criteria are completed. In the recommendation process, RNB is used beforehand as part of the Multi-Criteria Collaborative Filtering (MCCF) pipeline. The performance of RNB is then evaluated by examining its impact on recommendation accuracy, specifically in terms of predicted criteria ratings, overall ratings, and recommended items, using three real-world datasets: TripAdvisor (TA), Yahoo! Movies (YM), and BeerAdvocate (BA). Contribution: This study addresses the issue of partial preference in MCRS by highlighting the underexplored potential of NB for imputing missing criteria ratings. To this end, we propose RNB, a novel method that enhances traditional NB by adopting a sequential imputation strategy. Unlike conventional approaches that treat each criterion independently, RNB captures inter-criteria correlations, thereby improving imputation quality while preserving computational efficiency. Findings: RNB consistently outperformed baseline methods significantly, including no imputation, mean imputation, and NB imputation, in enhancing MCRS performance across all datasets. This is demonstrated by its performance in predicting criteria ratings, overall ratings, and recommended items. The improvements were most notable in datasets with a larger number of criteria, stronger inter-criteria correlations, and larger size. Additionally, RNB enhanced recommendation accuracy for both moderately and highly recommended items. Recommendations for Practitioners: By implementing MCRS, practitioners are encouraged to incorporate imputation techniques, such as RNB, during the preprocessing stage to improve data completeness and overall recommendation quality. RNB offers a practical balance between accuracy and efficiency, making it suitable for real-world applications where computational resources and data quality vary. It is especially recommended in scenarios involving sparse multi-criteria data with high inter-criteria correlation, such as in tourism, e-commerce, or entertainment domains. Recommendation for Researchers: Adopting RNB can be beneficial for researchers as a practical and effective imputation method in MCRS, particularly when dealing with sparse and partially filled datasets. Its ability to capture inter-criteria dependencies through a sequential process makes it a valuable alternative to traditional imputation methods that assume feature independence. RNB’s simplicity, efficiency, and ease of integration into existing MCRS frameworks make it suitable for empirical studies that require scalable and interpretable preprocessing techniques. Impact on Society: Recommender systems play a vital role in supporting decision-making across various domains such as tourism, entertainment, e-commerce, and education. By addressing the issue of partial preferences, RNB improves the completeness of user data, leading to more relevant and personalized recommendations. This impacts enhanced user satisfaction, better overall experiences, increased trust in digital platforms, and more informed consumer decisions. Moreover, the efficiency and simplicity of RNB support broader accessibility by enabling effective recommendations even in data-sparse environments. Future Research: The performance of RNB depends on the assumption that inter-criteria dependencies can be captured in a sequential manner. However, the optimal ordering of criteria may differ between datasets, requiring dataset-specific analysis. Future research may explore dynamic or hybrid ordering strategies that simultaneously consider both sparsity and correlation to improve imputation quality. In addition, incorporating more advanced machine learning techniques could help model complex or nonlinear relationships among criteria. Furthermore, enhancing the robustness and adaptability of the imputation process. http://www.informingscience.org/Publications/5696 imputation multi-criteria recommender system partial preference recurrent Naïve Bayes eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-02-09 21 5707 article Muhammad Rifai Katili mrifaikatili@ung.ac.id Mohamad Hidayat Koniyo hidayat_koniyo@ung.ac.id Lanto Ningrayati Amali ningrayati_amali@ung.ac.id Raflin Hinelo raflin@ung.ac.id Mohamad Syafri Tuloli syafri.tuloli@ung.ac.id Alfian Zakaria alfian.zakaria@ung.ac.id Aim/Purpose: The research aimed to design, develop, and test a system that enabled reciprocal knowledge flows between government, academia, business, media, and community stakeholders. Background: The research problem addressed in this study concerned the absence of an integrated, digital knowledge management (KM) system that could operationalize the Pentahelix framework to strengthen the management and governance of VOEs. Despite policy frameworks such as Government Regulation No. 11/2021, which formalized the operational mechanisms of Village-Owned Enterprises (VOEs) and emphasized entrepreneurship and community empowerment, challenges persisted in translating these frameworks into practice. Methodology: Employing a research and development (R&D) approach with Agile Scrum, the study engaged eight VOE managers from four villages in the Tomini Bay region of Gorontalo Province to elicit requirements through interviews, observations, and questionnaires. The system was developed iteratively over four sprints and implemented functionalities such as user authentication, collaborative forums, a knowledge repository, and analytics dashboards. The platform design utilized Unified Modeling Language (UML) diagrams to model workflows, actor roles, and class structures. System testing applied black-box and white-box approaches, complemented by sprint reviews and user acceptance testing. Contribution: This research contributed to the body of knowledge by offering both a conceptual framework and a tested prototype for digitally mediated multi-stakeholder collaboration in rural enterprise development. Findings: The findings underscored that digital KM platforms, when anchored in multi-stakeholder frameworks, served as strategic enablers of rural development. Evaluation demonstrated high system reliability with 100% functional test pass rate and optimized query response times (reduced by 60-75%). User acceptance testing revealed strong adoption potential, with Perceived Usefulness (M = 6.2/7.0), Intention to Use (M = 6.0/7.0), and Overall Satisfaction (M = 5.9/7.0) scores indicating high levels of satisfaction. Task completion rates improved from 72% in Sprint 1 to 95% in Sprint 4. The integration of the platform with potential e-government and e-commerce systems suggested significant implications for participatory governance, market democratization, and rural economic empowerment. Recommendations for Practitioners: Practically, by presenting a tested prototype developed using Agile Scrum methodology that served as a model for similar initiatives in developing countries. Recommendation for Researchers: Theoretically, by extending the application of KM and Pentahelix frameworks to rural enterprise contexts. Impact on Society: The platform’s adaptability to diverse digital readiness contexts signaled its transferability to other rural regions, provided that localized adjustments were made. Future Research: Future studies could explore the integration of automation, advanced analytics, and recommender systems while further evaluating the longitudinal impacts on business performance, collaboration intensity, and community well-being. http://www.informingscience.org/Publications/5707 village-owned enterprises knowledge management Pentahelix model digital knowledge management system rural development multi-stakeholder collaboration Indonesia eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-03-14 21 5711 article Jesús Salinas jesus.salinas@uib.es Francisca Negre-Bennasar xisca.negre@uib.es Jacoba Munar-Garau jacoba.munar@uib.cat Aim/Purpose: This study examines how digital technologies are used to support communication between families and educational centers, understood as formal primary and secondary schooling institutions, during and after the COVID-19 pandemic. The research explores parents’ perceptions of these communication practices, their perceived influence on family involvement, and the challenges and opportunities associated with digitally mediated family-school relationships. Background: The rapid digitalization of educational communication during the pandemic transformed established family-school interactions worldwide. Understanding families’ beliefs, everyday practices, and perceived difficulties in using digital technologies is essential to inform more inclusive and participatory communication strategies that remain relevant beyond emergency contexts. Methodology: The study uses a mixed-methods approach combining quantitative and qualitative methods through a convergent or concurrent triangulation design. For the quantitative phase, the COMCEFAM questionnaire (Questionnaire on Communication between the School and Families) was used, which was designed and validated for this purpose. It consists of 36 items and was administered to the families of primary and secondary school students. For the qualitative phase, a parent discussion group was used to explore in depth experiences and perceptions related to digital communication with schools. Contribution: This study’s contribution concerns parents’ perceptions of the use of digital technologies in family-school communication during and after the pandemic, the impact of this communication on family involvement in the school, and possible proposals for the use of digital technologies that promote new scenarios for family participation. Findings: Results indicate a broadly positive perception of digital technologies as tools for family-school communication. A large majority of respondents agreed that digital technologies are useful for communication (88.22%) and necessary in contemporary society (85.20%). However, perceived support for family participation through digital means was moderate, and only 30.48% of families reported receiving training from educational centers on using these technologies. Qualitative findings highlight persistent challenges, including the dispersion of communication channels, unequal digital competencies, and the predominance of informational rather than participatory communication practices. Recommendations for Practitioners: Promote training and digital literacy for families and teaching teams. Implement procedures that promote educational, participatory communication rather than focusing solely on the exchange of information. Recommendation for Researchers: Analyzing and understanding family-school communication is essential for designing quality proposals that enable effective and equitable communication between families and schools, regardless of context and the availability of devices and technological training. Impact on Society: Highlights the importance of communication between families and schools to improve family involvement in academic issues. Identifies additional challenges, such as the lack of preparation among teachers and families Future Research: Discuss possible proposals for the use of digital technologies that promote new scenarios for family participation, both for everyday situations and for unexpected emergencies. http://www.informingscience.org/Publications/5711 family attitudes digital technologies family-school relationships family-school digital communication eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-03-18 21 5724 article Delali Kwasi Dake dkdake@uew.edu.gh Elijah Ofori elijah.ofori@yahoo.com Aim/Purpose: This study develops a theory-informed, data-driven framework for identifying student learning modalities using Deep Embedded Clustering (DEC), with the goal of improving scalable and interpretable learner profiling in secondary education. Background: Traditional learning-style identification relies on qualitative or rule-based categorization that may not adequately capture complex learner behaviours. Although deep learning enables richer pattern discovery, many approaches lack interpretability for practical educational use. DEC offers a hybrid alternative by combining representation learning with unsupervised clustering. Methodology: A 48-item questionnaire grounded in the Felder–Silverman Learning Style Model (FSLSM) was administered to senior high school students. After preprocessing and controlled, distribution-preserving augmentation, an autoencoder learned compact latent representations. Clustering was then applied to derive learner profiles, followed by statistical validation and comparative classification experiments to assess structural and predictive utility. Contribution: This study proposes an integrated deep clustering and statistical validation pipeline that produces pedagogically interpretable learner profiles without relying on predefined labels. It extends prior work by demonstrating how unsupervised representation learning can reveal theory-consistent learning patterns. Findings: Four interpretable student profiles emerged, aligning with FSLSM dimensions and differentiated primarily by multivariate response patterns rather than isolated mean differences. Although internal validity indices indicated moderate separation, models trained on latent representations consistently outperformed those trained on raw features, demonstrating the discriminative value of learned embeddings. Recommendations for Practitioners: The identified profiles can support differentiated instruction, including structured visual materials, interactive learning tasks, blended strategies, and targeted scaffolding. Such profiling may enhance adaptive learning systems and early intervention strategies. Recommendation for Researchers: Future studies should validate findings using multi-site, non-augmented datasets and examine cluster stability across cohorts. Lightweight DEC architectures and longitudinal evaluations of personalization strategies warrant further exploration. Impact on Society: By enabling scalable, data-driven personalization, this framework may reduce reliance on subjective assessments and contribute to more equitable and responsive learning environments. Future Research: Further work should explore real-time integration within learning management systems, adaptive feedback mechanisms, and ethical considerations surrounding large-scale learner profiling. http://www.informingscience.org/Publications/5724 deep embedded clustering (DEC) learning modalities artificial intelligence in education personalized learning machine learning classification adaptive learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2026-04-02 21 5740 article Alexis Lazanas alexlas@upatras.gr YANNIS ANGELOPOULOS j_aggelo@sch.gr Aim/Purpose: The present paper focuses on the necessity of systematically incorporating knowledge produced within e-Communities of Practice (eCoPs) into formal organizational decision-making mechanisms, especially in environments of complexity, uncertainty, and accelerated digital evolution. Background: Even though eCoPs have been acknowledged as formidable tools for collaborative learning and knowledge sharing, their systematic integration into executive-level Decision Support Systems (DSS) has yet to be achieved. A coherent theoretical integration has not yet been developed. Methodology: The study takes a conceptual and design-based research approach in which the authors synthesize the modern literature on digital collaboration, knowledge management, leadership, and intelligent decision-support systems. Based on this, a knowledge-based, leadership-focused decision model is created. Contribution: The paper also proposes a reference architecture that serves as a layer of knowledge formation between eCoPs collaboration platforms and Intelligent Decision Support Systems (IDSS), facilitating two-way integration of tacit community insights and formal analytical models. In contrast to conventional data-based DSS models, the proposed model integrates socially constructed, practice-based knowledge into the decision-making process. Findings: The discussion shows that the systematic integration of knowledge generated by eCoPs makes decision-making more rational, helps address semi-structured and unstructured issues more effectively, and improves organizational learning and adaptive capacity. Recommendations for Practitioners: The eCoPs should be strategically institutionalized within organizations, supported by collaboration-enabling infrastructures coupled with decision systems, and embedded in leadership practices that encourage trust, openness, and the co-creation of knowledge. The model is especially relevant in SMEs and organizations undergoing digital transformation, where tacit knowledge is essential in strategic responsiveness. Recommendation for Researchers: In future research, the framework should be empirically tested in organizational settings, the governance and trust mechanisms of eCoPs-based decision systems should be studied, and the ways AI could be used to improve collaborative knowledge extraction and structuring should be identified. Impact on Society: The framework helps to make organizational decision-making more transparent, inclusive, and knowledge-based by formally integrating collective expertise into organizational decision systems. Future Research: Future research must use longitudinal and mixed-method designs to identify the quantifiable effects of eCoPs-created knowledge on decision quality and organizational performance, and to conduct cross-sector and cross-cultural comparisons. http://www.informingscience.org/Publications/5740 eCoPs; knowledge-driven systems intelligent decision support systems tacit and explicit knowledge organizational decision making collaborative intelligence eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-12-27 20 .i v 5420 article Table of Contents for Volume 20, 2025, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/5420 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-01-01 20 5406 article Kai Jin jinkai.kerry@gmail.com Md Kassim Normalini normalini_mk@yahoo.com Aim/Purpose: Chinese customers are now employing B2C E-Learning as a novel method to get an education. The issues of product homogenization, low user registration eagerness, and poor retention have become noticeable. The purpose of this research is to identify key elements that influence consumers’ intention to continue using E-Learning in China and to examine how user experience moderates the relationship between satisfaction and continuance usage intention (CUI) among users with varying levels of experience. The framework was built by including additional new factors into the Technology Continuance Theory (TCT) theory. Background: In the present day, B2C E-Learning is expanding quickly, and the E-Learning market is promising and has emerged as a new, widely recognized industry. The post-pandemic period and mobile Internet usage have powered the B2C E-Learning industry’s explosive growth. Nonetheless, post-pandemic research on B2C E-Learning is still in its early stages and lacks a complete framework. Methodology: The framework was built by including additional new factors into the TCT theory. A web-based survey was conducted among 493 E-Learning users in China. Structural equation modeling was conducted, and the results were examined using SPSS and SmartPLS. Contribution: This research significantly enhances the theory of TCT by incorporating previously unaddressed components (course trial, perceived cost, information quality, and service quality). The novelty of this study is that it focuses on brand-new technological factors and identifies key factors. Aside from theoretical implications, the research has several implications for designers, developers, companies, marketing personnel, and end-users. Findings: The results indicated satisfaction is the most significant predictor of continuance usage intention (CUI). Course trials and information quality were insignificant in terms of satisfaction, whereas there was a significant association between perceived cost, service quality, and satisfaction towards CUI. The experience did not moderate the relationship between satisfaction and CUI. The PLS-MGA results show that less experienced and more experienced users have no significant difference in continuance usage intention when they are satisfied. Recommendations for Practitioners: The research results have various implications for designers, developers, businesses, marketing representatives, and end users. Based on these determinants, organizations can develop more effective marketing strategies. Recommendation for Researchers: Researchers on this specific application can make use of the extension of the model. Researchers will have a comprehensive perspective on B2C E-Learning platforms through the holistic new research framework. Impact on Society: According to research, Chinese people use E-learning platforms for many reasons, including studying English and improving their personal lives. With this in mind, E-Learning platforms should include tools that allow users to manage their learning and lifestyle better. Future Research: Future research should employ longitudinal designs to better understand how users’ perceptions and behaviors evolve over time. Second, the use of a non-probability sampling technique and the focus on Chinese users limit the generalizability of the findings to other contexts. Future studies should replicate the proposed model in different cultural and educational settings to assess its external validity. http://www.informingscience.org/Publications/5406 E-Learning eLearning continuance usage intention course trial perceived cost information quality service quality satisfaction technology continuance theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-01-12 20 5423 article Abeer M. Azem Qashou p119381@siswa.ukm.edu.my Nurhidayah Bahar nbahar@ukm.edu.my Hazura Mohamed hazura.mohamed@ukm.edu.my Aim/Purpose: The primary goal of this research is to analyze the factors that influence the implementation of Mobile Cloud Computing (MCC) in Higher Education Institutions (HEIs). Background: Despite MCC’s benefits in lowering technology and administration costs, HEIs, particularly in developing countries such as Palestine, are skeptical and hesitant to use this technology. This research provides a model of MCC implementation based on the Technology-Organization-Environment framework (TOE) combined with the Diffusion of Innovation (DOI) model. Methodology: Data were collected through qualitative semi-structured interviews with a targeted sample of ten IT experts and professionals from Palestinian Higher Education Institutions (PHEIs) and local cloud service providers. The obtained data was examined using thematic analysis in the NVIVO software. Contribution: The findings can be used as a guide for introducing MCC in higher education settings. It will lead to a better understanding of MCC implementation by HEIs, which can help institutions harness the benefits and progress offered by MCC, enabling them to overcome challenges and enhance their operations. The study will provide valuable suggestions for the initial steps HEIs can take towards MCC implementation. Moreover, it will benefit cloud service providers, as it will enhance their understanding of the factors that influence MCC implementation in HEIs. This will help them tailor their services and solutions better to meet the unique needs and requirements of the higher education sector. Findings: The results show that data security risks, relative advantages, compatibility, complexity, top management support, competitive pressure, and cloud service provider support all have a substantial impact on MCC implementation. The interviewed IT specialists also proposed two new contributing factors (technology readiness and government support). Recommendations for Practitioners: The results are expected to aid decision-makers at HEIs and cloud service providers by focusing on the crucial role of the factors that appeared in the study. Recommendation for Researchers: It is recommended that researchers in future studies test the proposed model in settings and cultures different from the context in which this study was conducted. In addition, surveying the opinions of other stakeholders and adding other factors not included in the research are important to provide different perspectives and generalize the results. Impact on Society: Understanding the factors that influence the implementation of MCC in HEIs can enhance access to educational resources for both learners and teachers while promoting innovation in teaching and learning. Additionally, this understanding aids in the development of educational institutions, enabling them to contribute to societal progress by improving the quality of education and fostering global cooperation, ultimately leading to the advancement of society. Future Research: Examining the long-term effects of MCC implementation on educational outcomes, student performance, and institutional efficiency will offer valuable insights into the enduring advantages and possible limitations of these technologies. Future research should also investigate the impact of emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) in enhancing the functionality and effectiveness of MCC within educational environments. Furthermore, conducting comparative research across various regions and educational systems might help to identify the socioeconomic factors that influence MCC acceptance and implementation. http://www.informingscience.org/Publications/5423 mobile cloud computing cloud computing higher education diffusion of innovation technology-organization-environment eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-01-12 20 5430 article Md Kassim Normalini normalini_mk@yahoo.com Mohammed Rashed Mohamed Al Humaid Alneyadi Mohammed.alneyadi@student.usm.my Aim/Purpose: This research investigates factors influencing consumers’ decisions to use artificial intelligence cybersecurity technology in the United Arab Emirates. Background: The cyber-security risks are getting more complex as technology develops, putting the United Arab Emirates (UAE) businesses and government agencies at risk of severe losses from cybercrime. Methodology: A correlational study design and a quantitative research approach were employed, and 340 professionals working for different government and semi-government organizations in the United Arab Emirates were given questionnaires. The PLS-SEM approach was used to analyze the replies. Contribution: The present research framework remedies the inherent limitations in the PMT model by adding factors used to explain the influence of environmental factors and individual difference factors on behavior. This research framework is an extended application of the PMT model in the context of AI-based cybersecurity systems. Meanwhile, this study confirms the importance of perceived vulnerability in AI technology scenarios. Findings: The findings demonstrated that users’ adoption intentions were significantly and favorably impacted by social influence, facilitating conditions, perceived vulnerability, and perceived response efficacy. Meanwhile, job insecurity enhanced employees’ resistance to change, making resistance to change a major resistance to the intention to adopt AI-based cybersecurity systems. Recommendations for Practitioners: The report offers crucial insights that organizations can utilize to evaluate their readiness for adopting AI-based cybersecurity technologies and create plans to lessen employee resistance to advancements in the cybersecurity industry. Recommendation for Researchers: Researchers on this specific application can make use of the extension of the framework. Impact on Society: The research can be utilized to evaluate their readiness to adopt AI-based cybersecurity technologies. Future Research: Future research should broaden the scope to acquire a more thorough understanding of the behavioral intentions to use AI-cybersecurity systems in the United Arab Emirates. Other elements that could be considered include facilitating settings, Artificial Intelligence knowledge, social impact, effort efficacy, and other frameworks. http://www.informingscience.org/Publications/5430 artificial intelligence (AI) cybersecurity systems PMT intelligent systems cyber threats information security eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-02-05 20 5439 article Nuryani Nuryani yani98@gmail.com Rinaldi Munir rinaldi@informatika.org Ayu Purwarianti ayu@itb.ac.id Dessi Puji Lestari dessipuji@informatika.org Aim/Purpose: Most research on aspect-based sentiment analysis (ABSA) classifies sentiment polarity into two classes (positive and negative) or three classes (positive, negative, and neutral) and does not include conflict sentiment. This study investigates the four-class sentiment classification (positive, negative, neutral, and conflict) and proposes a BERT-based model for identifying conflicting sentiment in ABSA. Furthermore, we employ the open-source large language models (LLMs) created by Meta, Llama 3, for generating synthetic data to support research on four-class sentiment classification in ABSA. Background: Public opinions and experiences on product reviews, social events, political movements, etc. can be used for exploring customer behavior, predicting customer preferences, understanding public sentiment, etc., so it becomes an important component in the decision-making process. Providing an accurate opinion will enable an individual, business, or organization to have an in-formed judgement before making a decision. Methodology: This study utilizes a methodology that includes generating synthetic data to augment the original datasets, designing the input representation, detecting aspect categories, performing a multi-label sentiment classification, and rep-resenting sentiment in a four-class sentiment classification. Contribution: This study provides an investigation on the four-class sentiment classification (positive, negative, neutral, and conflict) and proposes a BERT-based method to identify aspects with conflicting sentiment in ABSA. Moreover, it also evaluates Llama 3 for generating synthetic data to address the issues related to the data scarcity and imbalance datasets in the research of four-class senti-ment classification in ABSA. Findings: The investigation of the four-class sentiment classification task in ABSA demonstrates that identifying conflict sentiment is challenging for several reasons. Among them are (1) the lack of a public dataset for this research; (2) the small amount of data with conflict labels in the available dataset resulting in an imbalanced dataset; (3) conflict sentiment is a complex sentiment con-taining both positive and negative sentiments; and (4) conflicting sentiments are usually expressed in long and complicated sentences and involve implicit aspects. Our solution to these challenges involved generating synthetic data using Llama 3 and designing a BERT-based model on multi-label aspects for identifying aspect with conflict sentiment. Recommendations for Practitioners: Most existing ABSA models with four-class sentiment classification are con-ducted for the product reviews (mostly in the restaurant domain) and in high-resource languages (mainly in English). Therefore, users may need to make some adjustments to different domains and languages. Recommendation for Researchers: Due to the limited datasets available for research in aspect-based sentiment analysis with four-class sentiment classification, the development of a dataset to support this research is urgently needed. Impact on Society: By providing more accurate sentiment through aspect-based sentiment analy-sis, this study can better help people, organizations, or companies in get a view or an opinion about any product, service, or candidate in an electoral vote. Future Research: Future research on aspect-based sentiment analysis could utilize the large language models (LLMs) for conducting ABSA tasks including aspect term extraction, aspect category detection, and its sentiment polarities. We could also focus on evaluating the model for cross-domain and cross-language AB-SA system. http://www.informingscience.org/Publications/5439 aspect-based sentiment analysis four-class sentiment classification conflict or conflicting sentiment pre-trained language models large language models eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-02-11 20 5438 article Cris Norman Patacsil Olipas olipas.cris@gmail.com Rose Anne G Cochanco ragcochanco28@gmail.com Aim/Purpose: The purpose of the study is to investigate the demographic profile, support levels, and sentiments of Information Technology students regarding a proposed dedicated comfort room for LGBTQIA+ members. By assessing student attitudes and support, the study aims to inform initiatives that promote inclusivity and address the needs of LGBTQIA+ individuals within the college community. Background: The background of the study highlights the growing recognition of the im-portance of inclusivity and support for LGBTQIA+ individuals in educational environments, particularly in the context of Information Technology programs. As colleges strive to create safe and supportive spaces for all students, the need for dedicated facilities like comfort rooms has emerged as a crucial aspect of fostering a welcoming atmosphere. This study seeks to explore the sentiments of IT students at the College of Information and Communications Technology regarding such a facility to better understand their perspectives and support levels Methodology: The methodology of the study employs a quantitative research design using a descriptive approach. A survey was administered to 508 Information Technology students across various year levels through a self-developed instrument via Google Forms. Sentiment analysis was conducted using a rule-based approach with Python programming and the TextBlob library, complemented by data visualization tools to effectively present the findings Contribution: This study contributes to the understanding of LGBTQIA+ inclusivity within educational settings by providing empirical data on the sentiments and support levels of Information Technology students regarding a dedicated comfort room. It highlights the demographic profile of the student population and emphasizes the importance of addressing their needs for safe spaces. The findings can in-form institutional policies and initiatives aimed at enhancing inclusivity, fostering a supportive environment, and guiding future research on LGBTQIA+ issues in higher education. Findings: The major findings of the study include 1. The surveyed IT students comprised 69.7% male, 21.9% female, and 8.4% identifying as LGBTQIA+ (including 1.8% lesbian, 1.0% transgender, 4.5% bisexual, 0.8% queer, and 0.4% other orientations). 2. A significant portion of respondents (36.2%) were aged 18 or younger, while 36.8% were between 19 and 20 years old. 3. A high level of support was reported, with 91.9% of students express-ing support for the LGBTQIA+ community. 4. Sentiment analysis revealed that 75.2% of responses were positive re-garding the proposed dedicated comfort room, 21.5% were neutral, and 3.4% were negative. 5. Word clouds highlighted prevalent terms and themes in the responses, reflecting the students' attitudes and concerns regarding the comfort room initiative. Recommendations for Practitioners: Practitioners are encouraged to enhance communication about the dedicated comfort room's purpose and benefits while engaging LGBTQIA+ students in the planning process to address their needs. Additionally, they should develop comprehensive inclusivity programs and ensure privacy and safety in the com-fort room design. Collaboration with campus organizations and ongoing evaluation of the initiative's impact will further promote a supportive environment for all students. Recommendation for Researchers: Researchers are encouraged to conduct further studies that explore the long-term impact of dedicated comfort rooms on the well-being and academic performance of LGBTQIA+ students. Additionally, future research could examine the effectiveness of various inclusivity programs in promoting a supportive environment within educational institutions. Expanding the scope to include comparative studies across different colleges may also provide valuable insights into best practices for fostering inclusivity Impact on Society: The study's findings highlight the importance of inclusivity for LGBTQIA+ individuals in educational settings, promoting a culture of acceptance and sup-port that can extend beyond the campus. By advocating for dedicated spaces like comfort rooms, the research contributes to broader societal efforts to address discrimination and enhance the well-being of marginalized communities. Ultimately, fostering inclusivity within educational institutions can lead to more equitable and understanding societies, encouraging positive change and collaboration across diverse groups. Future Research: Future research could focus on exploring the long-term effects of dedicated comfort rooms on the mental health and academic success of LGBTQIA+ students, assessing whether such initiatives lead to improved retention and engagement. Additionally, studies could investigate the effectiveness of various inclusivity programs across different educational institutions, identifying best practices that can be implemented more widely. Comparative research examining the experiences of LGBTQIA+ students in rural versus urban colleges could also provide valuable insights into the unique challenges and support needs of these populations. http://www.informingscience.org/Publications/5438 Dedicated Comfort Room Gender-Inclusive Spaces LGBTQIA+ SDG 5 Sentiment Analysis eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-02-18 20 5444 article Ahmad Nuh nuh@belgifoods.com Mohamad Rizan mohamadrizan72@unj.ac.id Andi Muhammad Sadat andims@unj.ac.id Aim/Purpose: This research aims to test the continued use of an AI platform through an extended Expectation Confirmation Model (ECM). Background: The paper addresses the issues of user trust and satisfaction in the context of an AI platform in education by employing the ECM to analyze how system quality, information quality, and user satisfaction influence continued use intentions among respondents from various educational institutions in Indonesia. Methodology: We utilized partial least squares structural equation modeling (PLS-SEM) to analyze data from 390 respondents. The analysis followed a two-step approach, focusing on measurement and structural models. The scales for system quality, information quality, confirmation, satisfaction, and continued use intention were adapted from established measures to fit the context of sustainable AI use. Contribution: The study identifies key factors such as system quality, information quality, satisfaction, and trust that influence continued use intentions. The findings show that satisfaction predicts trust more significantly than the reverse, suggesting that enhancing user satisfaction is key to fostering trust and encouraging ongoing engagement with an AI platform. Findings: Demographic analysis revealed a diverse sample, supporting the generalizability of our results. User satisfaction is identified as a stronger predictor of trust than vice versa, indicating that satisfied users are more likely to trust the AI platform, which is essential for continued use. Both system quality and information quality positively influence user satisfaction, which in turn leads to greater intentions to continue using the platform. Trust serves as a significant mediator between confirmation and continued use intention. Although confirmation itself does not directly impact satisfaction, it influences satisfaction through trust, ultimately affecting users’ intentions to continue engaging with the platform. Recommendations for Practitioners: Practitioners and policymakers should prioritize strategies that enhance user satisfaction with the AI platform, as this has been shown to significantly influence trust and intentions for continued use. Such strategies may include improving system usability, providing responsive customer support, and ensuring the relevance of AI outputs. Recommendation for Researchers: Future studies should investigate additional factors influencing user behavior with the AI platform, such as perceived ease of use, user demographics, and contextual variables in specific educational settings. Impact on Society: The findings of this paper have broader implications for integrating AI platforms across sectors, especially in education. By highlighting the importance of user satisfaction and trust, the research underscores the need for ethical AI development that prioritizes user experience. This can lead to more effective AI applications that enhance learning outcomes, promote equitable access to technology, and foster a more informed public discourse about AI’s role in society. Future Research: Future research should investigate the role of user experience by examining how various elements, such as interface design and personalization, influence satisfaction and trust in AI platforms. Additionally, understanding cultural influences is crucial, as it can reveal how cultural differences affect user perceptions and acceptance of AI platforms, particularly in diverse educational contexts. Lastly, evaluating the long-term effects of AI integration in education is essential, as this can provide insights into its impact on student engagement, learning outcomes, and overall satisfaction with educational technologies. http://www.informingscience.org/Publications/5444 AI platform satisfaction trust continued use intention Expectation Confirmation Model (ECM) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-02-22 20 5451 article Arfah Piliang arfahpiliang22@gmail.com Meutia Meutia tia_almer@yahoo.co.id Elvin Bastian elvinbas69@untirta.ac.id Munawar Muchlish muchlishmunawar@gmail.com Aim/Purpose: This study investigates how external stimuli and organizational culture influence the development of a management control system (MCS) to foster radical innovation and improve organizational performance. Specifically, it quantifies the effects of constraining and enabling levers on interaction and Knowledge sharing while examining how radical innovation mitigates technological turbulence to enhance performance. Background: This research was conducted on startup companies because many of them are closed due to a lack of visibility into the external environment and organizational culture in creating control system management and a lack of creation of radical innovation. Methodology: This quantitative research includes 329 respondents who are managers at startup companies in Indonesia. Questionnaires were distributed to respondents at startup enterprises to conduct the study. Data collection was performed both in person and online. SEM-PLS was the instrument employed for the measurement. Contribution: Startups are often in a dynamic environment with high uncertainty. This research offers insights into managing external influences and building an organizational culture that supports Knowledge and innovation to improve performance. The research can also provide input for policymakers, such as governments or business incubators, to create policies that support startup growth, especially in the face of technological challenges. Findings: Sampling 329 startup managers from Indonesia, this quantitative research was conducted using a structured self-administered questionnaire, and the data was analyzed through SEM-PLS. The results show that external stimuli and organizational culture significantly influence the establishment of the MCS and foster the ability of the startup to respond to drastic changes in the environment. This system encourages the promotion of knowledge sharing, which brings about radical innovations that increase market share and improve organizational performance. Interestingly, the analysis shows that enabling and constraining levers, knowledge sharing, and radical innovation are the factors that determine 76.9% (R² = 0.769) of organizational performance. Recommendations for Practitioners: Innovation remains the company’s main focus, and startups need to consider external stimuli, cultivate an organizational culture that supports innovation, and change the management control system so that the company can take advantage of fundamental changes and achievements, especially during the technological revolution. Recommendation for Researchers: Research has the potential to simultaneously add variables such as leadership style, employee engagement, or market orientation to observe how they affect innovation and organizational performance. The study may encompass startups and other marketplaces, including large technology firms, small and medium-sized enterprises, and the creative sector, to ensure consistency in findings across diverse settings. Impact on Society: With the improvement of the performance of startup organizations, people can enjoy high-quality products or services at more competitive prices. More innovative and well-performing startups will drive business growth, directly creating new job opportunities in various sectors. In addition, the growing emphasis on innovation means that people will be motivated to gain technological and creative skills, which in turn improves workforce efficiency. Future Research: Further research could examine how changes in government policies, such as implementing digital taxes or restrictions on foreign investors, affect the interaction between radical innovation and a company’s performance. Future researchers may also focus on the impact of blockchain technology on the creation of facilitating mechanisms for improving performance and innovation in technology-based startups. http://www.informingscience.org/Publications/5451 external stimuli organizational culture enabling levers constraining levers knowledge sharing radical innovation technological turbulence performance organization eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-03-06 20 5455 article Vignesh U vignesh.u@vit.ac.in Aman Amirneni aman.amirneni2022@vitstudent.ac.in Aim/Purpose: The study aims to develop a multilingual healthcare assistance chatbot that provides real-time, accurate answers to a query related to health matters in multiple languages. Conversion of written responses into spoken words lets users have the medical information necessary for them without interrupting communication between patients and health services. The purpose of this system is to break the language barriers for healthcare users, making it easier for them to access vital medical advice and resources. Background: This research focuses on fine-tuned large language models (LLMs) for providing accurate, context-aware responses in multiple languages with speech-based output. The chatbot, built on pre-trained Hugging Face models and fine-tuned with healthcare datasets, demonstrates a comprehensive understanding of medical terminology, symptoms, and healthcare concepts across languages. Unlike many existing chatbots that offer limited medical knowledge or support only a single language, the proposed chatbot leverages fine-tuning on a specialized medical corpus to deliver more accurate, context-rich responses. Furthermore, it provides text-based and speech-based outputs, improving user engagement and accessibility compared to text-only models. Methodology: A multilingual healthcare assistance chatbot is proposed using the pre-trained model aboonaji/llama2finetune-v2 and the specialized medical dataset aboonaji/wiki_medical_terms_llam2_format from Hugging Face. Key steps in the methodology include cleaning and normalizing medical terms, symptoms, and treatment advice to ensure uniformity across multiple languages. The model is fine-tuned on this healthcare dataset, enabling accurate and context-sensitive responses. Text-to-speech (TTS) technology is integrated to provide natural-sounding, voice-based answers, enhancing accessibility. Multilingual capability is ensured through modules for smooth language transitions. The chatbot is deployed on an intuitive web or mobile platform, simplifying user interaction. Performance metrics, including response accuracy, linguistic consistency, and user satisfaction, continuously improve through feedback and periodic updates with evolving medical knowledge and language models. Contribution: This research adds value to the medical sector by maximizing access to healthcare information across heterogeneous linguistic groups. It uses advanced natural language processing techniques and text-to-speech technology, facilitating quick and efficient interaction between patients and health providers. This allows users to follow crucial medical advice and information in their preferred language, thus promoting greater patient understanding and engagement. The output of the accurate, context-sensitive responses to healthcare search terms given by the chatbot assists in bridging the gap between patients and medical resources to make informed decisions for better overall health literacy. This model works as an instrumental instrument in solving language barriers in healthcare by introducing inclusiveness and promoting a stronger case for equality in healthcare. Findings: Results indicate that the chatbot effectively addresses language gaps in healthcare by generating contextually accurate and relevant responses to medical queries with excellent quality and reliability. Performance metrics demonstrate a BLEU score between 0.8 and 0.9, a perplexity score of 80.45, and an average latency of 20 seconds, highlighting robust translation accuracy, coherent response generation, and reasonable interaction time. Text-to-speech integration enhances accessibility and user engagement, while high user satisfaction confirms its potential to improve health literacy and patient comprehension. Continuous feedback during testing has enabled iterative refinements, ensuring the chatbot remains a reliable and inclusive tool for medical information delivery. Recommendations for Practitioners: Clinical practitioners should also encourage the adoption of the multilingual healthcare assistance chatbot in their clinical settings to enhance engagement and communication with the patient. This will enable healthcare providers to effectively bridge the language gap to provide patients with the exact health information they wish to receive in the language. The practice should encourage the different patient populations to use the chatbot and assist them in seeking information confidently. Recommendation for Researchers: It would be great to challenge this multilingual medical assistance chatbot through further research, for example, testing in other languages and improving its natural language processing properties to provide users with accurate medical answers. This study should be followed by further studies measuring the extended effects of chatbots on health literacy and patient outcomes in different healthcare settings. Collaboration in design with healthcare professionals will provide insights into user needs and ensure the chatbot remains practical and meaningful. Additionally, artificial intelligence and machine learning could enhance the learning of the interactions from the interactions with the chatbot, thus enhancing its effectiveness over time. These efforts can significantly advance technology in healthcare communication and patient support. Impact on Society: A multilingual health assistance chatbot can greatly affect society by giving diverse populations easy access to essential health information. It bridges the language barrier gaps, enabling individuals of many linguistic backgrounds to gain self-confident medical advice and information, thus furthering health literacy and informed decision-making. That enables better healthcare because the patients will be able to understand what might be wrong with them and likely to comply with some prescriptions made for the treatment. In addition, the chatbot encourages egalitarian healthcare because it allows for the inclusion of marginalized groups of society to be treated equally. At the same time, there should still be an equal occurrence in the healthcare system. This means, in turn, that the chatbot does not only enhance individual results in health but also community health at large because it is sure to encourage proactive engagement with the services and healthcare resources. Future Research: Future research may focus on expanding the knowledge database for the chatbot by incorporating many languages and dialects. It could also work on perfecting the natural language processing to interpret complex medical-related queries better. The integration of more advanced techniques of artificial intelligence may also further enhance the learning abilities of chatbots from user interactions and sharpen their response across time cycles. http://www.informingscience.org/Publications/5455 multilingual healthcare chatbot text-to-speech technology natural language processing health literacy language barriers patient engagement fine-tuning pre-trained model healthcare information eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-03-25 20 5469 article Anh Hoang Tuan Tran anhtran.31231024605@st.ueh.edu.vn Tuan Manh Nguyen tuannm@ueh.edu.vn Tam-Thanh Luong lthanhtam915@gmail.com Vi-Gia Luong Luonggiavi91827@gmail.com Aim/Purpose: Previous studies have primarily focused on comparing predictive models without considering the impact of data preprocessing on model performance. Therefore, this study sets two main objectives. The first objective is to investigate the effect of resampling methods for handling imbalanced data on model effectiveness. The second objective is to compare and evaluate machine learning methods to identify the optimal model for each resampling technique, thereby determining the model that achieves the highest performance. Background: In the highly competitive banking industry, attrition of customers is a major challenge for banks trying to improve customer retention. While many studies have focused on building and evaluating models to predict customer churn, they often miss addressing the problem of imbalanced data, which can significantly affect the model’s accuracy. Methodology: In this study, following exploratory data analysis (EDA), we apply various techniques to address data imbalance and use a range of machine learning models, including Naïve Bayes, Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting, XGBoost, and LightGBM, to predict customer churn using the dataset. Contribution: The contribution of this research lies in its comprehensive evaluation and comparison of various techniques for handling imbalanced data in churn prediction models. The study identifies SMOTE-ENN as the most effective method for resampling imbalanced data. Among the models tested, LightGBM (accuracy = 0.979) achieves the highest performance based on evaluation metrics. Additionally, the research highlights that tree-based machine learning models generally perform better when trained on imbalanced datasets. Findings: Tree-based and ensemble models perform better than regression and probability-based methods when dealing with imbalanced data. SMOTE-ENN has been shown to improve the performance of machine learning models greatly. Recommendations for Practitioners: Practitioners can deploy high-performance models, such as XGBoost and LightGBM, combined with effective resampling methods like SMOTE-ENN to predict customer churn in banking, marketing, and human resources. Recommendation for Researchers: To optimize the predictive model in the study, researchers can focus on feature selection, dimensionality reduction, or hyperparameter tuning. Impact on Society: Customer churn reduces revenue and threatens competitive advantage, so businesses need effective retention strategies to maintain sustainable growth. High-performance customer churn prediction models can be an effective solution to address this issue. Future Research: Deploy the model on real-world datasets while further optimizing the feature selection process and hyperparameter tuning, combined with SHAP values analysis to identify key features that significantly influence the model’s predictions. http://www.informingscience.org/Publications/5469 churn prediction machine learning imbalanced data classification models oversampling undersampling hybrid method banking industry eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-04-09 20 5476 article Narongsak Sukma narongsaks@siamtechno.ac.th Wachiranun Pum wachiranun@npu.ac.th Aim/Purpose: Traditional research methodology education faces challenges in developing student self-efficacy and integrating modern technology, necessitating innovative instructional approaches for graduate students. Background: This study introduces the BEST model (begin with learner analysis, establish clear learning objectives, select engaging learning activities, and tailor instruction using technology) to address these challenges through systematic TPACK integration. Methodology: A qualitative investigation was conducted with 10 graduate students through focus groups and in-depth interviews over one month, analyzed using narrative and content analysis approaches. Contribution: Content analysis revealed improvements in self-efficacy (from four to eight participants), peer learning (from three to six), and critical thinking (from three to six) while maintaining active learning engagement throughout implementation. Findings: Students showed significant improvements in self-efficacy (four to eight participants), peer learning (three to six), and critical thinking (three to six) while maintaining active learning engagement. Recommendations for Practitioners: Institutions should implement robust technical support systems and flexible learning pathways while ensuring adequate infrastructure before adoption. A phased implementation approach with peer mentoring is recommended to address technology integration challenges. Recommendation for Researchers: Future research should examine the BEST model’s effectiveness across different cultural contexts and disciplines through comparative and longitudinal studies while exploring the integration of emerging educational technologies. Impact on Society: The BEST model enhances the quality of graduate research education by developing students’ confidence and competence, potentially leading to more capable researchers and improved research outcomes. Future Research: Longitudinal studies should track the impact on research productivity and quality, while mixed-methods approaches incorporating standardized measures would strengthen the empirical foundation for the model. http://www.informingscience.org/Publications/5476 instructional design TPACK integration research methodology graduate education self-efficacy eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-05-05 20 5479 article Xuefeng Zhang xfzhang1987@ahpu.edu.cn Xinyu Qiu 550885455@qq.com Aim/Purpose: This study employs the Elaboration Likelihood Model (ELM) to investigate how six metainformational cues – number of updates, founder’s experience, media usage, number of investors, project text length, and psychological capital language – influence crowd-funding success. Background: Metainformational cues are essential information for demonstrating a crowdfunding project and play a critical role in investors’ investment decision-making. While prior research has focused on intrinsic project information, the role of supplementary metainformational cues remains underexplored, particularly through the lens of dual-processing theories like ELM. Methodology: This study collected data from 188 crowdfunding projects from Kickstarter, a popular crowdfunding platform. A regression analysis was conducted to test relations between the six metainformational cues and crowdfunding success through the central and peripheral routes. Contribution: Our research findings extend ELM’s application to crowdfunding, demonstrating how intuitive cues reduce investor uncertainty and drive decisions. Moreover, the study advances crowdfunding literature by empirically validating a novel framework that bridges metainformation and persuasion theory, offering actionable insights for founders and platforms. Findings: Regression analysis reveals that central route metainformational cues including the number of updates, founder's experience, and use of media are positively correlated with crowdfunding success. The three metainformational cues on the peripheral route, i.e., number of investors, project text length, and psychological capital language, also have a positive relationship with crowdfunding success. Recommendations for Practitioners: Founders should prioritize frequent updates, integrate multimedia (e.g., videos/images), and highlight past successes to build trust. Investors can rely on crowd signals (e.g., backer counts) as decision heuristics. Recommendation for Researchers: Researchers could deepen the theoretical framework and combine the ELM with signal theory to explore the dynamic interaction effects of metainformational cues, explore cultural differences in the effectiveness of cues, and use advanced natural language processing (NLP) for language analysis. Impact on Society: The findings empower underrepresented entrepreneurs, simplify investment decisions for novices, and promote transparent crowdfunding ecosystems, potentially boosting economic innovation. Future Research: Future research can track investor browsing behavior through eye-tracking experiments, identify real-time switching mechanisms between central and peripheral routes, test sustainability-related cues (such as Environmental, Social, and Governance statements), and validate results on non-western platforms (such as Taobao). http://www.informingscience.org/Publications/5479 crowdfunding metainformational cues ELM eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-05-20 20 5497 article Mengting Xi java_mc@163.com Huanyu Cheng chenghuanyu2020@163.com Yincheng Gu 583878324@qq.com Qiuyuan Zhong 2477939299@qq.com Liu Wei 1617880313@qq.com Aim/Purpose: This study aims to address the knowledge conflict issues encountered in multi-agent collaboration, particularly when agents based on large language models (LLMs) provide inconsistent answers or recommendations due to varied knowledge sources or errors caused by hallucinations. Background: The paper tackles the limitations of intelligent agents that cannot dynamically detect or resolve knowledge conflicts. The accuracy of agent responses is enhanced by introducing an automated conflict detection and resolution method. Methodology: We propose a Knowledge Conflict Resolution (KCR) method that leverages prompt engineering and fine-tuned LLM agents for conflict detection and resolution. The method is evaluated in task-oriented dialogue scenarios, comparing it against baseline models in terms of consistency, task success rate, and user satisfaction. Contribution: This study proposes a novel approach to detecting knowledge conflict in intelligent agents. Our innovative approach offers three key advantages over existing solutions: Higher Accuracy: Achieves 97.3% conflict detection rate compared to 85-91% in current methods. User-Friendly Design: Simplifies complex coordination between agents without technical expertise. Practical Implementation: Works effectively across different LLM platforms without requiring system overhauls. Findings: Experimental results show that our KCR method significantly outperforms existing approaches in resolving conflicts and maintaining coherent multi-agent conversations, notably improving user-perceived reliability. Recommendations for Practitioners: Incorporating conflict detection mechanisms in intelligent agents can improve knowledge management and enhance user satisfaction, particularly in knowledge-intensive industries. Recommendation for Researchers: Ensuring the consistency and accuracy of knowledge from different sources is crucial. This paper proposes an effective knowledge conflict detection method to enhance the consistency of knowledge. Impact on Society: Enhances the reliability and accuracy of intelligent agents in professional fields, facilitates organizational knowledge consistency, and promotes the practical adoption of large language models in complex scenarios. Future Research: Future research should broaden the scope of this method to include English, investigate its applicability in multimodal large models, and further develop strategies to ensure organizational knowledge consistency in intelligent agents. http://www.informingscience.org/Publications/5497 intelligent agent large language model knowledge conflict ChatGPT eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-05-20 20 5485 article Betty Purwandari bettyp@cs.ui.ac.id Shabrina Salsabila Kurniawan shabrina.salsabila21@ui.ac.id Imairi Eitiveni imairi@cs.ui.ac.id Erisva Hakiki Purwaningsih erisvaha.kiki@ui.ac.id Aim/Purpose: This study analyzed the factors influencing electronic word-of-mouth (e-WOM) intention and purchase intention among Shopee users toward stores with Star Seller status, including the mediating roles of cognitive and affective appraisal. It integrated Customer Value Theory, Social Learning Theory, and Perceived Value Theory to examine how perceived benefits influence user behavior. The study also aimed to provide empirical evidence on the advantages of Star Seller status and to educate sellers on how this status can enhance their business performance on Shopee. Background: Shopee is one of Indonesia's most widely used e-commerce platforms, where store status signals seller credibility. Among these, the Star Seller status offers multiple benefits. However, many sellers hesitate to pursue this status due to the associated administrative fees. A decline in the number of Star Seller stores may result in fewer offers for users, prompting them to compare and potentially switch to other platforms. This research sought to demonstrate the positive impact of Star Seller status on user behavior and reduce seller resistance through education. Methodology: The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data from an online survey of 452 Shopee users. The analysis tested relationships between perceived value dimensions (emotional, functional, and price), cognitive and affective appraisal, and behavioral intentions such as purchase and e-WOM. Contribution: Theoretically, the study offered a novel integration of Customer Value Theory and Social Learning Theory within Shopee’s Star Seller context to explain user behavior in e-commerce. Practically, it provided evidence-based insights for Shopee and its sellers, showing how Star Seller status can influence trust, purchase intention, and recommendations. Findings: The findings revealed that emotional, functional, and price value significantly influenced purchase and e-WOM intentions. Cognitive and affective appraisal mediated these relationships, with cognitive appraisal having a more substantial effect. These results highlight the critical role of Star Seller status in shaping user perceptions and behaviors, offering tangible benefits for sellers. Recommendations for Practitioners: Sellers should be educated on the benefits of Star Seller status to reduce reluctance and increase participation. Shopee is encouraged to strengthen communication on the unique advantages of Star Seller status, such as better service quality and exclusive promotions, to boost user engagement and seller adoption. Recommendation for Researchers: Future studies can explore additional perceived value dimensions and their influence on user behavior. Longitudinal and cross-platform comparisons can also provide deeper insights into the long-term effects of seller status on user retention and loyalty. Impact on Society: By promoting Star Seller adoption, this research may enhance user satisfaction and support sustainable e-commerce growth in Indonesia. The findings contribute to the broader e-commerce ecosystem by encouraging trust and improving platform efficiency. Future Research: Comparative studies between Star Seller and non-Star Seller stores across various platforms and investigations into cultural and social influences on perceived value are recommended. Longitudinal research may also reveal the long-term impact of seller status on loyalty and business growth. http://www.informingscience.org/Publications/5485 perceived value customer value theory purchase intention e-WOM intention seller education PLS-SEM Shopee Star Seller eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-05-20 20 5499 article Wiwin Suwarningsih winak03@gmail.com Ratna Santi ratna.s.kardi@gmail.com Ashwin Sasongko Sastrosubroto ashwin.sasongko@gmail.com Aim/Purpose: The study aimed to develop an automated, real-time monitoring system using YOLOv8 to detect the use of safety helmets in factories, thereby improving workplace safety and compliance. Background: Industrial safety, particularly in factories, is critical for preventing workplace accidents. The detection of safety helmets is an essential component of factory safety protocols; however, manual monitoring can be inefficient and prone to error. This study applies YOLOv8, a state-of-the-art object detection algorithm, to enhance monitoring efficiency by automating the detection process, particularly in challenging conditions such as low-light environments and dynamic settings. Methodology: The YOLOv8 model was trained on a comprehensive dataset of helmet images captured in various industrial settings, encompassing different lighting conditions, angles, and helmet types to ensure the model’s robustness. The system was designed to detect the presence or absence of helmets in real time using video footage. Performance metrics, including precision, recall, and accuracy, were utilized to evaluate the model’s effectiveness, with a focus on addressing the unique challenges of real-world applications. Contribution: This research contributes to the field of industrial safety by offering an automated and scalable solution for real-time helmet detection. The system significantly reduces the need for human intervention in monitoring safety compliance and provides an efficient mechanism for alerting supervisors about safety violations. Findings: The results indicated that the YOLOv8-based detection system achieved high accuracy in real-time helmet detection, even under challenging environmental conditions. The system successfully identified instances of non-compliance, allowing for timely corrective actions. Additionally, the model demonstrated low false-positive and false-negative rates. Statistical significance testing revealed that the model’s performance metrics, including sensitivity and specificity, showed significant improvements compared to previous versions and traditional methods (p < 0.05), underscoring the robustness of YOLOv8 in dynamic factory conditions. Recommendations for Practitioners: Factory managers and safety officers are encouraged to implement this system to enhance safety oversight, reduce the risk of accidents, and streamline the monitoring process without requiring extensive human resources. Recommendation for Researchers: Further research could focus on integrating additional safety features, such as detecting other protective gear (e.g., gloves, goggles), and expanding the dataset to include more diverse industrial environments. Impact on Society: Enhancing safety protocols in industrial settings has the potential to significantly reduce workplace injuries, leading to safer working environments and greater compliance with safety regulations. Future Research: Future research may explore the integration of this system with Internet of Things (IoT) devices for broader safety monitoring and the application of YOLOv8 in detecting other safety hazards beyond helmet use. http://www.informingscience.org/Publications/5499 safety helmet detection object detection area monitoring computer vision eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-05-28 20 5515 article Akshatha Shetty akshathashetty@stagnescollege.edu.in Dr. Manjaiah D H drmdhmu@gmail.com Praveena Kumari M. K. narayan.praveena@gmail.com Aim/Purpose: The need for this paper stems from the challenge of efficiently analyzing large volumes of customer reviews in the hotel industry, which is growing and complex due to the widespread use of digital platforms. With consumers increasingly sharing feedback across various social media applications, manual processing becomes impractical, necessitating machine learning algorithms for accurate sentiment analysis and prediction. Background: This paper addresses the problem by applying machine learning algorithms, specifically fine-tuned bidirectional GRU with FastText embedding, to perform location-based sentiment analysis and prediction of customer reviews in the hotel industry, providing an efficient solution to process large-scale unstructured data and extract valuable insights for improving customer experience. Methodology: This study employs machine learning techniques, including Random Forest (RF), Support Vector Machine (SVM), Bidirectional Long-Short Term Memory (BiLSTM), and Bidirectional Gated Recurrent Unit (GRU), to perform sentiment analysis on customer reviews in the hotel industry. The paper focuses on using a fine-tuned bidirectional GRU model with FastText embedding for location-based sentiment analysis and prediction. The research sample consists of a large dataset of customer reviews, which are processed and analyzed to predict sentiment and evaluate model performance, achieving an overall score of 84.31%. Contribution: This paper contributes to the body of knowledge by demonstrating the effective application of advanced machine learning algorithms, particularly a fine-tuned bidirectional GRU with FastText embedding, for sentiment analysis in the hotel industry. It offers a unique approach to location-based sentiment analysis, allowing for a deeper understanding of regional variations in customer perceptions. The study also provides insights into the comparative effectiveness of different machine learning models for sentiment classification and prediction by comparing multiple algorithms. This work enhances the existing methodologies for processing large-scale, unstructured data and highlights the potential of sentiment analysis to drive data-informed strategies in customer-centric industries. Findings: The study found that the fine-tuned bidirectional GRU model with FastText embedding achieved an accuracy of 84.31%, outperforming other algorithms in sentiment classification. It highlighted the effectiveness of location-based sentiment analysis for understanding regional variations in customer perceptions. The approach also demonstrated strong predictive capabilities, aiding data-driven decision-making in the hospitality sector. Recommendations for Practitioners: Practitioners in customer-focused sectors, particularly hospitality, should consider using advanced models like the fine-tuned bidirectional GRU with FastText embedding for precise sentiment analysis. This approach helps capture regional customer preferences, allowing for tailored services. Integrating sentiment insights with real-time data can further enhance responsiveness to customer needs, supporting data-driven improvements in customer satisfaction. Recommendation for Researchers: Researchers should investigate more advanced models and varied datasets to enhance sentiment analysis accuracy and applicability. Extending sentiment analysis to fields like healthcare and finance could offer broader insights into consumer behavior. Additionally, integrating sentiment analysis with real-time data sources, such as social media, may yield more dynamic predictive models and reveal key regional trends. Impact on Society: The findings of this paper have significant implications for industries, particularly in the hospitality sector, as they provide an effective method for analysing customer sentiment at a granular level. The ability to assess customer opinions through sentiment analysis can help businesses improve customer service, tailor their offerings to meet customer needs, and enhance the overall customer experience. Additionally, location-based sentiment analysis can enable businesses to understand regional differences, allowing for more personalized marketing strategies and better resource allocation. Future Research: Future research could focus on improving the accuracy and efficiency of sentiment analysis models by incorporating more advanced deep learning techniques and larger, more diverse datasets. Exploring the application of sentiment analysis in other sectors, such as healthcare, education, and finance, could provide broader insights into customer perception. Additionally, integrating sentiment analysis with other data sources, such as social media and customer feedback, may lead to more comprehensive and real-time prediction models. Further directions include multilingual sentiment analysis, the use of transformer-based models, and deployment in resource-constrained environments. http://www.informingscience.org/Publications/5515 sentiment analysis bidirectional GRU fast-text embeddings location eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-06-02 20 5491 article Nimasha Arambepola nimasha@kln.ac.lk Waruni Lalendra Wimalasena rawlw241@kln.ac.lk Lankeshwara Munasinghe l.munasinghe@rgu.ac.uk Aim/Purpose: This paper focuses on app review analysis techniques, driven by the rapid advancement of the mobile app market and NLP techniques in optimizing mobile app user experiences. Background: Owing to technological advancements, app review analysis has rapidly evolved. This study examines both conventional and emerging techniques, including current advancements such as large language models (LLMs) in app review analysis. It provides an overview of the various methods used across different categories of app review analysis, comparing effective strategies for identifying user concerns and enhancing app functionality. Methodology: A systematic review was utilized based on two major standard guidelines, PRISMA and Kitchenham’s guidelines, for the period of 2014 to 2024. After defining the review protocol, papers were identified through keyword-based searches on six major online databases: Scopus, Web of Science, IEEE Xplore, ACM Digital Library, Science Direct, and Springer. Following screening and excluding papers based on defined quality criteria, 53 papers were considered for this study. The use of PRISMA ensures a transparent and reproducible review process, while Kitchenham’s guidelines provide a structured and rigorous approach for evaluating and synthesizing the literature. Contribution: This review study aims to evaluate the current state of knowledge on app review analysis techniques to improve mobile app user experiences. This study categorized the existing state-of-the-art papers into eight different categories, such as sentiment analysis, review classification, summarization, and prioritization, and examined challenges related to app review analysis. Furthermore, the study emphasizes the potential of LLMs for optimizing and automating app review analysis and provides future directions to address gaps in user-centric app development. Findings: Among the eight main categories defined in app review analysis, sentiment analysis is the most prevalent, followed by review classification and information extraction. Most studies use a combination of these categories to achieve a comprehensive goal. Prioritization techniques such as risk matrices, thumbs-up count-based approach, and anomaly detection are widely used to identify emerging issues. Extracting meaningful information and evaluating the proposed approach are the most common challenges identified. Novel LLMs, like Chat-GPT, significantly enhance review analysis by automating the process, improving feature extraction, and enabling context-aware review classification. Recommendations for Practitioners: The combination of conventional approaches and novel LLM-based methods can enhance both the efficiency and accuracy in identifying and addressing critical issues raised through mobile app user reviews. It effectively prioritizes user concerns by leveraging the strengths of both traditional preprocessing techniques and advanced LLMs. Recommendation for Researchers: Researchers are encouraged to explore the integration of emerging technologies like LLMs to enhance the of app review analysis, particularly in feature-specific sentiment analysis. Impact on Society: The results of this study contribute to enhancing the mobile app user experience through effective app review analysis, which improves user satisfaction and supports user-centered app development. This ultimately leads to a better mobile app ecosystem, benefiting both users and developers. Future Research: In the future, this research can be extended in multiple directions. Researchers can address the existing research gaps that LLMs have yet to address, particularly in prioritizing user concerns. Additionally, there is potential for further research on tool implementations focusing on identifying persistent issues through time series analysis by considering the app version and date of the app reviews. Moreover, there is a need to develop comprehensive frameworks that are more generalizable across different apps and categories, with a focus on identifying user concerns related to specific features. http://www.informingscience.org/Publications/5491 app user reviews text analysis LLM user experience systematic review eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-06-23 20 5537 article Majzoob K. Omer mkomer@bu.edu.sa Aim/Purpose: This study aims to develop and assess a speed monitoring system that enforces continuous compliance with speed regulations on highways by calculating average vehicle speed between two fixed cameras. Background: Unlike traditional point-based enforcement methods, this approach ensures continuous speed monitoring over an extended distance, reducing the possibility of speed manipulation by drivers. Methodology: The proposed system employs mathematical models to calculate average vehicle speed by considering factors such as acceleration, air resistance, and environmental road conditions. To assess its performance, a computer-based simulation was conducted, simulating vehicle movements across a predefined highway segment. The simulation incorporated various driving behaviors and environmental conditions to evaluate the system's accuracy and reliability in detecting speed violations. Due to resource constraints and ethical considerations regarding real-world testing of enforcement systems, this study primarily relies on simulated data, with limitations clearly acknowledged throughout the methodology section. Contribution: This research contributes to the field of intelligent transportation systems by addressing limitations of conventional approaches and leveraging technological advancements to develop more effective interventions for reducing speed-related accidents. Findings: The simulation results demonstrate that the proposed system significantly outperforms traditional point-based enforcement across all key performance metrics, achieving higher measurement accuracy and violation detection rates. Recommendations for Practitioners: Transportation authorities should consider implementing average speed enforcement systems on highways with high accident rates, as they promote more consistent driving behavior and eliminate the "kangaroo effect" commonly observed with point-based enforcement. Recommendation for Researchers: Future research should focus on field implementation and validation, advanced vehicle identification methods, behavioral impact studies, and integration with emerging vehicle technologies. Impact on Society: By encouraging consistent compliance with speed limits, the system could significantly reduce speed-related accidents and fatalities, alleviate pressure on emergency medical services, decrease fuel consumption and emissions, and promote equitable enforcement. Future Research: Further investigation is needed into real-world implementation, enhanced vehicle identification techniques, long-term behavioral impacts, integration with connected vehicle technologies, and comprehensive cost-benefit analyses. http://www.informingscience.org/Publications/5537 speed monitoring average speed enforcement (ASE) intelligent traffic systems speed cameras highway speed enforcement vehicle speed detection real-time traffic monitoring traffic enforcement technology eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-07-07 20 5525 article I Gede Susrama Mas Diyasa igsusrama.if@upnjatim.ac.id Eva Yulia Puspaningrum evapuspaningrum.if@upnjatim.ac.id Dimas Saputra 21081010151@student.upnjatim.ac.id Wan Suryani Wan Awang suryani@unisza.edu.my Aim/Purpose: The purpose of this paper is to address the gap in the recognition of prior learning (RPL) by automating the classification of non-formal learning certificates using deep learning techniques. This study aims to evaluate the effectiveness of different text augmentation strategies—character-level, token-level, and semantic-level—in improving the classification accuracy of these certificates, which are crucial for bridging the skills gap in the digital economy. Background: Traditional education systems often overlook skills gained through non-formal learning, creating a gap between industry needs and academic qualifications. This paper addresses this by using BERT-based deep learning models to classify non-formal learning certificates, enhanced by text augmentation techniques to improve accuracy in mapping them to formal academic standards. Methodology: This study employs a deep learning approach using Bidirectional Encoder Representations from Transformers (BERT) to classify non-formal learning certificates into seven core computer science courses. The research utilizes text augmentation techniques at character, token, and semantic levels to improve classification accuracy. A dataset of 525 certificates, collected through data gathering, was preprocessed using Optical Character Recognition (OCR) to extract text from PDF documents, followed by cleaning and augmentation before training the BERT model. Contribution: This paper addresses the growing need for efficient Recognition of Prior Learning (RPL) in the context of rapidly advancing knowledge, particularly in the AI era, where non-formal learning is becoming increasingly important. We present a novel approach to automating the classification and validation of non-formal learning certificates using deep learning techniques. The study evaluates and compares character-level, token-level, and semantic-level text augmentation methods to improve the accuracy of certificate classification. What sets this research apart is the systematic assessment of which augmentation method best enhances model performance for RPL tasks, providing new insights into optimizing deep learning models for this purpose. The findings aim to reduce human error and improve the efficiency of RPL implementation, offering a scalable solution for better integrating or converting non-formal learning into formal educational systems. Findings: The study found that token-level augmentations, particularly word insertion and word deletion, significantly improved classification accuracy, with validation accuracies exceeding 88%. Character-level augmentations also contributed to model performance, but with slightly lower accuracy. Semantic-level augmentation via back translation showed the least impact. These results demonstrate that token-level text augmentations offer the most effective strategy for enhancing the classification of non-formal learning certificates in the context of Recognition of Prior Learning (RPL). Recommendations for Practitioners: Practitioners should focus on token-level text augmentation techniques, like word insertion and deletion, to improve the accuracy of machine learning models for classifying non-formal learning certificates, enabling better integration into formal education and employment pathways. Recommendation for Researchers: Researchers should explore combining multiple augmentation techniques (e.g., token-level and semantic-level) and investigate advanced models like BERT-large or multilingual variants for improved classification accuracy. Additionally, examining the impact of different OCR tools and preprocessing strategies could further enhance non-formal learning certificate recognition. Impact on Society: The findings of this study have significant implications for improving access to education and employment opportunities. By enhancing the recognition of prior learning through automated classification of non-formal learning certificates, this research supports a more inclusive and equitable education system. It can help individuals, particularly those with non-traditional educational backgrounds, gain recognition for their skills, ultimately bridging the skills gap in the workforce and promoting lifelong learning in the digital economy. Future Research: Future research should focus on expanding the dataset to include multilingual certificates, which would enhance the model’s ability to generalize across different languages and cultural contexts. Additionally, researchers could investigate the use of hybrid models that combine BERT with other machine learning techniques to further improve classification accuracy. Exploring the integration of real-world data sources, such as employer-verified work experience and additional non-formal learning formats, could also provide a more comprehensive approach to recognizing prior learning. http://www.informingscience.org/Publications/5525 document classification text augmentation recognition of past learning (RPL) BERT non-formal learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-07-07 20 5527 article Nadiia Mykolaivna Boliubash nnadbol@gmail.com Oleksandr Nykyforovych Yevtushenko alnievt@ukr.net Aim/Purpose: Automation of information extraction from digitized complex documents that contain both printed and handwritten text (as well as non-textual information) is one of the actual problems in the digital transformation of public administration. This study proposes an ML-based approach to improve the quality of automated extraction and processing of numerical data from digitized documents with handwritten digits using optical character recognition technology. Background: Currently, in public institutions in Ukraine, manual intervention is a bottleneck in the process of extracting numerical data from digitized documents and subsequent processing. New approaches to automating these processes are needed. Methodology: The methodology includes preprocessing of the document image, segmentation and classification of handwritten digits, conversion of the extracted digits into a date format with the possibility of their validation, and performing necessary calculations based on the extracted numerical information. First, handwritten digits from scanned images of document pages are segmented, then they are preprocessed and sent for recognition with a module based on convolutional neural networks. The image preprocessing steps consisted of binarization, application of a Gaussian filter to remove noise, and use of the Hough transform to correct the document’s skew angle. A CNN model was used to perform character-by-character classification for the recognition of segmented digits. Contribution: The study addresses current limitations in the extraction of handwritten digits from complex document images. The segmentation technique utilizes morphological transformations such as erosion and dilation, as well as the connected components method. The study explored different architectures with convolutional neural networks to determine the optimal hyperparameter configuration. The research findings confirm the importance of integrating methods to ensure effective image preprocessing, segmentation, and recognition of extracted digits. Findings: Experimental results demonstrate that the proposed approach decreases the processing time by a factor of 7.7 and increases the accuracy of numerical data recognition on pages containing fragments of handwritten digits. This indicates that operational tasks are completed with higher accuracy and efficiency. Recommendations for Practitioners: Software may be developed based on this research and implemented in the Pension Fund of Ukraine to automate the processing of digitized documents to determine service lengths and calculate the amount of pension to be awarded. The solution makes it possible to eliminate manual intervention in the process of data extraction and processing. Recommendation for Researchers: The study showed high accuracy in recognizing individual handwritten digits – 99.68% with the training data and 99.55% with the test data. However, the accuracy of recognition is lower if complex documents contain both handwritten and printed text as well as non-textual information. This is due to the complexity of segmenting handwritten characters, which requires further research to identify more effective methods for preprocessing and segmentation. Impact on Society: The proposed methodology allows a significant reduction of human factors in the process of extracting data from digitized documents, accelerating their processing and increasing the efficiency of government institutions. Future Research: Further research may further explore the areas of automated processing of digitized documents, especially in other branches of the state administration, taking into account the specifics of data extracted for further processing. http://www.informingscience.org/Publications/5527 digital transformation public administration document processing automation optical character recognition (OCR) handwritten text recognition handwritten digit recognition (HDR) convolutional neural network (CNN) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-07-14 20 5591 article Minh Duc Nguyen nguyenminhduc@hueuni.edu.vn Aim/Purpose: The paper introduces and develops the Core Ontology for Customs Procedures (COCP), a modular and scalable knowledge model designed to address the complexities of customs operations by formally representing operational, regulatory, security, transport, and financial transaction knowledge in alignment with global standards. Background: Customs authorities face increasing challenges related to evolving regulations, inconsistent documentation, and the lack of interoperability in existing systems. While some ontologies exist, they are often domain-specific and fail to provide a unified structure capable of supporting the breadth of customs activities and automation needs. COCP responds to this gap by offering a comprehensive and integrative solution. Methodology: COCP was developed using the NeOn scenario-based methodology, which supports iterative development and resource reuse. The ontology went through multiple phases including requirements specification based on competency questions, structured knowledge acquisition from authoritative sources, formal implementation in OWL using Protégé, axiomatization of semantic rules, and validation through reasoning tools, question-based testing, and SPARQL-based real-world scenarios. Contribution: The paper contributes a formalized and validated ontology that unifies key customs processes and ensures semantic consistency across modules. It incorporates internationally recognized models such as the World Customs Organization (WCO) Data Model and Harmonized System (HS) Codes, allowing it to function as a foundation for legal compliance, operational efficiency, and AI integration. COCP is structured for modularity, making it adaptable and extendable to changing regulatory and technical environments. Findings: COCP helps standardize customs procedures by promoting consistent data exchange, goods classification, and declaration handling across borders. It supports legal compliance and risk management through formalized rule definitions and reasoning mechanisms. The ontology also facilitates integration with intelligent technologies by providing machine-readable structures. Recommendations for Practitioners: Customs authorities and operational stakeholders are advised to adopt COCP to automate customs clearance, ensure uniform regulatory compliance, and integrate intelligent tools for decision support. The ontology's standardized structure can improve coordination among actors and reduce procedural delays. Recommendation for Researchers: Researchers are encouraged to expand COCP’s application to specialized customs domains, such as trade sanctions, bonded zones, or e-commerce-related imports. Opportunities also exist to explore its integration with machine learning and natural language processing for automated knowledge updates and deeper analytics. Impact on Society: The implementation of COCP can lead to faster, more transparent, and legally compliant customs processes, reducing friction in global trade and enhancing public trust in customs governance. By supporting streamlined procedures and intelligent automation, the ontology contributes to more effective and secure international commerce. Future Research: Future directions include extending COCP to region-specific and domain-specific customs contexts, strengthening its interoperability with diverse platforms, and incorporating AI-driven reasoning systems for advanced automation. Ensuring the ontology remains adaptable to continuous legal and procedural changes will be essential for sustaining its value in global customs environments. http://www.informingscience.org/Publications/5591 customs procedures core ontology global trade risk management compliance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-08-04 20 5578 article Fadoua Tamtam fadoua.tamtam@gmail.com Amina Tourabi a.tourabi@uiz.ac.ma Aim/Purpose: This paper presents a structured evaluation framework for renewable energy technologies (RETs) in project management, addressing the critical need to mitigate environmental impacts and reduce dependence on fossil fuels. By integrating decision-making techniques, the study aims to provide a systematic approach for selecting optimal RETs. Background: Subjective judgments and uncertainties often complicate RET selection. To overcome these challenges, this study develops a dual-method framework using Fuzzy Analytic Hierarchy Process (F-AHP) and Grey Relational Analysis (GRA), applied within the Moroccan Agency for Sustainable Energy (MASEN) project. The framework enhances objectivity in RET decision-making. Methodology: The research employs F-AHP to determine the relative importance of selection criteria, accounting for uncertainty in expert judgments. GRA then ranks RETs based on these weighted criteria. The methodology is applied to the MASEN project to validate its effectiveness empirically. Contribution: This study introduces a novel integration of F-AHP and GRA in RET evaluation, bridging qualitative and quantitative decision-making approaches. By refining selection methodologies, it advances the practical application of systematic assessment tools in sustainable energy projects. Findings: The proposed F-AHP-GRA methodology demonstrates high effectiveness in RET evaluation. RET4, identified as the optimal choice, reflects the framework’s ability to enhance decision-making transparency and accuracy. Detailed analysis of criteria weights provides deeper insights into RET prioritization. Recommendations for Practitioners: Energy project managers can adopt this framework to make data-driven and objective decisions in RET selection, improving project sustainability and efficiency. Recommendation for Researchers: Future studies should explore the adaptability of the F-AHP-GRA methodology across various energy project contexts, assessing its effectiveness in diverse geopolitical and technological settings. Additionally, refining selection criteria – such as socio-economic impacts and lifecycle costs – could enhance RET evaluation accuracy. Impact on Society: By providing a structured framework for RET selection, this research supports sustainable energy advancements, reducing environmental degradation, and aiding the transition toward global sustainability goals. The methodology promotes data-driven decision-making, fostering more efficient and responsible energy management. Future Research: Further investigation could focus on expanding the model to include dynamic, real-time data integration for improved responsiveness in RET evaluations. Additionally, exploring its applicability beyond RET selection, such as in broader sustainability initiatives, could unlock new opportunities for energy policy and project management. http://www.informingscience.org/Publications/5578 MASEN renewable energy technologies fuzzy analytic hierarchy process grey relational analysis sustainable decision-making eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-08-04 20 5600 article Narongsak Sukma narongsaks@siamtechno.ac.th Chayan Nuntawong chayan@nsru.ac.th Chakkrit Snae Namahoot chakkrits@nu.ac.th Kanokkarn Snae Namahoot Kanokkarnn@nu.ac.th Aim/Purpose: This study develops an automated framework for evaluating computer science curriculum alignment with educational standards, addressing assessment challenges in rapidly evolving technical fields. Background: Educational institutions struggle with time-consuming, subjective manual curriculum evaluation processes that are difficult to standardize, particularly when technological innovations frequently outpace curriculum updates. Methodology: The ONTO-ALIGN framework employs three complementary matching techniques: direct matching (H1), semantic analysis using WordNet and similarity algorithms (H2), and approximate matching for related concepts. The system evaluates course descriptions against the standards of the Thai Qualifications Framework (TQF: HEd) and Computer Science Curricula 2023 (CS2023). Contribution: This research provides the first comprehensive framework integrating multiple ontology linking techniques within a unified assessment system, bridging pedagogical theory with automated assessment technology for systematic curriculum evaluation. Findings: Validation through five computer science courses demonstrates effectiveness in identifying alignment gaps, with 82.9% agreement with expert assessments. The multi-method strategy proved valuable: direct matching identified 40.9% of correspondences, semantic analysis captured 29.3%, and approximate matching detected 17.1% of alignments. Recommendations for Practitioners: Educational institutions can implement multi-level curriculum assessments that consider both exact terminology matches and semantic relationships, enabling more frequent and systematic evaluations than traditional manual approaches. Recommendation for Researchers: Future research should explore the integration of machine learning with multiple matching techniques for increased accuracy in evolving knowledge domains. Impact on Society: By improving curriculum alignment with established standards, this framework enhances educational quality in computer science, leading to better-prepared graduates for an increasingly digital society. Future Research: Integrating machine learning with multiple matching techniques for increased accuracy in evolving knowledge domains represents a key advancement opportunity. http://www.informingscience.org/Publications/5600 curriculum evaluation computer science education educational standards semantic similarity constructive alignment ontology matching eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-08-04 20 5602 article Niko Ibrahim niko.ibrahim@gmail.com Putu Wuri Handayani putu.wuri@cs.ui.ac.id Aim/Purpose: This paper aims to qualitatively analyze barriers to Business Intelligence (BI) system adoption in Indonesia’s hotel industry from the technological, organizational, and environmental perspectives. This study is expected to thoroughly understand the adoption of BI systems in the hotel industry. Additionally, this study offers details that can assist public administrators or system developers in planning the implementation of BI systems in the hotel industry. Background: There has been a significant increase in the study of the adoption and use of BI systems. However, our understanding of the adoption determinants within the hotel industry is still limited. Methodology: This research uses the guidelines from the Technology, Organization, and Environment (TOE) framework because of its suitability to the context of this research, which was carried out not at the individual level but at the company level, considering environmental factors that exist in the hotel downstream supply chain ecosystem. We used semi-structured interviews with four tourism public administrators and experts, 20 hoteliers, and 10 managers of hotel distribution channels. Interview data were analyzed using thematic analysis in ATLAS.ti and categorized based on the TOE framework. Contribution: This research enriches the current research by involving various stakeholders in the hotel industry to understand the obstacles and actions that can be taken to foster the necessary cooperation. We highlight three challenges in adopting a BI system in the hotel industry: the necessity for a digital platform, the enhancement of data analytical skills, and the demand for an affordable solution for cooperation. Findings: The findings reveal the current barriers to BI system adoption and the actions to take. The barriers are a lack of regulation, a lack of trust, a lack of data integration, a lack of accuracy, a lack of resources, and a lack of competence. Recommendations for Practitioners: This research suggests a mapping of actions that can be undertaken to overcome the barriers. Practitioners and policymakers are advised to establish a regulatory policy on data collection, maintain data security by implementing data aggregation, hold regular training in data analytics, and provide a platform for data sharing and analytics. Recommendation for Researchers: Based on the findings, researchers can conduct further exploration to enrich insight related to technology factors to ensure continuous commitment from stakeholders, enhance coordination, and automate data-sharing processes. Impact on Society: This study thoroughly examines the adoption of BI systems in Indonesia and may apply to other emerging nations with comparable technological, regulatory, or cultural traits. Information from this study might help government officials or system developers plan and implement a BI system at the industry level. Future Research: More representative insight should be conducted in this study on a larger sample of hospitality and tourism organizations that are geographically more dispersed. To enrich the result, a quantitative analysis is also advised to understand the findings better and gain more specific evidence of the barriers and actions that need to be established. http://www.informingscience.org/Publications/5602 hotel business intelligence barriers adoption TOE framework eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-08-19 20 5529 article Zeynab Hatami hzeynab50@gmail.com Zahra Razmi zahrarazmi@alzahra.ac.ir Hadis Amiri Zadeh hadisamirizade56@gmail.com Aim/Purpose: To design and validate a knowledge management model to improve business performance in knowledge-based enterprises (KBEs). Background: In recent years, KBEs have become essential drivers of economic development, particularly in Iran. These enterprises face unique challenges, such as intense competition and limited access to advanced knowledge management practices. Addressing these challenges through effective management models is critical for enhancing their performance. This study aims to design and validate a knowledge management model tailored to the specific needs of KBEs in Iran, fostering improved business performance and competitiveness. Methodology: This research adopts an exploratory mixed-methods approach, integrating both qualitative and quantitative techniques. The qualitative phase involved in-depth interviews with 21 managers from knowledge-based enterprises in Iran, selected through theoretical sampling. In the quantitative phase, data were collected from 140 experts from these enterprises, chosen using simple random sampling. Data collection was carried out via interviews and questionnaires. The qualitative data were analyzed using grounded theory methodology, while the quantitative data were analyzed using Partial Least Squares (PLS) analysis to validate the proposed knowledge management model. Contribution: This study is the first of its kind in Iran to develop a knowledge management model specifically designed for knowledge-based enterprises and to evaluate its impact on business performance. The results offer valuable insights for policymakers and managers, enabling them to refine competitive strategies and foster sustainable growth. Furthermore, the study introduces a validated paradigmatic model of knowledge management, underscoring its pivotal role in enhancing business performance across financial, marketing, innovation, and social domains. Findings: The findings indicate that the implementation of the knowledge management model can significantly improve the performance of knowledge-based enterprises in Iran. This model focuses on enhancing knowledge repositories, streamlining business processes, and strengthening competitive capabilities. Key factors influencing knowledge management include managerial leadership, knowledge workers, a knowledge-oriented culture, and organizational learning. The knowledge management infrastructure in these enterprises acts as a foundational element, while business support factors and environmental uncertainty serve as mediating variables. Recommendations for Practitioners: Organizations should prioritize the development of robust knowledge management infrastructures to enhance business performance. This includes fostering a knowledge-driven culture, investing in collaborative tools, and ensuring effective leadership to create sustainable competitive advantages. Recommendation for Researchers: Future research should investigate the integration of knowledge management strategies in diverse organizational contexts and evaluate their long-term effects on innovation. Exploring how these practices contribute to organizational agility and resilience is also recommended. Impact on Society: The findings highlight the pivotal role of knowledge management in driving societal and organizational progress, particularly in knowledge-driven economies. By optimizing knowledge flow, organizations can contribute to sustainable development and address complex societal challenges. Future Research: Further research should explore the impact of emerging technologies, such as artificial intelligence (AI) and machine learning, on the enhancement of knowledge management practices. Investigating their potential to automate knowledge processes, optimize decision-making, and facilitate real-time knowledge sharing will be crucial for advancing the field. Additionally, examining the ethical implications of integrating these technologies into knowledge management systems represents a critical area for future inquiry. http://www.informingscience.org/Publications/5529 knowledge management business performance knowledge-based companies eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-09-04 20 5616 article Ester Ernest Mnzava esterrnst@sua.ac.tz Lorette Jacobs ejacobl1@unisa.ac.za Aim/Purpose: Despite the necessity of ensuring that reliable and recent information for economic development, particularly agriculture, is accessed and shared, the information found on websites related to agricultural topics requires assessment to ensure that only accurate information is shared with stakeholders within the maize industry in Tanzania. A rigorous tool for assessing the quality, accuracy, reproducibility, value, and use of agricultural information on the web is needed to ensure that web agriculture information can be meaningful to users. This study was undertaken to design a tool that can be used to assess the quality of agricultural information on the web. Methodology: This study employed an interpretive qualitative case study design. The qualitative data collection involved the design of the Web Agricultural Information Quality Evaluation Tool, in which data was collected through literature analysis and interviews. Thematic analysis was the main method of data analysis, where a literature review and data from interviews were used to identify themes that may be included in quality information evaluation tools for the maize industry in Tanzania. The Web Agricultural Information Quality Evaluation Tool has two main parts. Part A is the fundamental information quality criteria, which include authority and timeliness. Part B relates to the relevancy and completeness of the agricultural information on the web. Findings: The findings revealed that authority, timeliness, relevancy, and completeness are the key information quality criteria for assessing the quality of web agricultural information related to the maize industry. Impact on Society: The value of the Web Agricultural Information Quality Evaluation Tool is that it assists stakeholders involved in the agriculture value chain to assess the quality of information available on the web to ensure that timely, trustworthy, and accurate information is used to ensure the sustainability of the maize industry. Future Research: The research is based on the first three components of the analysis, design, development, and evaluation framework (ADDIE) model. Further research on the implementation and evaluation is needed to assess the relevance of the tool, specifically related to the maize industry and other agricultural sectors. http://www.informingscience.org/Publications/5616 information quality information evaluation agricultural information web information digital information eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-09-21 20 5613 article Krishna Mohan Ankala krishna.ankala@gmail.com Chiranjeevi Paritala mailmeparitala@gmail.com Vahiduddin Shariff shariff.v@gmail.com Aim/Purpose: Federated learning (FL) enables collaborative model training without centralizing raw data, thereby preserving privacy compared to traditional centralized machine learning approaches. To develop a privacy-preserving and explainable framework – where explainability is achieved through local SHAP analyses at each client and an aggregated global SHAP view – for health risk prediction in decentralized, heterogeneous environments, addressing the challenge of maintaining data confidentiality while achieving high predictive performance. Background: Traditional centralized health analytics solutions compromise data privacy; this paper introduces a federated learning approach that enables collaborative model building without exposing raw data. Methodology: The study integrates TreeNetX, a stable ensemble meta-learner, with SHAP-based explainability, leveraging client-specific training using gradient boosting models (XGBoost, LightGBM, CatBoost) and federated aggregation to address non-IID client distributions. Each client performs local feature selection using Recursive Feature Elimination with Cross-Validation (RFECV) before training. Experiments were conducted on three heterogeneous, tabular lung-cancer datasets from Kaggle to validate the model’s performance, using metrics including accuracy, precision, recall, F1-score, AUC, and calibration-related measures. Contribution: This paper contributes a novel federated ensemble learning framework that enhances predictive accuracy, robustness, and model interpretability, while ensuring data privacy in sensitive healthcare applications. Findings: The federated TreeNetX model achieved 91.17% accuracy and an AUC of 0.9667. It outperformed individual client models in robustness and generalization. SHAP-based analysis provided clinically meaningful insights, enhancing model trustworthiness. Recommendations for Practitioners: Practitioners should adopt federated ensemble strategies like TreeNetX for privacy-conscious predictive analytics to maintain compliance with data protection regulations while achieving high model performance. Recommendation for Researchers: Researchers should further explore hybrid federated architectures that combine explainability and advanced ensemble techniques to optimize interpretability and performance across heterogeneous environments. Impact on Society: The approach promotes ethical, privacy-preserving AI adoption in healthcare and other sensitive fields, contributing to safer and more trustworthy smart systems. Future Research: Future studies should investigate scaling the framework to even larger, more diverse client networks, integrating additional explainability tools, and extending applications beyond healthcare to other regulated industries. http://www.informingscience.org/Publications/5613 federated learning TreeNetX SHAP health risk prediction explainable AI data privacy ensemble meta-learner gradient boosting model interpretability eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-09-21 20 5610 article Caroline Magunje caroline.magunje@uct.ac.za Wallace Chigona wallace.chigona@uct.ac.za Inneth B Makofane babyinneth3@gmail.com Aim/Purpose: The current study aimed to explore the perceptions of school stakeholders on their responsibilities towards cybersafety and to propose a cybersafety community of purpose to mitigate cybersafety challenges in marginalised schools. Background: The COVID-19 pandemic accelerated the adoption of information and communication technologies in education. In the post-pandemic era, schools are increasingly using technologies in curriculum delivery, data management, and communication. The increased access to cyberspace, however, exposes schools to cyber risks and cyberattacks. Methodology: The study employed a qualitative exploratory methodology using case studies of four marginalised schools located in the Western Cape and Limpopo provinces of South Africa. We collected the data via semi-structured interviews of thirty participants who were stakeholders in a school context, including learners, educators, social workers, parents, and community leaders. Data analysis was based on an inductive approach with themes derived from data and the literature review. Contribution: Using the social-ecological framework, the study showed that effective cybersafety is an ecological phenomenon that requires the understanding and involvement of individuals, the family of learners, and the school, in a community context. The study contributes to the body of knowledge by suggesting a bottom-up cybersafety community of purpose activity system for marginalised schools. Such a cybersafety community of purpose activity system would allow stakeholders to work together to gather resources and acquire actions that would lead to a cybersafe and cyber resilient school environment as an outcome. The activity system highlights the interrelationships between school stakeholders as they use cyberspace and how they can achieve the required outcomes, the family of learners, and the school, in a community context. Findings: The findings of the study indicate that there is a disconnection in terms of cybersafety among school stakeholders in marginalised schools. There is a lack of clarity among stakeholders in terms of who is responsible for cybersecurity in the school context. Recommendations for Practitioners: We propose that a bottom-up cybersafety community of purpose within an activity system would be an effective way to ensure the safety of school stakeholders as they use cyberspace. Recommendation for Researchers: Researchers should implement the cybersafety community of purpose activity system in marginalised schools to determine its effectiveness. Impact on Society: A cybersafety community of purpose would bring together all stakeholders within a school context, leading to effective cybersafety initiatives for a positive cybersecurity culture and cyber resilience within a school context. Future Research: Future studies should adopt a design science approach to create and implement the cybersafety community of purpose activity system to determine its effectiveness. http://www.informingscience.org/Publications/5610 cybersecurity cybersafety in education community of purpose marginalised schools eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-09-29 20 5614 article Kai Jin jinkai.kerry@gmail.com Wenwen Xu cherrylina@163.com Xia Zhong 1965676086@qq.com Aim/Purpose: This systematic literature review seeks to synthesize and examine the key factors shaping learners’ willingness to persist in e-learning courses. Background: The proliferation of online learning, particularly Massive Open Online Courses (MOOCs) and various Learning Management Systems (LMS), has made it a central element of higher education and vocational training. However, despite advantages such as flexibility and accessibility, low continuance intention and poor course completion rates remain persistent challenges in the online learning domain. Methodology: A systematic literature review was conducted, synthesizing findings from 21 recent studies published in the Scopus and Web of Science databases between 2019 and 2024. Contribution: Through a comprehensive review of existing literature, this study identifies several dimensions of influencing factors, including technological aspects, individual characteristics, instructional elements, and environmental and social contexts. Findings: The findings indicate that learner satisfaction and perceived usefulness are key mediators between technological quality, individual traits, and continuance intention. Moreover, the use of targeted instructional strategies (such as personalized feedback and real-world case applications) and the integration of emerging technologies, including gamification and artificial intelligence, positively affect learners’ engagement. Recommendations for Practitioners: The results of this review offer practical insights for course developers and platform designers, supporting the optimization of online learning experiences to enhance long-term learner participation and academic outcomes. Recommendation for Researchers: It provided a deep understanding of the attributes of e-learning. Learners’ intrinsic motivation, personalized learning support, and timely feedback, fostering positive student-instructor and peer interactions, are key factors in e-learning. Impact on Society: Adequate technical, resource, and policy support should be provided to encourage instructors to innovate teaching methods and create favorable learning environments for learners. Future Research: Future research should continue to deepen the understanding of diverse influencing factors and their interactions. At the same time, the practical effects and ethical implications of emerging technologies, such as AI, VR/AR, and learning analytics in sustaining online learning engagement, should be further examined. http://www.informingscience.org/Publications/5614 e-learning consumers’ continuance usage intention systematic literature review satisfaction eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-10-06 20 5617 article SUDARSANAM S K sudarsanam.sk@vit.ac.in RACHEL EVELYN VIJAYARAJAN rachelevelyn.v2021@vitstudent.ac.in Aim/Purpose: This study investigates the psychological mechanisms linking remote/flexible work to intention to quit among middle and senior managers in India’s IT/ITES sector. Guided by the Transactional Model of Stress and Coping, it positions work stress as a mediator, and tests perceived organizational support (POS) as a moderating buffer. Background: Remote/flexible work, while offering flexibility, can also heighten stress through blurred work–life boundaries, communication challenges, and social isolation. This study addresses this gap by extending the Transactional Model of Stress and Coping to examine how POS moderates stress-driven intention to quit in remote/flexible work contexts. Methodology: A sequential exploratory mixed-methods design was employed. In the qualitative phase, interviews with 22 managers were analyzed using natural language processing and sentiment analysis to identify key stressors. In the quantitative phase, survey data from 260 managers were tested using Confirmatory Factor Analysis and structural equation modeling to examine mediation (work stress) and moderation (POS) effects. Both were found to be statistically significant. Contribution: The study contributes by integrating qualitative insights on stressors with quantitative validation of mediation and moderation effects. It advances remote/flexible work literature by extending the Transactional Model of Stress and Coping to hybrid work contexts and provides a contextualized framework for understanding managerial retention. Findings: The qualitative analysis revealed three dominant stressors: blurred work–life boundaries, communication breakdowns in virtual settings, and social isolation. Sentiment analysis further indicated predominantly negative emotions such as frustration, fatigue, and anxiety, underscoring the psychological burden of remote/flexible work. These insights informed the survey design. The quantitative results confirmed that work stress mediates the relationship between remote/flexible work and intention to quit, while POS significantly buffers this pathway. Managers perceiving higher POS reported lower stress and reduced intention to quit than those with weaker support. Recommendations for Practitioners: The major suggestions would be to prioritize employee well-being with stress-management programs (flexible scheduling, mental health resources). To strengthen POS via recognition, transparent communication, and support. This study also suggests fostering work-life balance through clear boundaries and reduced after-hours expectations. Recommendation for Researchers: Future research should test additional mediators, such as job autonomy and empowerment, as well as moderators, including leadership style. Longitudinal and cross-sectoral studies across industries such as healthcare and education are recommended to enhance generalizability and capture evolving workforce dynamics. Impact on Society: Reducing managerial turnover preserves organizational knowledge, sustains productivity, and supports healthier workplace cultures. At a societal level, improving retention strengthens organizational sustainability, contributes to economic stability, and enhances employee well-being in increasingly digital work environments. Future Research: Future research should examine the long-term impacts of remote/flexible work on employee stress levels and retention to understand evolving workforce dynamics. Cross-cultural investigations into perceived organizational support and stress appraisal mechanisms could uncover contextual variations in coping strategies and organizational commitment. Integrating artificial intelligence (AI) technologies for real-time monitoring of stress indicators in remote/flexible work environments may enhance proactive interventions. These explorations could contribute to more resilient and adaptive organizational models in an increasingly digital work landscape. http://www.informingscience.org/Publications/5617 remote/flexible work perceived organizational support work stress intention to quit IT/ITES sector machine learning speech processing natural language processing sentiment analysis eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-10-12 20 5623 article Abubakar Sadiq Muhammad sadiqunmohd@gmail.com Labaran Isiaku lisiaku@ciu.edu.tr ABDILLAHI MOHAMOUD SHEIKH MUSE asheikmusa@ciu.edu.tr Aim/Purpose: This study investigates the key factors influencing cryptocurrency adoption among international students in Northern Cyprus. It addresses the gap in understanding how technological and motivational factors affect adoption decisions in this demographic. Background: By applying the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), the study examines how facilitating conditions, hedonic motivation, effort expectancy, and performance expectancy drive adoption, while also examining the potential moderating influence of government support. Although government support was expected to be significant, the findings show otherwise, a surprising result that reshapes assumptions about its role. Methodology: A quantitative research design was employed, utilizing snowball sampling to distribute structured questionnaires to 305 international students. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with bootstrap resampling techniques. Contribution: This paper contributes to the growing body of knowledge on cryptocurrency adoption by focusing on international students, an underrepresented group in adoption studies, and applying the UTAUT2 model in a unique regional context. Findings: Facilitating conditions, hedonic motivation, effort expectancy, and performance expectancy significantly influence students’ intention to adopt cryptocurrencies, while government support does not have a significant moderating effect. Recommendations for Practitioners: Policymakers, educators, and cryptocurrency service providers should emphasize usability, accessibility, and user motivation rather than relying on regulatory promotion to encourage adoption. Recommendation for Researchers: Future studies should investigate other potential moderators beyond government support, such as cultural or institutional trust, and apply the UTAUT2 model in other emerging markets or student populations. Impact on Society: The results suggest that cryptocurrency adoption in emerging markets can progress without strong government intervention, being driven instead by individual needs and technological access. This has implications for financial inclusion and digital economy strategies. Future Research: Subsequent studies should consider longitudinal designs, qualitative insights, and comparative analyses with domestic student groups or other regions to deepen contextual understanding. http://www.informingscience.org/Publications/5623 cryptocurrency adoption UTAUT2 model international students Northern Cyprus government support eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-10-19 20 5629 article I Gede Susrama Mas Diyasa igsusrama.if@upnjatim.ac.id Mohammad Idhom idhom@upnjatim.ac.id Ahmad Sofian Aris Saputra ahmadsofianarissaputra@gmail.com DESHINTA ARROVA DEWI deshinta.ad@newinti.edu.my Tresna Maulana Fahrudin tresnamf@s.okayama-u.ac.jp Aim/Purpose: This study aims to develop and evaluate an automated scoring model for Indonesian student answers that enhances objectivity, accuracy, and adaptability – addressing persistent challenges in manual assessment, such as subjectivity, inconsistency, time inefficiency, and the increasing grading workload faced by teachers. Background: The proposed model combines GloVe word embeddings with a Long Short-Term Memory (LSTM) network, supported by evaluation algorithms including ROUGE Score, TF-IDF, and cosine similarity, to form a robust hybrid scoring system. Methodology: The methodology involves designing the model architecture, assembling a proprietary dataset of 3,420 student answers (processed into 3,152 samples) from online sources, practice books, and public repositories, applying standard NLP preprocessing techniques, and training the model using TensorFlow and Keras. A comparative baseline using a manually implemented LSTM with NumPy was also explored. Contribution: This research contributes a tailored hybrid model for automated scoring in the Indonesian language, providing a foundational analysis that highlights both the model’s potential and its key limitations, thereby informing future system improvements. Findings: The model achieved a mean absolute error (MAE) of 0.0761 and a Pearson correlation of 0.8429, indicating a strong alignment with manual grading in terms of relative ranking. However, it tends to overestimate scores for low-quality or irrelevant responses. It struggles with the use of synonyms, variations in answer length, and minor linguistic errors. Recommendations for Practitioners: As a proof-of-concept, the model shows promise as a supportive grading tool that can help reduce teachers’ correction workload and provide fairer, faster assessments in digital learning environments. Recommendation for Researchers: Future research should prioritize expanding the dataset’s size and diversity, enhancing architectural components, and integrating more advanced linguistic features. Investigating contextual embeddings, such as BERT, may also address current semantic limitations. Impact on Society: A reliable automated scoring system could significantly reduce teachers’ grading workload, enabling them to dedicate more time to qualitative learning activities and fostering fairer, more efficient assessments. Future Research: Further efforts should focus on enhancing the model’s precision, particularly in identifying and penalizing low-quality answers, through improved hybrid architecture design, rigorous hyperparameter optimization, and the exploration of more sophisticated embedding techniques. http://www.informingscience.org/Publications/5629 automated scoring GloVe LSTM ROUGE score TF-IDF cosine similarity natural language processing deep learning automated essay scoring Indonesian language education quality innovation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-11-25 20 5652 article Qusai Shambour q.shambour@ammanu.edu.jo Mahran Al-Zyoud m.zyoud@ammanu.edu.jo AbdelRahman Hussein a.husein@ammanu.edu.jo Aim/Purpose: The primary aim of this study is to address the persistent challenge of delayed autism spectrum disorder (ASD) diagnosis in toddlers. Early detection enables timely interventions that can improve developmental outcomes; however, conventional approaches rely on lengthy and resource-intensive behavioral assessments. We therefore introduce an interpretable AI screening framework designed to accelerate ASD triage while providing clinically understandable rationales to support decision-making. Background: Traditional ASD diagnosis depends on expert behavioral evaluation and parent reports which, despite their value, are time-consuming and capacity-limited, delaying access to early intervention. With ASD prevalence rising, scalable and effective approaches are urgently needed. This study proposes a robust AI framework for early ASD detection that integrates targeted preprocessing, feature selection, principled model optimization, and post-hoc explanations, aiming to improve diagnostic utility and clarity for end users in clinical and community settings. Methodology: We develop a unified, reproducible pipeline that combines data preprocessing, class balancing, feature selection, and Bayesian hyperparameter tuning. The pipeline also incorporates SHapley Additive exPlanations (SHAP) to provide model explanations. Six diverse machine learning models – Extreme Gradient Boosting (XGB), Histogram-based Gradient Boosting (HGB), Random Forest (RF), Naïve Bayes (NB), Mixture Discriminant Analysis (MDA), and Multi-layer Perceptron (MLP) – are evaluated to assess framework robustness rather than to crown a single best classifier. A cross-cultural dataset of toddlers aged 12–36 months (n=1,560) is constructed by merging two public sources containing Q-CHAT-10 items with demographic attributes. Preprocessing removes non-informative variables and encodes categorical features; Gaussian noise-based upsampling (GNUS) mitigates post-merge imbalance; RobustScaler stabilizes training. Gradient Boosting Feature Selection (GBFS) ranks and reduces features to enhance parsimony and interpretability. Performance is reported via accuracy, precision, recall, F1, and Matthews Correlation Coefficient (MCC). Model behavior is elucidated with SHAP to reveal feature contributions and decision pathways. Contribution: This work presents an interpretable AI framework for early ASD detection that couples performance with clinician-oriented explanation in a single pipeline. Rather than optimizing for accuracy alone, we emphasize synergy among preprocessing, balancing, feature selection, and explanation – the multimodel evaluation evidence adaptability across algorithmic families. GBFS and SHAP are used to ensure concise, explainable predictions. Notably, the framework achieved very strong internal validation results (high F1 and MCC across folds) with XGB, while SHAP-derived patterns aligned with clinical heuristics. Results are promising but preliminary, pending external, multi-site validation. Findings: GNUS and robust normalization improved generalization on the cross-cultural dataset. With GBFS-selected features, XGB achieved near-ceiling internal scores across key metrics, a trend observed – though to a lesser extent – in other models after comparable optimization. SHAP consistently highlighted behaviors such as gaze-following and social/emotional responsiveness among the most influential predictors, in line with clinical practice. Collectively, the findings indicate that interpretable ML can complement conventional screening, while warranting prospective and external validation to assess generalizability and potential dataset shift. Recommendations for Practitioners: Clinicians and community programs may consider adopting interpretable ML as a screening aid to prioritize referrals and shorten time-to-assessment. Attention to features repeatedly identified as influential can guide focused early interventions and resource allocation. Recommendation for Researchers: Future studies should test the framework on larger and more diverse cohorts to evaluate generalizability. Exploring ensembles and deeper architectures, as well as alternative preprocessing, resampling, and feature selection strategies, may further enhance performance, particularly for cases that are borderline. Impact on Society: Earlier, more reliable screening can improve access to services during critical neurodevelopmental windows. Integrating interpretable AI into practice may also strengthen clinician confidence in ML-assisted tools, supporting responsible, human-centered deployment and broader public health benefits. Future Research: Next steps include conducting real-world pilots across various clinical/community settings, integrating with complementary diagnostic tools to build multimodal platforms, and systematically evaluating balancing/optimization choices. These directions will help translate the framework into practical impact and inspire analogous applications in pediatric neurodevelopmental assessment. http://www.informingscience.org/Publications/5652 data-to-diagnosis early diagnosis autism spectrum disorder machine learning explainable artificial intelligence interpretable AI knowledge-driven screening eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-11-26 20 5653 article Nidhi Aggarwal nidhi.aggarwal@keshav.du.ac.in Anjali Thukral athukral@keshav.du.ac.in Chand Prakash Saini chandsaini03@gmail.com Pooja Kapoor poojakapoor@mru.edu.in Aim/Purpose: To examine how fake reviews function as dark patterns and affect consumer behaviour within the Stimulus-Organism-Response (SOR) framework grounded in nudge theory. Background: On e-commerce platforms, fake reviews function as dark patterns, serving as a manipulative digital nudge that exploits cognitive biases in accordance with Nudge Theory Methodology: A systematic search was conducted in the Scopus database using keywords combining nudging, dark patterns, and fake reviews. The search yielded 27 relevant peer-reviewed articles for detailed analysis. This study employed a conceptual approach, utilizing the SOR framework, which is anchored in nudge theory, to understand how fake reviews act as stimuli that trigger internal consumer responses, which in turn drive behavioural outcomes. Contribution: Through a comprehensive analysis of 27 peer-reviewed articles, this study advances the research on fake reviews by framing them as dark patterns based on nudge theory within the SOR framework. Findings: The study reveals that fake reviews exploit cognitive biases and emotional responses, shaping consumer purchase intentions and behaviour in online contexts. Recommendations for Practitioners: Platforms should treat fake reviews as manipulative nudges, strengthen detection systems, and design transparent, awareness-driven interfaces. Recommendation for Researchers: To empirically study the proposed questions and propositions, and to examine psychological mechanisms and interventions to counter fake review influence on consumers. Impact on Society: Considering fake reviews as intentional nudges helps eradicate unethical digital practices and strengthen consumer trust in e-commerce. Future Research: The study proposes 10 research questions and 9 propositions, urging interdisciplinary inquiry across psychology, marketing, and information systems. http://www.informingscience.org/Publications/5653 dark patterns nudge theory fake reviews manipulative design patterns persuasive design eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-11-26 20 5644 article V.P Joshith getjoshith@gmail.com Sashi Ranjan sashiranjan393@gmail.com K Kavitha kavithakrishnan229@gmail.com Aim/Purpose: Despite rapid digitalisation transforming Asian higher education, knowledge management (KM) implementation remains paradoxically fragmented across the region’s diverse institutional landscapes, creating critical theoretical and practical gaps that require systematic investigation. Background: This scoping review addresses these gaps by examining KM practices in Asian universities through a novel multi-dimensional analytical framework encompassing disciplines, practices, aspects, and stakeholder dynamics. Methodology: Following the PRISMA-ScR guidelines, we systematically reviewed 29 peer-reviewed studies (2009–2025) from Scopus and Google Scholar across nine Asian countries, highlighting both the field’s limited empirical base and emerging contours through thematic coding across four dimensions. Contribution: The study’s primary theoretical contribution is a hybrid ‘technology-mediated personalisation’ approach. This concept recontextualises Nonaka’s SECI model (a framework for converting tacit and explicit knowledge) and challenges existing KM strategy typologies. Furthermore, this paper presents the first multi-dimensional scoping review of KM practices across diverse Asian higher education contexts. Findings: Knowledge utilisation dominates practice (48% of studies), contradicting Western literature’s emphasis on knowledge creation. Institutional management applications significantly outweigh pedagogical implementations. Robust multi-stakeholder ecosystems emerge, involving faculty, administrators, and students; yet, university-industry collaboration remains severely underdeveloped. Policy-driven implementation prevails over organic knowledge communities, reflecting distinct cultural adaptations. Recommendations for Practitioners: Institutions should develop integrated KM frameworks balancing policy-driven governance with collaborative knowledge communities, invest in technology platforms supporting multiple KM processes, and strengthen university-industry knowledge transfer mechanisms. Recommendation for Researchers: Future research should focus on developing education-specific KM theoretical frameworks, conducting cross-cultural comparative studies, and investigating emerging AI-enhanced knowledge management technologies in academic contexts. Impact on Society: Enhanced KM practices will improve educational effectiveness, foster innovation ecosystems, and strengthen knowledge-based economic development across Asia’s rapidly evolving higher education landscape. Future Research: Critical priorities include longitudinal studies that track the evolution of KM systems, cross-cultural comparative frameworks, research on technology-enhanced knowledge creation, and sustainable university-industry collaboration models. http://www.informingscience.org/Publications/5644 knowledge management higher education Asian universities scoping review stakeholder dynamics technology integration institutional practices eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-12-01 20 5650 article Johannah Mae V Pastorfide johannahmae19@gmail.com Jodell R Bulaclac skylar04yue@gmail.com Christian Noli C Tambio cynx998@gmail.com Niño G Herrera nghninoherrera@gmail.com Aim/Purpose: The aim of this study is to develop and evaluate the King’s Way Cashless Payment and Product Monitoring System with QR Technology, specifically designed for the fitness industry. The system seeks to enhance operational efficiency, strengthen transaction security, and provide a seamless experience for gym members and administrators through digital transformation. Its novelty lies in the integration of QR-based transactions with automated membership and product monitoring features within a unified platform, a combination not yet widely adopted in small and medium-sized fitness enterprises. Background: With the rapid rise of digital payment technologies, the shift toward cashless transactions has become indispensable for modern businesses. The fitness industry, characterized by frequent transactions and dynamic membership management, continues to struggle with inefficiencies caused by manual payment and record-keeping systems. These traditional processes are prone to delays, errors, and data security vulnerabilities, underscoring the need for an integrated digital solution tailored to the operational structure of fitness centers. Methodology: The system was developed using Agile methodology, allowing for iterative testing and user feedback integration throughout the development cycle. Functionalities include QR-based payment processing, automated membership tracking, and real-time sales monitoring. Usability and performance were assessed using the System Usability Scale (SUS) and time-efficiency metrics. Contribution: This study provides a validated prototype that demonstrates the feasibility and effectiveness of integrating QR technology into gym operations. It distinguishes itself by combining cashless payment, membership management, and inventory tracking into a single, interactive system. The research also contributes empirical data on user acceptance and operational impact, offering a benchmark for future digitalization initiatives in the fitness sector. Findings: Performance evaluation revealed significant efficiency and accuracy improvements over manual systems, including the following: 80% reduction in average transaction time, 95% accuracy rate in financial and inventory tracking, and 88/100 mean SUS usability score. Statistical analysis confirmed that the digital system significantly improved transaction speed, reduced administrative workload, and enhanced data security compared to traditional methods (p < 0.05). Recommendations for Practitioners: Fitness centers and similar service-based enterprises are encouraged to adopt integrated digital systems combining payment, monitoring, and tracking features. Emphasizing real-time data visibility and user-friendly interfaces can lead to improved customer satisfaction, operational transparency, and streamlined business management. Recommendation for Researchers: Future researchers should explore cross-industry applications of QR-based management systems and analyze how demographic factors influence user adoption. Longitudinal studies are also recommended to assess the sustained effects of system implementation on business performance, customer loyalty, and profitability. Impact on Society: The study supports the broader shift toward cashless, contactless payment solutions, promoting digital inclusion and operational transparency. By minimizing human error and physical cash handling, the system contributes to both public health safety and the digital advancement of small to medium enterprises in developing regions. Future Research: Subsequent system iterations will explore the integration of biometric authentication, AI-driven analytics for customer behavior insights, and multi-branch scalability. Further studies will assess user acceptance of these advanced features and their contribution to long-term business resilience and innovation in the fitness industry. http://www.informingscience.org/Publications/5650 cashless transactions QR technology gym management system eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-12-06 20 5667 article Ammar Abdallah a.qasaimeh@psut.edu.jo Rand Abdel-Wahad Randsaber@outlook.com Chahd El-Qutob cha20248132@std.psut.edu.jo Mohammad Yousef Abuhashesh m.abuhashesh@psut.edu.jo Fandi Yousef Omeish f.omeish@psut.edu.jo Aim/Purpose: This study examines the cognitive factors that shape blockchain adoption among Jordanian consumers. Guided by Protection Motivation Theory (PMT), this study explores threat and coping appraisals. It also explored electronic Word-of-Mouth (e-WOM) as a moderating factor, as it is an understudied variable in blockchain research. Integrating e-WOM as a behavioral driver offers a novel contribution to blockchain literature. Background: Although blockchain ensures transparency and decentralization, its adoption in the Middle East and North Africa (MENA) regions remains slow due to trust and awareness gaps. Several factors, including psychological and perceptual influences on its adoption, have yet to be examined more specifically within the MENA region. Jordanian consumers are actively utilizing e-commerce; however, they are cautious about new technologies. To encourage the adoption of blockchain, there should be a deep understanding of the cognitive influences and impact of e-WOM. Methodology: A cross-sectional quantitative survey was conducted to collect data from 351 Jordanian individuals aged 18-45 years, all of whom had prior experience with e-commerce and blockchain technology. To conduct a suitable analysis for this research, Statistical Package for Social Sciences (SPSS) (v28) and Analysis of Moment Structures (AMOS) (v26) were utilized while implementing Structural Equation Modeling (SEM). Contribution: This study extends PMT by integrating e-WOM, offering a novel behavioral dimension within the blockchain adoption literature. It provides regional insights for emerging economies such as Jordan and deepens the understanding of consumer cognitive behavior toward blockchain technology. Findings: The constructs of PMT explain 51.9% of the variation in adoption behavior. The integration of e-WOM as a moderating factor increased explanatory power to 59.3%. Self-efficacy and response efficacy were the most influential factors, while e-WOM significantly moderated the effects of both threat and coping appraisals on the intention to adopt. These findings can inform policymakers and industry leaders in developing awareness and trust-building strategies. Recommendations for Practitioners: Emphasize response efficacy in messaging (demonstrable security and transparency gains) and provide user training/onboarding to raise self-efficacy. Systematically leverage positive e-WOM (testimonials, community Q&A, and creator reviews) to reinforce confidence and reduce uncertainty at the evaluation/adoption stages. Align communication with trust-building cues (interoperability, data control, and auditability). Recommendation for Researchers: Extend PMT and e-WOM models with longitudinal and cross-cultural designs, test additional moderators (such as trust, digital literacy, and perceived value), and examine post-adoption outcomes (use/continuance). Compare coping versus threat pathways across different sectors (finance, healthcare, supply chains) to generalize the findings. Impact on Society: This study demonstrates the importance of cognitive perception, trust, and e-WOM in technology adoption. These findings inform policymakers and industry leaders to develop awareness and trust-building strategies. This study extends the PMT with e-WOM and provides practical guidelines for trust-driven blockchain adoption in emerging markets. Future Research: Future research should explore adoption within different industry and cultural contexts. Investigating various variables such as risk tolerance, innovation readiness and trust will add greater value to research within this scope as well as studying the effectiveness and efficiency of communication strategies in shaping the acceptance of technology. http://www.informingscience.org/Publications/5667 blockchain technology adoption PMT e-WOM e-commerce Jordanian consumers eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-12-10 20 5635 article Johannah Mae V Pastorfide johannahmae19@gmail.com Jodell R Bulaclac skylar04yue@gmail.com Ruth G. Luciano rcgluciano@gmail.com Niño G Herrera nghninoherrera@gmail.com Aim/Purpose: The purpose of this study is to design, develop, and evaluate the Irenea Estate Subdivision Site Interactive Mapping System (i-SIMS), a web-based GIS application that enhances spatial data management and navigation within residential subdivisions, while contributing to scholarly discourse on GIS applications in human–computer interaction (HCI) and urban planning. Background: Geographic Information Systems (GIS) are widely recognized as critical tools for managing spatial data across various domains; however, residential subdivisions often lack integrated systems that combine navigation, property information, and community planning support. This study addresses that gap by introducing i-SIMS as a model that bridges practical community needs with academic inquiry in GIS-based urban informatics. Methodology: A systems development approach was applied, incorporating both backend GIS integration and front-end interactive design principles. Real-time data updating mechanisms were implemented to maintain accuracy. System evaluation employed user testing with 40 residents, focusing on usability, efficiency, and information accessibility, which was analyzed through quantitative and qualitative measures. Contribution: This research advances the academic discussion on the intersection of GIS and HCI by demonstrating how interactive mapping systems can be tailored for micro-urban contexts, such as subdivisions. The study provides a framework for integrating real-time GIS functionalities into web applications, offering insights applicable to both community-based GIS design and urban planning research. Findings: User testing results indicated a mean satisfaction rating of 4.6 out of 5 and a 32% reduction in task completion time for navigation-related activities compared to existing methods. These outcomes highlight i-SIMS’s effectiveness in improving usability, spatial awareness, and accessibility of property information. Recommendations for Practitioners: Urban planners, developers, and system designers should adopt GIS-based interactive platforms, such as i-SIMS, to enhance property management, resident navigation, and transparency in decision-making within residential communities. Recommendation for Researchers: Future research should investigate the integration of advanced technologies, such as machine learning, to enable predictive mapping and behavioral insights, thereby extending the applications of GIS in urban informatics. Impact on Society: i-SIMS strengthens transparency and efficiency in residential communities by providing residents and developers with improved access to accurate spatial information. This contributes to smarter navigation, more informed property-related decisions, and enhanced community engagement. Future Research: Further work could explore the use of augmented reality (AR) for immersive navigation, as well as advanced data analytics for real-time decision support in both residential and broader urban contexts. http://www.informingscience.org/Publications/5635 GIS technologies interactive mapping system real estate development residential subdivisions urban planning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2025-12-27 20 5688 article Fadoua Tamtam fadoua.tamtam@gmail.com Amina Tourabi a.tourabi@uiz.ac.ma Aim/Purpose: Strategic decision-making in Sustainable Bio-Based Supply Chains (SBSCs) is increasingly hindered by semantic ambiguity, expert inconsistency, and the inability of conventional models to handle uncertainty. These challenges compromise the alignment of AI integration with sustainability goals, especially in complex, multi-criteria environments. This study develops an AI-based decision support framework that addresses uncertainty and complexity in evaluating SBSCs, leveraging hybrid fuzzy logic methodologies. Background: The shift toward AI-enabled SBSCs introduces multifaceted sustainability trade-offs and challenges rooted in linguistic ambiguity, subjective judgments, and expert inconsistency. Existing methods often lack the semantic resilience required for strategic supply chain planning under uncertainty. Methodology: This study proposes an integrated hybrid approach combining Circular Intuitionistic Fuzzy Sets (C-IFS) with a Type-2 Fuzzy MAIRCA method. The framework operates in two stages: (1) C-IFS aggregation and entropy-based filtering to derive robust criteria weights and manage low-consensus indicators; and (2) application of Type-2 Fuzzy MAIRCA to assess and prioritize AI-integrated SBSC alternatives against idealized performance targets using interval-valued fuzzy distances. Contribution: The proposed model introduces a novel fusion of advanced fuzzy logic techniques to enable transparent, interpretable, and information-centric evaluation of bio-based supply chain configurations in uncertain environments. Findings: Among the evaluated SBSC configurations, the fully integrated AI-driven model (A2) achieved the highest sustainability score (0.872) with the lowest performance gap (Ψ = 0.486), confirming its strategic alignment. Scenario testing under semantic shifts upheld the model’s robustness and highlighted digital infrastructure as a key sensitivity factor. Recommendations for Practitioners: Practitioners can adopt the proposed framework to improve the strategic alignment of AI implementations in SBSCs, enabling more resilient, data-driven decisions across operational and regulatory dimensions. Recommendation for Researchers: Researchers are encouraged to explore extensions of this hybrid approach to other high-uncertainty domains and to examine the integration of additional soft computing methods for enhanced decision fidelity. Impact on Society: By supporting sustainable and technologically adaptive supply chains, this framework contributes to greener production ecosystems and informed policymaking in bioeconomy sectors. Future Research: Future studies may incorporate dynamic feedback systems, real-time AI learning, or bibliometric modeling to enrich the methodological scope and cross-sector applicability of the framework. http://www.informingscience.org/Publications/5688 information-centric decision support bio-based supply chains circular intuitionistic fuzzy sets (C-IFS) Type-2 fuzzy MAIRCA artificial intelligence in supply chain management digital twin-enabled evaluation models eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-02-06 19 .i v 5251 article Table of Contents for Volume 19, 2024, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/5251 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-02-06 19 5248 article Ahmad Samed Al-Adwan a.adwan@ammanu.edu.jo Devkant Kala devkant.kala@ddn.upes.ac.in Rakesh Kumar Meet rakeshmeet111@gmail.com Dhani Shanker Chaubey chaubeyds@gmail.com Aim/Purpose: This study investigates the drivers of user satisfaction in e-government services and its influence on continued use intention and citizen trust in government. It employs the integration of the Technology Acceptance Model (TAM) and the Information System Success Model (ISSM). Background: Electronic government, transforming citizen-state interactions, has gained momentum worldwide, including in India, where the aim is to leverage technology to improve citizen services, streamline administration, and engage the public. While prior research has explored factors influencing citizen satisfaction with e-government services globally, this area of study has been relatively unexplored in India, particularly in the post-COVID era. Challenges to widespread e-government adoption in India include a large and diverse population, limited digital infrastructure in rural areas, low digital literacy, and weak data protection regulations. Additionally, global declines in citizen trust, attributed to economic concerns, corruption, and information disclosures, further complicate the scenario. This study seeks to investigate the influence of various factors on user satisfaction and continuance usage of e-government services in India. It also aims to understand how these services contribute to building citizens’ trust in government. Methodology: The data were collected by utilizing survey items on drivers of e-government services, user satisfaction, citizen trust, and continuance use intention derived from existing literature on information systems and e-government. Responses from 501 Indian participants, collected using an online questionnaire, were analyzed using PLS-SEM. Contribution: This study makes a dual contribution to the e-government domain. First, it introduces a comprehensive research model that examines factors influencing users’ satisfaction and continuance intention with e-government services. The proposed model integrates the TAM and ISSM. Combining these models allows for a comprehensive examination of e-government satisfaction and continued intention. By analyzing the impact of user satisfaction on continuance intention and citizen trust through an integrated model, researchers and practitioners gain insights into the complex dynamics involved. Second, the study uncovers the effects of residential status on user satisfaction, trust, and continuance intention regarding e-government services. Findings reveal disparities in the influence of system and service quality on user satisfaction across different user segments. Researchers and policymakers should consider these insights when designing e-government services to ensure user satisfaction, continuance intention, and the building of citizen trust. Findings: The findings indicate that the quality of information, service, system, and perceived usefulness play important roles in user satisfaction with e-government services. All hypothesized paths were significant, except for perceived ease of use. Furthermore, the study highlights that user satisfaction significantly impacts citizen trust and continuance use intention. Recommendations for Practitioners: The findings suggest that government authorities should focus on delivering accurate, comprehensive, and timely information in a secure, glitch-free, and user-friendly digital environment. Implementing an interactive and accessible interface, ensuring compatibility across devices, and implementing swift query resolution mechanisms collectively contribute to improving users’ satisfaction. Conducting awareness and training initiatives, providing 24×7 access to online tutorials, helpdesks, technical support, clear FAQs, and integrating AI-driven customer service support can further ensure a seamless user experience. Government institutions should leverage social influence, community engagement, and social media campaigns to enhance user trust. Promotional campaigns, incentive programs, endorsements, and user testimonials should be used to improve users’ satisfaction and continuance intention. Recommendation for Researchers: An integrated model combining TAM and ISSM offers a robust approach for thoroughly analyzing the diverse factors influencing user satisfaction and continuance intention in the evolving digitalization landscape of e-government services. This expansion, aligning with ISSM’s perspective, enhances the literature by demonstrating how user satisfaction impacts continuance usage intention and citizen trust in e-government services in India and other emerging economies. Impact on Society: Examining the factors influencing user satisfaction and continuance intention in e-government services and their subsequent impact on citizen trust carries significant societal implications. The findings can contribute to the establishment of transparent and accountable governance practices, fostering a stronger connection between governments and their citizens. Future Research: There are several promising avenues to explore to enhance future research. Expanding the scope by incorporating a larger sample size could enable a more thorough analysis. Alternatively, delving into the performance of specific e-government services would offer greater precision, considering that this study treats e-government services generically. Additionally, incorporating in-depth interviews and longitudinal studies would yield a more comprehensive understanding of the dynamic evolution of digitalization. http://www.informingscience.org/Publications/5248 e-government user satisfaction continuance intention citizen trust India eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-03-07 19 5259 article Basil Alzougool b.alzougool@gmail.com Aim/Purpose: This study examined the use of Social Media Applications (SMAs) for accessing health-related information within a heterogeneous population in Jordan. The objective of this study was therefore threefold: (i) to investigate the usage of SMAs, including WhatsApp, Twitter, YouTube, Snapchat, Instagram, and Facebook, for accessing health-related information; (ii) to examine potential variations in the use of SMAs based on demographic and behavioral characteristics; and (iii) to identify the factors that can predict the use of SMAs. Background: There has been limited focus on investigating the behavior of laypeople in Jordan when it comes to seeking health information from SMAs. Methodology: A cross-sectional study was conducted among the general population in Jordan using an online questionnaire administered to 207 users. A purposive sampling technique was employed, wherein all the participants actively sought online health information. Descriptive statistics, t-tests, and regression analyses were utilized to analyze the collected data. Contribution: This study adds to the existing body of research on health information seeking from SMAs in developing countries, with a specific focus on Jordan. Moreover, laypeople, often disregarded by researchers and health information providers, are the most vulnerable individuals who warrant greater attention. Findings: The findings indicated that individuals often utilized YouTube as a platform to acquire health-related information, whereas their usage of Facebook for this purpose was less frequent. Participants rarely utilized Instagram and WhatsApp to obtain health information, while Twitter and Snapchat were very seldom used for this purpose. The variable of sex demonstrated a notable positive correlation with the utilization of YouTube and Twitter for the purpose of finding health-related information. Conversely, the variable of nationality exhibited a substantial positive correlation with the utilization of Facebook, Instagram, and Twitter. Consulting medical professionals regarding information obtained from the Internet was a strong indicator of using Instagram to search for health-related information. Recommendations for Practitioners: Based on the empirical results, this study provides feasible recommendations for the government, healthcare providers, and developers of SMAs. Recommendation for Researchers: Researchers should conduct separate investigations for each application specifically pertaining to the acquisition of health-related information. Additionally, it is advisable to investigate additional variables that may serve as predictors for the utilization of SMAs. Impact on Society: The objective of this study is to enhance the inclination of the general public in Jordan to utilize SMAs for health-related information while also maximizing the societal benefits of these applications. Future Research: Additional research is required to examine social media’s usability (regarding ease of use) and utility (comparing advantages to risks) in facilitating effective positive change and impact in healthcare. http://www.informingscience.org/Publications/5259 social media health information seeking Internet Jordan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-03-09 19 5250 article Hussain A. Younis hussain.younis@uobasrah.edu.iq Ahmed Ghazi Hameed Al-Rikabi ahmedalnoor129@gmail.com Putra Bin Sumari Hussain394@yahoo.com Aim/Purpose: This study examines the adoption and continued use of m-learning in Iraqi universities amidst an unstable environment by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) and Expectation-Confirmation Model (ECM) models. The primary goal is to address the specific challenges and opportunities in Iraq’s higher education institutions (HEIs) due to geopolitical instability and understand their impact on student acceptance, satisfaction, and continued m-learning usage. Background: The research builds on the growing importance of m-learning, especially in HEIs, and recognizes the unique challenges faced by institutions in Iraq, given the region’s instability. It identifies gaps in existing models and proposes extensions, introducing the variable “civil conflicts” to account for the volatile context. The study aims to contribute to a deeper understanding of m-learning acceptance in conflict-affected regions and provide insights for improving m-learning initiatives in Iraqi HEIs. Methodology: To achieve its objectives, this research employed a quantitative survey to collect data from 399 students in five Iraqi universities. PLS-SEM is used for the analysis of quantitative data, testing the extended UTAUT2 and ECM models. Contribution: The study’s findings are expected to contribute to the development of a nuanced understanding of m-learning adoption and continued usage in conflict-affected regions, particularly in the Iraqi HEI context. Findings: The study’s findings may inform strategies to enhance the effectiveness of m-learning initiatives in Iraqi HEIs and offer insights into how education can be supported in regions characterized by instability. Recommendations for Practitioners: Educators and policymakers can benefit from the research by making informed decisions to support education continuity and quality, particularly in conflict-affected areas. Recommendation for Researchers: Researchers can build upon this study by further exploring the adoption and usage of m-learning in unstable environments and evaluating the effectiveness of the proposed model extensions. Impact on Society: The research has the potential to positively impact society by improving access to quality education in regions affected by conflict and instability. Future Research: Future research can expand upon this study by examining the extended model’s applicability in different conflict-affected regions and assessing the long-term impact of m-learning initiatives on students’ educational outcomes. http://www.informingscience.org/Publications/5250 mobile learning (m-learning) higher education institutions (HEIs) unified theory of acceptance and use of technology 2 (UTAUT2) expectation confirmation model (ECM) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-03-13 19 5261 article Ayman Abdulhadi Alarabiat ayman.arabiat@bau.edu.jo Mohammad Al Hadidi s2131315@siswa.um.edu.my Aim/Purpose: The research aims to investigate the factors that influence the continuous use of mobile banking applications to complete banking monetary transactions. Background: Despite a significant increase in the use of mobile banking applications, particularly during the COVID-19 pandemic, new evidence indicates that the use rate of mobile banking applications for operating banking monetary transactions has declined. Methodology: The study proposed an integrated model based mainly on the process virtualization theory (PVT) with other novel factors such as mobile banking application anthropomorphism and virtual process failure risk. The study model was empirically validated using structural equation modeling analysis on quantitative data from 484 mobile banking application users from Jordan. Contribution: The study focuses on continuing use or post-adoption behavior rather than pre-adoption behavior. This is important since the maximum and long-term viability, as well as the financial investment in mobile banking applications, depend on regular usage rather than first-time use or initial experience. Findings: The results indicate that process virtualizable and anthropomorphism have a strong positive impact on bank customers’ decisions to continue using mobile banking applications to complete banking monetary transactions. Meanwhile, the negative impact of virtualization process failure risk on continuous use has been discovered. The found factors explain 67.5% of the variance in continuous use. Recommendations for Practitioners: The study identified novel, significant factors that affect bank customers’ decisions to use mobile banking applications frequently, and these factors should be examined, matched, satisfied, or addressed when redesigning or upgrading mobile applications. Banks should provide users with clear directions, processes, or tutorials on how to complete monetary transactions effectively. They should also embrace Artificial Intelligence (AI) technology to improve their applications and products with anthropomorphic features like speech synthesizers, Chatbots, and AI-powered virtual bank assistants. This is expected to help bank customers conduct various banking services conveniently and securely, just as if interacting with real people. The study further recommends that banks create and publish clear norms and procedures, as well as promote tolerance and protect consumers’ rights when the process fails or mistakes occur. Recommendation for Researchers: The study provides measurement items that were specifically built for the context of mobile banking applications based on PVT notions. Researchers are invited to reuse, test, and modify existing measurement items, as well as submit new ones if necessary. The study model does not consider psychological aspects like trust and satisfaction, which would provide additional insight into factors affecting continuing use. Researchers could potentially take a different approach by focusing on user resistance and non-adoption. Impact on Society: Financial inclusion is problematic, particularly in underdeveloped nations. According to financial inclusion research, Jordanians rarely utilize mobile banking apps. Continuous usage of mobile banking applications will be extremely beneficial in closing the financial inclusion gap, particularly among women. Furthermore, it could help the country’s efforts to transition to a digital society. Future Research: The majority of study participants are from urban areas. Future studies should focus on consumers who live in rural areas. It was also suggested that the elderly be targeted because they may have different views/perspectives on the continued use of mobile banking applications. http://www.informingscience.org/Publications/5261 mobile banking applications continuous use process virtualization theory post-adoption eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-03-18 19 5257 article Wiwin Suwarningsih winak03@gmail.com Rinda Kirana rind005@brin.go.id Purnomo H Khotimah purn005@brin.go.id Andri Fachrur Rozie andr035@brin.go.id Dianadewi Riswantini dian003@brin.go.id Ekasari Nugraheni ekas003@brin.go.id Devi Munandar devi.munandar@brin.go.id Andria Arisal andria.arisal@brin.go.id Noor Roufiq Ahmadi noorroufiqahmadi@gmail.com Aim/Purpose: This research aims to evaluate models from meta-learning techniques, such as Riemannian Model Agnostic Meta-Learning (RMAML), Model-Agnostic Meta-Learning (MAML), and Reptile meta-learning, to obtain high-quality metadata. The goal is to utilize this metadata to increase accuracy and efficiency in identifying chili varieties in smart agriculture. Background: The identification of chili varieties in smart agriculture is a complex process that requires a multi-faceted approach. One challenge in chili variety identification is the lack of a large and diverse dataset. This can be addressed using meta-learning techniques, which allow the model to leverage knowledge learned from other related tasks or artificially expand the dataset by applying transformations to existing data. Another challenge is the variation in growing conditions, which can affect the appearance of chili varieties. Meta-learning techniques can help address this challenge by allowing the model to adapt to variations in growing conditions with task-specific embeddings and optimizations. With the help of meta-learning techniques, such as data augmentation, data characterization, selection of datasets, and performance estimation, quality metadata for accurate identification of chili varieties can be achieved even in the presence of limited data and variations in growing conditions. Furthermore, the use of meta-learning techniques in chili variety identification can also assist in addressing challenges related to the computational complexity of the task. Methodology: The research approach employed is quantitative, specifically comparing three models from meta-learning techniques to determine which model is most suitable for our dataset. Data was collected from the variety assembly garden in the form of images of chili leaves using a mobile device. The research successfully gathered 1,974 images of chili leaves, with 697 images of large red chilies, 649 images of curly red chilies, and 628 images of cayenne peppers. These chili leaf images were then processed using augmentation techniques. The results of image data augmentation were categorized based on leaf characteristics (such as oval, lancet, elliptical, serrated leaf edges, and flat leaf edges). Subsequently, training and validation utilized three models from meta-learning techniques. The final stage involved model evaluation using 2-way and 3-way classification, as well as 5-shot and 10-shot learning scenarios to select the dataset with the best performance. Contribution: Improving classification accuracy, with a focus on ensuring high-quality data, allows for more precise identification and classification of chili varieties. Enhancing model training through an emphasis on data quality ensures that the models receive reliable and representative input, leading to improved generalization and performance in identifying chili varieties. Findings: With small collections of datasets, the authors have used data augmentation and meta-learning techniques to overcome the challenges of limited data and variations in growing conditions. Recommendations for Practitioners: By leveraging the knowledge and adaptability gained from meta-learning, accurate identification of chili varieties can be achieved even with limited data and variations in growing conditions. The use of meta-learning techniques in chili variety identification can greatly improve the accuracy and reliability of the identification process. Recommendation for Researchers: Using meta-learning techniques, such as transfer learning and parameter optimization, researchers can overcome challenges related to limited data and variations in growing conditions in chili variety identification. Impact on Society: The findings from this research can help identify superior chili seeds, thereby motivating farmers to cultivate high-quality chilies and achieve bountiful harvests. Future Research: We intend to verify our approach on a more extensive array of datasets and explore the implementation of more resilient regularization techniques, going beyond image augmentation, within the meta-learning techniques. Furthermore, our goal is to expand our research to encompass the automatic learning of parameters during training and tackle issues associated with noisy labels. Building on the insights gained from our observed outcomes, a future objective is to enhance the refinement of model-agnostic meta-learning techniques that can effectively adapt to intricate task distributions with substantial domain gaps between tasks. To realize this aim, our proposal involves devising model-agnostic meta-learning techniques specifically designed for multi-modal scenarios. http://www.informingscience.org/Publications/5257 chili variety identification meta-learning 2-3 way classification 5-10 shot classification eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-03-28 19 5262 article Avita Tri Utami avitatri.ui@gmail.com Teguh Raharjo teguh.raharjo12@ui.ac.id Ilham Zharif Mustaqim zharifilham@gmail.com Ni Wayan Trisnawaty ni.wayan05@ui.ac.id Aim/Purpose: The objective of this study is to summarize the challenges of Agile Requirements Engineering (Agile RE) in the public sector in republican and constitutional monarchy nations. Additionally, it offers recommendations to address these challenges. Background: Failure of IT projects in the public sector results in financial losses for the state and loss of public trust, often attributed to issues in requirements engineering such as prioritization of user needs and excessive scope of requirements. IT projects can have a higher success rate with Agile RE, but there are also drawbacks. Therefore, this study holds significance by presenting a thorough framework designed to pinpoint and overcome the challenges associated with Agile RE to increase the success rate of IT projects. Methodology: This study employs a Systematic Literature Review (SLR) protocol in the field of software engineering or related domains, which consists of three main phases: planning the review, conducting the review with a snowballing approach, and reporting the review. Furthermore, the authors perform open coding to categorize challenges based on the Agile methodologies adoption factor model and axial coding to map potential solutions. Contribution: The authors assert that this research enriches the existing literature on Agile RE, specifically within the public sector context, by mapping out challenges and possible solutions that contribute to creating a foundation for future studies to conduct a more in-depth analysis of Agile adoption in the public sector. Furthermore, it compares the barriers of Agile RE in the public sector with the general context, leading to the discovery of new theories specifically for this field. Findings: Most challenges related to Agile RE in the public sector are found in the people and process aspects. Project and organizational-related are subsequent aspects. Therefore, handling people and processes proficiently is imperative within Agile RE to prevent project failure. Recommendations for Practitioners: Our findings offer a comprehensive view of Agile RE in the public sector in republican and constitutional monarchy nations. This study maps the challenges encountered by the public sector and provides potential solutions. The authors encourage practitioners to consider our findings as a foundation for adopting Agile methodology in the public sector. Furthermore, this study can assist practitioners in identifying existing barriers related to Agile RE, pinpointing elements that contribute to overcoming those challenges, and developing strategies based on the specific needs of the organizations. Recommendation for Researchers: Researchers have the potential to expand the scope of this study by conducting research in other countries, especially African countries, as this study has not yet encompassed this geographic region. Additionally, they can strengthen the evidence linking Agile RE challenges to the risk of Agile project failure by performing empirical validation in a specific country. Impact on Society: This research conducts a comprehensive exploration of Agile RE within the public sector, serving as a foundation for the successful adoption of Agile methodology by overcoming obstacles related to Agile RE. This study highlights the importance of managing people, processes, projects, and organizational elements to increase the success of Agile adoption in the public sector. Future Research: In the future, researchers should work towards resolving the limitations identified in this study. This study has not provided a clear prioritization of challenges and solutions according to their significance. Therefore, future researchers can perform a Fuzzy Analytical Hierarchical Process (F-AHP) to prioritize the proposed solutions. http://www.informingscience.org/Publications/5262 Agile requirements engineering public sector Agile challenges systematic literature review eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-04-18 19 5269 article Putu Wuri Handayani putu.wuri@cs.ui.ac.id Muhammad Alfi Syakir muhammad.alfi81@ui.ac.id Shafira Ayu Maharani shafira.ayu81@ui.ac.id Yobelio Ekaharja Putra yobelio.ekaharja@ui.ac.id Sali Rahadi Asih sali.rahadi@ui.ac.id Aim/Purpose: This study aims to analyze the factors that influence user addiction to AR face filters in social network applications and their impact on the online social anxiety of users in Indonesia. Background: To date, social media users have started to use augmented reality (AR) face filters. However, AR face filters have the potential to create positive and negative effects for social media users. The study combines the Big Five Model (BFM), Sense of Virtual Community (SVOC), and Stimuli, Organism, and Response (SOR) frameworks. We adopted the SOR theory by involving the personality factors and SOVC factors as stimuli, addiction as an organism, and social anxiety as a response. BFM is the most significant theory related to personality. Methodology: We used a quantitative approach for this study by using an online survey. We conducted research on 903 Indonesian respondents who have used an AR face filter feature at least once. The respondents were grouped into three categories: overall, new users, and old users. In this study, group classification was carried out based on the development timeline of the AR face filter in the social network application. This grouping was carried out to facilitate data analysis as well as to determine and compare the different effects of the factors in each group. The data were analyzed using the covariance-based structural equation model through the AMOS 26 program. Contribution: This research fills the gap in previous research which did not discuss much about the impact of addiction in using AR face filters on online social anxiety of users of social network applications. Findings: The results of this study indicated neuroticism, membership, and immersion influence AR face filter addiction in all test groups. In addition, ARA has a significant effect on online social anxiety. Recommendations for Practitioners: The findings are expected to be valuable to social network service providers and AR creators in improving their services and to ensure policies related to the list of AR face filters that are appropriate for use by their users as a form of preventing addictive behavior of that feature. Recommendation for Researchers: This study suggested other researchers consider other negative impacts of AR face filters on aspects such as depression, life satisfaction, and academic performance. Impact on Society: AR face filter users may experience changes in their self-awareness in using face filters and avoid the latter’s negative impacts. Future Research: Future research might explore other impacts from AR face filter addiction behavior, such as depression, life satisfaction, and so on. Apart from that, future research might investigate the positive impact of AR face filters to gain a better understanding of the impact of AR face filters. http://www.informingscience.org/Publications/5269 augmented reality face filter Instagram social media Indonesia eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-04-21 19 5266 article Anas Husain anasjh@aabu.edu.jo Mohammad Alsharo mohammad.alsharo@aabu.edu.jo Yazan Alnsour alnsoury@uwosh.edu Aim/Purpose: This study aims to identify the characteristics of YouTube video reviews that consumers utilize to evaluate review helpfulness and explores how they process such information. This study aims to investigate the effect of argument quality, review popularity, number of likes, and source credibility on consumers’ perception of YouTube’s video review helpfulness. Background: Video reviews posted on YouTube are an emerging form of online reviews, which have the potential to be more helpful than textual reviews due to their visual and audible cues that deliver more vivid information about product features and specifications. With the availability of an enormous number of video reviews with unpredictable quality, it becomes challenging for consumers to find helpful reviews without consuming significant time and effort. In addition, YouTube does not provide a specific feature that indicates a review helpfulness similar to the one found on e-commerce websites. Consequently, consumers have to examine the characteristics of video reviews that are readily available on YouTube, evaluate them, and form a perception of whether a review is helpful or not. Despite the increasing popularity of YouTube’s video reviews, video reviews’ helpfulness received inadequate attention in the literature. The antecedents of the helpfulness of online video reviews are still underinvestigated, and more research is needed to identify the characteristics that consumers depend upon to assess video review helpfulness. Furthermore, it is important to understand how consumers process the information they gain from these characteristics to form a perception of their helpfulness. Methodology: Following an extended investigation of the relevant literature, we identified four key video characteristics that consumers presumably utilize to evaluate review helpfulness on YouTube (i.e., review popularity, number of likes, source credibility, and argument quality). By employing the Elaboration Likelihood Model (ELM), we classified these characteristics along the central and peripheral routes. The central route characteristics require a high cognitive effort by consumers to process the review’s message and reach a logical decision. In contrast, the peripheral route assumes that consumers judge the review’s message based on superficial qualities without substantial cognitive effort. A research model is introduced to investigate the effect of central and peripheral cues and their corresponding video review characteristics on review helpfulness. Accordingly, argument quality is proposed in the central route of the model, while review popularity, number of likes, and source credibility are proposed in the peripheral route. Furthermore, the study investigates how consumers process the information they obtain from these routes jointly or independently. To empirically test the proposed model, a convenient sample of 361 YouTube users was obtained through an online survey. The partial least squares method was used to investigate the effect of the proposed characteristics on video review helpfulness. Contribution: This study contributes to the literature in several ways. First, it is one of the few studies that investigate online video reviews’ helpfulness. Second, this study identifies several unique characteristics of YouTube’s video reviews that span peripheral and central routes, which potentially contribute to review helpfulness. Third, this study proposes a conceptual model based on the ELM to explore the effect of central and peripheral cues and their corresponding review characteristics on review helpfulness. Fourth, the research findings provide implications for research and practice that advance the theoretical understanding of video reviews’ helpfulness and serve as guidelines to create more helpful video reviews by better understanding the consumer’s cognitive processes. Findings: The results show that among the four characteristics proposed in the research model, argument quality in the central route is the strongest determinant factor affecting video review helpfulness. Results also show that review popularity, source credibility, and the number of likes in the peripheral route have significant effects on video review helpfulness. Altogether, our results show that the effect of the peripheral route adds up to 0.463 compared to 0.430, which is the impact magnitude of the argument quality construct in the central route. Based on the comparable effect magnitude of the central and peripheral routes of the model on video review helpfulness, our results indicate that both peripheral and central cues significantly affect consumers’ perception of video review helpfulness. The two routes are not mutually exclusive, and their cues can be processed in parallel or consecutive ways. Recommendations for Practitioners: The study recommends creating a dedicated category for reviews on YouTube with a specific feature for consumers to indicate the helpfulness of a video review, similar to the helpful vote button in textual reviews. The study also recommends that reviewers deliver more appealing and convincing argument quality, work toward improving their credibility, and understand the factors that contribute to video popularity. Impact on Society: Identifying the characteristics that affect video review helpfulness on YouTube helps consumers access helpful reviews more efficiently and improves their purchase decisions. Future Research: Future research could look into different types of data that could be extracted from YouTube to investigate the helpfulness of online video reviews. Future studies could employ machine learning and sentiment analysis techniques to reach more insights. Future research could also investigate the effect of product types in the context of online video reviews. http://www.informingscience.org/Publications/5266 review helpfulness online reviews video reviews YouTube elaboration likelihood model eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-04-23 19 5277 article Pivithuru J Kumarasinghe pivithuru@sjp.ac.lk Qiubo Huang qiubo_huang@zjsru.edu.cn Gothami Sakunthala Jayarathna gothami.usjp@gmail.com Aim/Purpose: This paper aims to investigate and understand the intentions of management undergraduate students in Hangzhou, China, regarding the adoption of Artificial Intelligence (AI) technologies in their education. It addresses the need to explore the factors influencing AI adoption in the educational context and contribute to the ongoing discourse on technology integration in higher education. Background: The paper addresses the problem by conducting a comprehensive investigation into the perceptions of management undergraduate students in Hangzhou, China, regarding the adoption of AI in education. The study explores various factors, including Perceived Relative Advantage and Trialability, to shed light on the nuanced dynamics influencing AI technology adoption in the context of higher education. Methodology: The study employs a quantitative research approach, utilizing the Confirmatory Tetrad Analysis (CTA) and Partial Least Squares Structural Equation Modeling (PLS-SEM) methodologies. The research sample consists of management undergraduate students in Hangzhou, China, and the methods include data screening, principal component analysis, confirmatory tetrad analysis, and evaluation of the measurement and structural models. We used a random sampling method to distribute 420 online, self-administered questionnaires among management students aged 18 to 21 at universities in Hangzhou. Contribution: This paper explores how management students in Hangzhou, China, perceive the adoption of AI in education. It identifies factors that influence AI adoption intention. Furthermore, the study emphasizes the complex nature of technology adoption in the changing educational technology landscape. It offers a thorough comprehension of this process while challenging and expanding the existing literature by revealing the insignificant impacts of certain factors. This highlights the need for an approach to AI integration in education that is context-specific and culturally sensitive. Findings: The study highlights students’ positive attitudes toward integrating AI in educational settings. Perceived relative advantage and trialability were found to impact AI adoption intention significantly. AI adoption is influenced by social and cultural contexts rather than factors like compatibility, complexity, and observability. Peer influence, instructor guidance, and the university environment were identified as pivotal in shaping students’ attitudes toward AI technologies. Recommendations for Practitioners: To promote the use of AI among management students in Hangzhou, practitioners should highlight the benefits and the ease of testing these technologies. It is essential to create communication strategies tailored to the student’s needs, consider cultural differences, and utilize the influence of peers and instructors. Establishing a supportive environment within the university that encourages innovation through policies and regulations is vital. Additionally, it is recommended that students’ attitudes towards AI be monitored constantly, and strategies adjusted accordingly to keep up with the changing technological landscape. Recommendation for Researchers: Researchers should conduct cross-disciplinary and cross-cultural studies with qualitative and longitudinal research designs to understand factors affecting AI adoption in education. It is essential to investigate compatibility, complexity, observability, individual attitudes, prior experience, and the evolving role of peers and instructors. Impact on Society: The study’s insights into the positive attitudes of management students in Hangzhou, China, toward AI adoption in education have broader societal implications. It reflects a readiness for transformative educational experiences in a region known for technological advancements. However, the study also underscores the importance of cautious integration, considering associated risks like data privacy and biases to ensure equitable benefits and uphold educational values. Future Research: Future research should delve into AI adoption in various academic disciplines and regions, employing longitudinal designs and qualitative methods to understand cultural influences and the roles of peers and instructors. Investigating moderating factors influencing specific factors’ relationship with AI adoption intention is essential for a comprehensive understanding. http://www.informingscience.org/Publications/5277 AI integration in education Chinese university education student perspectives diffusion theory PLS-SEM analysis eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-04-30 19 5275 article Minyar Sassi Hidri mmsassi@iau.edu.sa Aim/Purpose: This study aims to evaluate the success of deep learning in building user profiles for personalized information access. Background: To better express document content and information during the matching phase of the information retrieval (IR) process, deep learning architectures could potentially offer a feasible and optimal alternative to user profile building for personalized information access. Methodology: This study uses deep learning-based models to deduce the domain of the document deemed implicitly relevant by a user that corresponds to their center of interest, and then used predicted domain by the best given architecture with user’s characteristics to predict other centers of interest. Contribution: This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information adapted to their context and their preferences meeting their precise needs. To better express document content and information during this phase, deep learning models are employed to learn complex representations of documents and queries. These models can capture hierarchical, sequential, or attention-based patterns in textual data. Findings: The results show that deep learning models were highly effective for building user profiles for personalized information access since they leveraged the power of neural networks in analyzing and understanding complex patterns in user behavior, preferences, and user interactions. Recommendations for Practitioners: Building effective user profiles for personalized information access is an ongoing process that requires a combination of technology, user engagement, and a commitment to privacy and security. Recommendation for Researchers: Researchers involved in building user profiles for personalized information access play a crucial role in advancing the field and developing more innovative deep-based networks solutions by exploring novel data sources, such as biometric data, sentiment analysis, or physiological signals, to enhance user profiles. They can investigate the integration of multimodal data for a more comprehensive understanding of user preferences. Impact on Society: The proposed models can provide companies with an alternative and sophisticated recommendation system to foster progress in building user profiles by analyzing complex user behavior, preferences, and interactions, leading to more effective and dynamic content suggestions. Future Research: The development of user profile evolution models and their integration into a personalized information search system may be confronted with other problems such as the interpretability and transparency of the learning-based models. Developing interpretable machine learning techniques and visualization tools to explain how user profiles are constructed and used for personalized information access seems necessary to us as a future extension of our work. http://www.informingscience.org/Publications/5275 personalized IR user profile deep learning recurrent neural networks artificial neural networks convolutional neural networks eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-05-07 19 5280 article Lindung Parningotan Manik lind008@brin.go.id Zaenal Akbar zaenal.akbar@brin.go.id Yulia Aris Kartika yuli027@brin.go.id Niken Fitria Apriani nike007@brin.go.id Ariani Indrawati aria006@brin.go.id Dwi Setyo Rini dwis008@brin.go.id Priyanti Priyanti priyanti@uinjkt.ac.id Agusdin D. Fefirenta adindharma@gmail.com Tutie Djarwaningsih Sumowardoyo djarwaningsih.tutie55@gmail.com Aim/Purpose: This research investigated the determinant factors influencing the adoption intentions of Chatsicum, a Knowledge-Based Chatbot (KBC) aimed at enhancing the species literacy of biodiversity students. Background: This research was conducted to bridge the gap between technology, education, and biodiversity conservation. Innovative solutions are needed to empower individuals with knowledge, particularly species knowledge, in preserving the natural world. Methodology: The study employed a quantitative approach using the Partial Least Square Structural Equation Modeling (PLS-SEM) and sampled 145 university students as respondents. The research model combined the Task-Technology Fit (TTF) framework with elements from the Diffusion of Innovation (DOI), including relative advantage, compatibility, complexity, and observability. Also, the model introduced perceived trust as an independent variable. The primary dependent variable under examination was the intention to use the KBC. Contribution: The findings of this research contribute to a deeper understanding of the critical factors affecting the adoption of the KBC in biodiversity education and outreach, as studies in this context are limited. This study provides valuable insights for developers, educators, and policymakers interested in promoting species literacy and leveraging innovative technologies by analyzing the interplay of TTF and DOI constructs alongside perceived trust. Ultimately, this research aims to foster more effective and accessible biodiversity education strategies. Findings: TTF influenced all DOI variables, such as relative advantage, compatibility, observability, and trust positively and complexity negatively. In conclusion, TTF strongly affected usage intention indirectly. However, relative advantage, complexity, and observability insignificantly influenced the intention to use. Meanwhile, compatibility and trust strongly affected the use intention. Recommendations for Practitioners: Developers should prioritize building and maintaining chatbots that are aligned with the tasks, needs, and goals of the target users, as well as establishing trust through the assurance of information accuracy. Educators could develop tailored educational interventions that resonate with the values and preferences of diverse learners and are aligned closely with students’ learning needs, preferences, and curriculum while ensuring seamless integration with the existing educational context. Conservation organizations and policymakers could also utilize the findings of this study to enhance their outreach strategies, as the KBC is intended for students and biodiversity laypeople. Recommendation for Researchers: Researchers should explore the nuances of relationships between TTF and DOI, as well as trust, and consider the potential influence of mediating and moderating variables to advance the field of technology adoption in educational contexts. Researchers could also explore why relative advantage, complexity, and observability did not significantly impact the usage intention and whether specific user segments or contextual factors influence these relationships. Impact on Society: This research has significant societal impacts by improving species literacy, advancing technology in education, and promoting conservation efforts. Species knowledge could raise awareness regarding biodiversity and the importance of conservation, thereby leading to more informed and responsible citizens. Future Research: Future works should address the challenges and opportunities presented by KBCs in the context of species literacy enhancement, for example, interventions or experiments to influence the non-significant factors. Furthermore, longitudinal studies should investigate whether user behavior evolves. Ultimately, examining the correlation between species literacy, specifically when augmented by chatbots, and tangible conservation practices is an imperative domain in the future. It may entail evaluating the extent to which enhanced knowledge leads to concrete measures promoting biodiversity preservation. http://www.informingscience.org/Publications/5280 task-technology fit diffusion of innovation knowledge-based system chatbot trust biodiversity species literacy eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-05-16 19 5287 article Duaa Barakat dua20228080@std.psut.edu.jo Lubna Hazaimeh lub20228060@std.psut.edu.jo Ahmad Mousa Altamimi a.altamimi@psut.edu.jo Hazem Qattous h.qattous@psut.edu.jo Aim/Purpose: This paper investigates the user acceptability of blockchain technology in the healthcare sector, with a specific focus on healthcare professionals in Jordan. Background: The study seeks to identify the factors that affect healthcare professionals’ use and acceptance of blockchain technology in Jordan. Methodology: The study’s research framework integrates factors from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). A questionnaire was distributed to collect data from 372 healthcare professionals in Jordan, and the results were analyzed using structural equation modeling based on the Partial Least Square (PLS) technique. Contribution: While only a few previous studies have explored blockchain technology acceptance in the healthcare sector using either the TAM or the UTAUT, this study uniquely integrates elements from both models, offering a novel approach that provides a comprehensive understanding of the factors that influence the acceptance of blockchain technology among healthcare professionals in Jordan. The findings can assist decision-makers in developing strategies to enhance the adoption rate of blockchain technology in the Jordanian healthcare sector. Findings: The study revealed that usability, convenience, privacy and security, cost, and trust significantly impact the perceived usefulness of blockchain technology. The findings also suggest that healthcare professionals are more likely to have a positive attitude towards blockchain-based healthcare systems if they perceive them as useful and easy to use. Attitude, social influence, and facilitating conditions were found to significantly impact behavioral intention to use. Recommendations for Practitioners: Stakeholders should focus on developing blockchain-based healthcare systems that are easy to use, convenient, efficient, and effort-free. Recommendation for Researchers: Researchers may compare the acceptance of blockchain technology in the healthcare sector with other industries to identify industry-specific factors that may influence adoption. This comparative analysis can contribute to a broader understanding of technology acceptance. Impact on Society: Successful adoption of blockchain technology in the healthcare sector can lead to improved efficiency, enhanced protection of healthcare data, and reduced administrative burdens. This, in turn, can positively impact patient care and lead to cost savings, which contributes to more sustainable and accessible healthcare services. Future Research: Future research may explore integrating blockchain technology with other emerging technologies, such as artificial intelligence and sidechain, to create more comprehensive and innovative healthcare solutions. http://www.informingscience.org/Publications/5287 blockchain technology healthcare acceptance TAM UTAUT eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-05-29 19 5296 article Ammar Abdallah a.qasaimeh@psut.edu.jo Saja Alzubi alz20218070@std.psut.edu.jo Alaeddin Ahmad a.aladdin1973@gmail.com Aim/Purpose: This study focuses on two targeting strategies of out-store Location-Based Mobile Advertising (LBMA): the geo-fencing strategy (i.e., targeting customers who are near the focal store) and the geo-conquesting strategy (i.e., targeting those who are near competitors’ stores to visit the focal store). To the authors’ knowledge, no previous studies have compared the perceived intrusiveness of advertisements (ads) in geo-fencing and geo-conquesting settings, despite the accumulating literature on out-store LBMA. Hence, the aim of this study is to determine which targeting strategy is more effective in terms of reducing the perception of ads’ intrusiveness and increasing positive customers’ attitudes and purchase intention. Background: The intrusive nature of LBMA is perceived negatively by some customers, impacting their attitudes toward the ad, purchase intention, and even their perception of the brand. Therefore, identifying the targeting strategy under which ads are perceived as less intrusive is essential. Additionally, brick-and-mortar clothing stores in Jordan are facing challenges due to the rise of online shopping and increased competition from nearby stores. Thus, examining geo-fencing and geo-conquesting might tackle these challenges and encourage local clothing retailers to adopt these strategies. Methodology: A quantitative method was used in this study. A between-subjects experimental design was used to collect the data using a scenario-based survey distributed to Jordanians aged 18 to 45. A total of 531 responses were collected. After excluding those who do not belong to the targeted age group and those who did not pass the manipulation check, 406 responses were analyzed using the Statistical Package for the Social Sciences (SPSS) software version 28 and the Analysis of Moment Structures (AMOS) software version 26 to conduct Structural Equation Modeling (SEM). Contribution: This work offers valuable contributions by investigating the impact of the perceived intrusiveness of ads on purchase intention in the contexts of geo-fencing and geo-conquesting, which has not been studied before. Additionally, it fills a gap by examining this phenomenon in Jordan, a developing country in which attitudes toward LBMA have not been previously explored. Findings: The results revealed that location-based mobile ads sent under a geo-fencing strategy are perceived as less intrusive than those sent under a geo-conquesting strategy. In addition, customers’ attitudes fully mediate the relationship between intrusiveness and purchase intention only under the geo-fencing strategy. Ultimately, neither of the strategies is more effective in terms of increasing positive customer attitudes and purchase intentions in the context of clothing retail stores in Jordan. Recommendations for Practitioners: Clothing retailers in Jordan should consider adopting geo-fencing and geo-conquesting strategies to boost purchase intentions and tackle industry challenges. Additionally, to increase purchase intentions with geo-fencing, practitioners should focus on fostering positive customer attitudes toward ads, as simply perceiving them as less intrusive is not sufficient to drive purchase intention without the mediating effect of positive attitudes. Recommendation for Researchers: This research is crucial for academics and researchers as geolocation technology and LBMA are expected to advance significantly in the future. Researchers can investigate this topic through a randomized field experiment, followed by a research questionnaire to collect data from a real-world setting. Impact on Society: Utilizing LBMA is essential for local clothing retail stores that are trying to effectively reach and connect with their customers because searching the Internet for local goods and services is done primarily on mobile devices. Indeed, this study revealed that customers in both settings (i.e., geo-fencing and geo-conquesting) reported a high intention to visit the promoting store and to purchase from the advertised product category. Future Research: Future research can apply this topic to different industries and cultural contexts, as the results may vary across industries and regions. Moreover, future research could build on this study by investigating additional constructs, such as product category involvement, customization, and content type of the message (e.g., informative, entertaining). http://www.informingscience.org/Publications/5296 mobile marketing location-based mobile marketing location-based mobile advertising geo-fencing geo-conquesting perceived intrusiveness attitudes purchase intention eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-06-12 19 5303 article ACHMAD WILDAN KURNIAWAN achmad17003@mail.unpad.ac.id SUWANDI SUMARTIAS sabbir.phd@yahoo.com SOEGANDA PRIYATNA intan.harry@gmail.com KARIM SURYADI oom260415@gmail.com Aim/Purpose: This paper intends to answer the question regarding the extent to which political postings with value differences/similarities will influence the level of implicit knowledge sharing (KS) among work colleagues in organizations. More specifically, the study assesses contributors’ responses to a workmate’s publicity about politics on social media platforms (SMP) and their eagerness to implement implicit KS to the co-worker. Background: Previously published articles have confirmed an association between publicity about politics and the reactions from workfellows in the organization. Moreover, prior work confirmed that workers’ social media postings about politics may create unfavorable responses, such as being disliked and distrusted by workfellows. This may obstruct the KS because interpersonal relations are among the KS’s essential components. Therefore, it is imperative to assess whether the workfellows’ relationship affected by political publicity would impede the KS in the office. Methodology: Data was gathered using the vignette technique and online survey. A total of 510 online and offline questionnaires were distributed to respondents in Indonesian Halal firms who have implemented knowledge-sharing practices and have been at work for no less than twelve months in the present role. Next, the 317 completed questionnaires were examined with partial least squares structural equation modeling (PLS-SEM). Contribution: Postings about politics on SMP can either facilitate or impede the level of KS in organizations, and this research topic is relatively scarce in the knowledge management discipline. While previously published articles have concentrated on public organizations, this research centers on private firms. Moreover, this work empirically examines private companies in Indonesia, which is also understudied in the existing literature. Findings: The outcomes confirm that perceived political value similarity (PPV) in a co-worker’s social-media publicity has a significant and indirect influence on contributors’ eagerness to perform implicit/tacit KS. Further, colleague likability and trustworthiness significantly influence the level of KS among respondents. As PPV significantly forms colleague likability, likability strongly and positively shapes trustworthiness. Recommendations for Practitioners: The study shows that political publicity significantly affects implicit knowledge sharing (KS). As a result, managers and leaders, particularly those in private firms, are strengthened to instruct their staff about the ramifications of publicity embedded in employees’ SMP postings, particularly about political topics, as it may result in either negative or positive perceptions amongst the staff towards the workmate who posts. Recommendation for Researchers: As this study focuses on examining KS behavior in a large context, i.e., Indonesia Halal firms that dominate the Indonesian economy, and the fact that much polarization research focuses on society at large and less on specific sectors of life, it is important and interesting for researchers to conduct similar studies in a specific workplace as political agreements and disagreements become so important and consequential in everyday lives. Impact on Society: This article makes the implication that a person’s personality can influence how they react to political posts on SMP. It is difficult for the exposers to know the personality of each viewer of publicity in daily life. Workers’ newfound knowledge can motivate them to use SMP responsibly and lessen the probability that they will disclose information that might make their co-workers feel or perceive anything unfavorably. Future Research: There is a need for further studies to examine if the results can be applied to different locations and organizations, as individuals’ behaviors may vary according to the cultures of society and firms. Furthermore, future research can take into account the individual characteristics of workers, such as hospitability, self-confidence, and psychological strength, which may be well-matched with future work models. Future research may potentially employ a qualitative technique to offer deeper insights into the same topic. http://www.informingscience.org/Publications/5303 political communication private organization social media tacit knowledge sharing PLSSEM eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-06-27 19 5317 article Wahyu Setiawan Wibowo wahyu.setiawan11@ui.ac.id Rudy Fadrial rudyfadrial@gmail.com Sujianto Sujianto sujianto@lecturer.unri.ac.id Harapan Tua Ricky Freddy Simanjuntak harapan.tua@lecturer.unri.ac.id Welly Wirman welly.wirman@lecturer.unri.ac.id Aim/Purpose: This study aims to investigate the influence of e-government public services on public trust at the local government level, addressing the pressing need to understand the factors shaping citizen perceptions and trust in government institutions. Background: With the proliferation of e-government initiatives worldwide, governments are increasingly turning to digital solutions to enhance public service delivery and promote transparency. However, despite the potential benefits, there remains a gap in understanding how these initiatives impact public trust in government institutions, particularly at the local level. This study seeks to address this gap by examining the relationship between e-government service quality, individual perceptions, and public trust, providing valuable insights into the complexities of citizen-government interactions in the digital age. Methodology: Employing a quantitative approach, this study utilises surveys distributed to users of e-government services in one of the regencies in Indonesia. The sample consists of 278 individuals. Data analysis is conducted using Partial Least Squares Structural Equation Modelling, allowing for the exploration of relationships among variables and their influence on public trust. Contribution: This study provides insights into the factors influencing public trust in e-government services at the local government level, offering a nuanced understanding of the relationship between service quality, individual perceptions, and public trust. Findings: This study emphasises information quality and service quality in e-government-based public services as crucial determinants of individual perception in rural areas. Interestingly, system quality in e-government services has no influence on individual perception. In the individual perception, perceived security and privacy emerge as the strongest antecedent of public trust, highlighting the need to guarantee secure and private services for citizens in rural areas. These findings emphasise the importance of prioritising high-quality information, excellent service delivery, and robust security measures to foster and sustain public trust in e-government services. Recommendations for Practitioners: Practitioners must prioritise enhancing the quality of e-government services due to their significant impact on individual perception, leading to higher public trust. Government agencies must ensure reliability, responsiveness, and the effective fulfilment of user needs. Additionally, upholding high standards of information quality in e-government services by delivering accurate, relevant, and timely information remains crucial. Strengthening security measures through robust protocols such as data encryption and secure authentication becomes essential for protecting user data. With that in mind, the authors believe that public trust in government would escalate. Recommendation for Researchers: Researchers could investigate the relation between system quality in e-government services and individual perception in different rural settings. Longitudinal studies could also elucidate how evolving service quality, information quality, and security measures impact user satisfaction and trust over time. Comparative studies across regions or countries can reveal cultural and contextual differences in individual perceptions, identifying both universal principles and region-specific strategies for e-government platforms. Analysing user behaviour and preferences across various demographic groups can inform targeted interventions. Furthermore, examining the potential of emerging technologies such as blockchain or artificial intelligence in enhancing e-government service delivery, security, and user engagement remains an interesting topic. Impact on Society: This study’s findings have significant implications for fostering public trust in government institutions, ultimately strengthening democracy and citizen-government relations. By understanding how e-government initiatives influence public trust, policymakers can make informed decisions to improve service delivery, enhance citizen engagement, and promote transparency, thus contributing to more resilient and accountable governance structures. Future Research: Future research could opt for longitudinal studies to evaluate the long-term effects of enhancements in service quality, information quality, and security. Cross-cultural investigations can uncover universal principles and contextual differences in user experiences, supporting global e-government strategies in rural areas. Future research could also improve the research model by adding more variables, such as risk aversion or fear of job loss, to gauge individual perceptions. http://www.informingscience.org/Publications/5317 e-government public trust service quality information quality citizen perceptions local government Indonesia eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-07-05 19 5315 article Albertus A. K. Buitendag BuitendagAAK@tut.ac.za Frederik Gerhardus Hattingh HattinghFG@tut.ac.za Aim/Purpose: This research aims to develop a smart agricultural knowledge management framework to empower emergent farmers and extension officers (advisors to farmers) in developing countries as part of a smart farming lab (SFL). The framework utilizes knowledge objects (KOs) to capture information and knowledge of different forms, including indigenous knowledge. It builds upon a foundation of established agricultural knowledge management (AKM) models and serves as the cornerstone for an envisioned SFL. This framework facilitates optimal decision support by fostering linkages between these KOs and relevant organizations, knowledge holders, and knowledge seekers within the SFL environment. Background: Emergent farmers and extension officers encounter numerous obstacles in their knowledge operations and decision-making. This includes limited access to agricultural information and difficulties in applying it effectively. Many lack reliable sources of support, and even when information is available, understanding and applying it to specific situations can be challenging. Additionally, extension offices struggle with operational decisions and knowledge management due to agricultural organizations operating isolated in silos, hindering their access to necessary knowledge. This research introduces an SFL with a proposed AKM process model aimed at transforming emergent farmers into smart, innovative entities by addressing these challenges. Methodology: This study is presented as a theory-concept paper and utilizes a literature review to evaluate and synthesize three distinct AKM models using several approaches. The results of the analysis are used to design a new AKM process model. Contribution: This research culminates in a new AKM process framework that incorporates the strengths of various existing AKM models and supports emergent farmers and extension officers to become smart, innovative entities. One main difference between the three models analyzed, and the one proposed in this research, is the deployment and use of knowledge assets in the form of KOs. The proposed framework also incorporates metadata and annotations to enhance knowledge discoverability and enable AI-powered applications to leverage captured knowledge effectively. In practical terms, it contributes by further motivating the use of KOs to enable the transfer and the capturing of organizational knowledge. Findings: A model for an SFL that incorporates the proposed agricultural knowledge management framework is presented. This model is part of a larger knowledge factory (KF). It includes feedback loops, KOs, and mechanisms to facilitate intelligent decision-making. The significance of fostering interconnected communities is emphasized through the creation of linkages. These communities consist of knowledge seekers and bearers, with information disseminated through social media and other communication integration platforms. Recommendations for Practitioners: Practitioners and other scholars should consider implementing the proposed AKM process model as part of a larger SFL to support emergent farmers and extension officers in making operational decisions and applying knowledge management strategies. Recommendation for Researchers: The AKM process model is only presented in conceptual form. Therefore, researchers can practically test and assess the new framework in an agricultural setting. They can also further explore the potential of social media integration platforms to connect knowledge seekers with knowledge holders. Impact on Society: The proposed AKM process model has the potential to support emergent farmers and extension officers in becoming smart, innovative entities, leading to improved agricultural practices and potentially contributing to food security. Future Research: This paper discusses the AKM process model in an agrarian setting, but it can also be applied in other domains, such as education and the healthcare sector. Future research can evaluate the model’s effectiveness and explore and further investigate the semantic web and social media integration. http://www.informingscience.org/Publications/5315 smart farming lab emergent farmers extension officers agricultural knowledge management AKM process model knowledge objects social media integration eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-07-09 19 5329 article Qusai Shambour q.shambour@ammanu.edu.jo Mosleh Abualhaj Moslehabualhaj@yahoo.com Ahmad Abu-Shareha a.abushareha@ammanu.edu.jo Qasem Kharma qasem.kharma@gmail.com Aim/Purpose: This study aims to develop a solution for personalized tourism recommendations that addresses information overload, data sparsity, and the cold-start problem. It focuses on enabling tourists to choose the most suitable tourism-related facilities, such as restaurants and hotels, that match their individual needs and preferences. Background: The tourism industry is experiencing a significant shift towards digitalization due to the increasing use of online platforms and the abundance of user data. Travelers now heavily rely on online resources to explore destinations and associated options like hotels, restaurants, attractions, transportation, and events. In this dynamic landscape, personalized recommendation systems play a crucial role in enhancing user experience and ensuring customer satisfaction. However, existing recommendation systems encounter major challenges in precisely understanding the complexities of user preferences within the tourism domain. Traditional approaches often rely solely on user ratings, neglecting the complex nature of travel choices. Data sparsity further complicates the issue, as users might have limited interactions with the system or incomplete preference profiles. This sparsity can hinder the effectiveness of these systems, leading to inaccurate or irrelevant recommendations. The cold-start problem presents another challenge, particularly with new users who lack a substantial interaction history within the system, thereby complicating the task of recommending relevant options. These limitations can greatly hinder the performance of recommendation systems and ultimately reduce user satisfaction with the overall experience. Methodology: The proposed User-based Multi-Criteria Trust-aware Collaborative Filtering (UMCTCF) approach exploits two key aspects to enhance both the accuracy and coverage of recommendations within tourism recommender systems: multi-criteria user preferences and implicit trust networks. Multi-criteria ratings capture the various factors that influence user preferences for specific tourism items, such as restaurants or hotels. These factors surpass a simple one-star rating and take into account the complex nature of travel choices. Implicit trust relationships refer to connections between users that are established through shared interests and past interactions without the need for explicit trust declarations. By integrating these elements, UMCTCF aims to provide more accurate and reliable recommendations, especially when data sparsity limits the ability to accurately predict user preferences, particularly for new users. Furthermore, the approach employs a switch hybridization scheme, which combines predictions from different components within UMCTCF. This scheme leads to a more robust recommendation strategy by leveraging diverse sources of information. Extensive experiments were conducted using real-world tourism datasets encompassing restaurants and hotels to evaluate the effectiveness of UMCTCF. The performance of UMCTCF was then compared against baseline methods to assess its prediction accuracy and coverage. Contribution: This study introduces a novel and effective recommendation approach, UMCTCF, which addresses the limitations of existing methods in personalized tourism recommendations by offering several key contributions. First, it transcends simple item preferences by incorporating multi-criteria user preferences. This allows UMCTCF to consider the various factors that users prioritize when making tourism decisions, leading to a more comprehensive understanding of user choices and, ultimately, more accurate recommendations. Second, UMCTCF leverages the collective wisdom of users by incorporating an implicit trust network into the recommendation process. By incorporating these trust relationships into the recommendation process, UMCTCF enhances its effectiveness, particularly in scenarios with data sparsity or new users with limited interaction history. Finally, UMCTCF demonstrates robustness towards data sparsity and the cold-start problem. This resilience in situations with limited data or incomplete user profiles makes UMCTCF particularly suitable for real-world applications in the tourism domain. Findings: The results consistently demonstrated UMCTCF’s superiority in key metrics, effectively addressing the challenges of data sparsity and new users while enhancing both prediction accuracy and coverage. In terms of prediction accuracy, UMCTCF yielded significantly more accurate predictions of user preferences for tourism items compared to baseline methods. Furthermore, UMCTCF achieved superior coverage compared to baseline methods, signifying its ability to recommend a wider range of tourism items, particularly for new users who might have limited interaction history within the system. This increased coverage has the potential to enhance user satisfaction by offering a more diverse and enriching set of recommendations. These findings collectively highlight the effectiveness of UMCTCF in addressing the challenges of personalized tourism recommendations, paving the way for improved user satisfaction and decision-making within the tourism domain. Recommendations for Practitioners: The proposed UMCTCF approach offers a potential opportunity for tourism recommendation systems, enabling practitioners to create solutions that prioritize the needs and preferences of users. By incorporating UMCTCF into online tourism platforms, tourists can utilize its capabilities to make well-informed decisions when selecting tourism-related facilities. Furthermore, UMCTCF’s robust design allows it to function effectively even in scenarios with data sparsity or new users with limited interaction history. This characteristic makes UMCTCF particularly valuable for real-world applications, especially in scenarios where these limitations are common obstacles. Recommendation for Researchers: The success of UMCTCF can open up new avenues in personalized recommendation research. One promising direction lies in exploring the integration of additional contextual information, such as temporal (time-based) or location-based information. By incorporating these elements, the model could be further improved, allowing for even more personalized recommendations. Furthermore, exploring the potential of UMCTCF in domains other than tourism has considerable significance. By exploring its effectiveness in other e-commerce domains, researchers can broaden the impact of UMCTCF and contribute to the advancement of personalized recommendation systems across various industries. Impact on Society: UMCTCF has the potential to make a positive impact on society in various ways. By delivering accurate and diverse recommendations that are tailored to individual user preferences, UMCTCF fosters a more positive and rewarding user experience with tourism recommendation systems. This can lead to increased user engagement with tourism platforms, ultimately enhancing overall satisfaction with travel planning. Furthermore, UMCTCF enables users to make more informed decisions through broader and more accurate recommendations, potentially reducing planning stress and leading to more fulfilling travel experiences. Future Research: Expanding upon the success of UMCTCF, future research activities can explore several promising paths. Enriching UMCTCF with various contextual data, such as spatial or location-based data, to enhance recommendation accuracy and relevance. Leveraging user-generated content, like reviews and social media posts, could provide deeper insights into user preferences and sentiments, improving personalization. Additionally, applying UMCTCF in various e-commerce domains beyond tourism, such as online shopping, entertainment, and healthcare, could yield valuable insights and enhance recommendation systems. Finally, exploring the integration of optimization algorithms could improve both recommendation accuracy and efficiency. http://www.informingscience.org/Publications/5329 tourism recommendation multi-criteria analysis implicit trust network data sparsity cold start new user eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-07-15 19 5335 article Maya Botvin mayamoyal1@gmail.com Alona Forkosh-Baruch alonabar@l-w.ac.il Arnon Hershkovitz arnon.hershkovitz@gmail.com Aim/Purpose: This study explored teachers’ data-driven decision-making processes during routine and emergency remote teaching, as experienced during the COVID-19 pandemic. Background: Decision-making is essential in teaching, with informed decisions promoting student learning and teachers’ professional development most effectively. However, obstacles to the use of data have been identified in many studies. Methodology: Using a qualitative methodology (N=20), we studied how teachers make decisions, what data is available, and what data they would like to have to improve their decision-making. We used an inductive approach (bottom-up), utilizing teachers’ statements related to decision-making as the unit of analysis. Contribution: Our findings shed an important light on teachers’ Data-Driven Decision-Making (DDDM), highlighting the differences between routine and Emergency Remote Teaching (ERT). Findings: Overall, we found that teachers make teaching decisions in three main areas: pedagogy, discipline-related issues, and appearance and behavior. They shift between making decisions based on data and making decisions based on intuition. Academic-related decisions are the most prominent in routine teaching, and during ERT, they were almost the only area in which teachers’ decisions were made. Teachers reported collecting data about students’ academic achievements and emotional state and considered the organizational culture, consultation with colleagues, and parents’ involvement before decision-making. Recommendations for Practitioners: Promote a culture of data-driven decision-making across the education system; Make diverse and rich data of different types accessible to teachers; Increase professional and emotional support for teachers. Recommendation for Researchers: Researchers have the potential to expand the scope of this study by conducting research using other methodologies and in different countries. Impact on Society: This study highlights the importance of teachers’ data-driven decision-making in improving teaching practices and promoting students’ achievement. Future Research: Additional research is required to examine data-driven decision-making in diverse circumstances. http://www.informingscience.org/Publications/5335 data-driven decision-making emergency remote teaching (ERT) qualitative research COVID-19 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-11 19 5334 article Vignesh U vignesh.u@vit.ac.in Tushar Moolchandani tushar.moolchandani2020@vitstudent.ac.in Aim/Purpose: Accurate detection of vacant parking spaces is crucial for autonomous parking. Deep learning, particularly Graph Neural Networks (GNNs), holds promise for addressing the challenges of diverse parking lot appearances and complex visual environments. Our GNN-based approach leverages the spatial layout of detected marking points in around-view images to learn robust feature representations that are resilient to occlusions and lighting variations. We demonstrate significant accuracy improvements on benchmark datasets compared to existing methods, showcasing the effectiveness of our GNN-based solution. Further research is needed to explore the scalability and generalizability of this approach in real-world scenarios and to consider the potential ethical implications of autonomous parking technologies. Background: GNNs offer a number of advantages over traditional parking spot detection methods. Unlike methods that treat objects as discrete entities, GNNs may leverage the inherent connections among parking markers (lines, dots) inside an image. This ability to exploit spatial connections leads to more accurate parking space detection, even in challenging scenarios with shifting illumination. Real-time applications are another area where GNNs exhibit promise, which is critical for autonomous vehicles. Their ability to intuitively understand linkages across marking sites may further simplify the process compared to traditional deep-learning approaches that need complex feature development. Furthermore, the proposed GNN model streamlines parking space recognition by potentially combining slot inference and marking point recognition in a single step. All things considered, GNNs present a viable method for obtaining stronger and more precise parking slot recognition, opening the door for autonomous car self-parking technology developments. Methodology: The proposed research introduces a novel, end-to-end trainable method for parking slot detection using bird’s-eye images and GNNs. The approach involves a two-stage process. First, a marking-point detector network is employed to identify potential parking markers, extracting features such as confidence scores and positions. After refining these detections, a marking-point encoder network extracts and embeds location and appearance information. The enhanced data is then loaded into a fully linked network, with each node representing a marker. An attentional GNN is then utilized to leverage the spatial relationships between neighbors, allowing for selective information aggregation and capturing intricate interactions. Finally, a dedicated entrance line discriminator network, trained on GNN outputs, classifies pairs of markers as potential entry lines based on learned node attributes. This multi-stage approach, evaluated on benchmark datasets, aims to achieve robust and accurate parking slot detection even in diverse and challenging environments. Contribution: The present study makes a significant contribution to the parking slot detection domain by introducing an attentional GNN-based approach that capitalizes on the spatial relationships between marking points for enhanced robustness. Additionally, the paper offers a fully trainable end-to-end model that eliminates the need for manual post-processing, thereby streamlining the process. Furthermore, the study reduces training costs by dispensing with the need for detailed annotations of marking point properties, thereby making it more accessible and cost-effective. Findings: The goal of this research is to present a unique approach to parking space recognition using GNNs and bird’s-eye photos. The study’s findings demonstrated significant improvements over earlier algorithms, with accuracy on par with the state-of-the-art DMPR-PS method. Moreover, the suggested method provides a fully trainable solution with less reliance on manually specified rules and more economical training needs. One crucial component of this approach is the GNN’s performance. By making use of the spatial correlations between marking locations, the GNN delivers greater accuracy and recall than a completely linked baseline. The GNN successfully learns discriminative features by separating paired marking points (creating parking spots) from unpaired ones, according to further analysis using cosine similarity. There are restrictions, though, especially where there are unclear markings. Successful parking slot identification in various circumstances proves the recommended method’s usefulness, with occasional failures in poor visibility conditions. Future work addresses these limitations and explores adapting the model to different image formats (e.g., side-view) and scenarios without relying on prior entry line information. An ablation study is conducted to investigate the impact of different backbone architectures on image feature extraction. The results reveal that VGG16 is optimal for balancing accuracy and real-time processing requirements. Recommendations for Practitioners: Developers of parking systems are encouraged to incorporate GNN-based techniques into their autonomous parking systems, as these methods exhibit enhanced accuracy and robustness when handling a wide range of parking scenarios. Furthermore, attention mechanisms within deep learning models can provide significant advantages for tasks that involve spatial relationships and contextual information in other vision-based applications. Recommendation for Researchers: Further research is necessary to assess the effectiveness of GNN-based methods in real-world situations. To obtain accurate results, it is important to employ large-scale datasets that include diverse lighting conditions, parking layouts, and vehicle types. Incorporating semantic information such as parking signs and lane markings into GNN models can enhance their ability to interpret and understand context. Moreover, it is crucial to address ethical concerns, including privacy, potential biases, and responsible deployment, in the development of autonomous parking technologies. Impact on Society: Optimized utilization of parking spaces can help cities manage parking resources efficiently, thereby reducing traffic congestion and fuel consumption. Automating parking processes can also enhance accessibility and provide safer and more convenient parking experiences, especially for individuals with disabilities. The development of dependable parking capabilities for autonomous vehicles can also contribute to smoother traffic flow, potentially reducing accidents and positively impacting society. Future Research: Developing and optimizing graph neural network-based models for real-time deployment in autonomous vehicles with limited resources is a critical objective. Investigating the integration of GNNs with other deep learning techniques for multi-modal parking slot detection, radar, and other sensors is essential for enhancing the understanding of the environment. Lastly, it is crucial to develop explainable AI methods to elucidate the decision-making processes of GNN models in parking slot detection, ensuring fairness, transparency, and responsible utilization of this technology. http://www.informingscience.org/Publications/5334 parking slot detection bird’s-eye images graph neural networks attention mechanism autonomous vehicles deep learning real-time processing eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-13 19 5346 article Minh Hoang Vu minhvuhoang88@gmail.com Long Phi Tran longtp@neu.edu.vn Anh Nguyen Tuan Doan anhdnt.ctdaep@gmail.com Anh Xuan Dinh dinhxuananh.work@gmail.com Hanh Minh Trinh trinhminhhanh0912@gmail.com Aim/Purpose: This study investigates the relationship between Electronic Word-of-Mouth (EWOM), Information Adoption, and the stock investment of Vietnamese investors. Background: Misinformation spreads online, and a lack of strong information analysis skills can lead Vietnamese investors to make poor stock choices. By understanding how online conversations and information processing influence investment decisions, this research can help investors avoid these pitfalls. Methodology: This study applies Structural Equation Modelling (SEM) to investigate how non-professional investors react to online information and which information factors influence their investment decisions. The final sample includes 512 investors from 18 to 65 years old from various professional backgrounds (including finance, technology, education, etc.). We conducted a combined online and offline survey using a convenience sampling method from August to November 2023. Contribution: This study contributes to the growing literature on Electronic Word-of-Mouth (EWOM) and its impact on investment decisions. While prior research has explored EWOM in various contexts, we focus on Vietnamese investors, which can offer valuable insights into its role within a developing nation’s stock market. Investors, particularly those who are new or less experienced, are often susceptible to the influence of EWOM. By examining EWOM’s influence in Vietnam, this study sheds light on a crucial factor impacting investment behavior in this emerging market. Findings: The results show that EWOM has a moderate impact on the Information Adoption and investment decisions of Vietnamese stock investors. Information Quality (QL) is the factor that has the strongest impact on Information Adoption (IA), followed by Information Credibility (IC) and Attitude Towards Information (AT). Needs for Information (NI) only have a small impact on Information Adoption (IA). Finally, Information Adoption (IA) has a limited influence on investor decisions in stock investment. We also find that investors need to verify information through official sites before making investment decisions based on posts in social media groups. Recommendations for Practitioners: The findings suggest that state management and media agencies need to coordinate to improve the quality of EWOM information to protect investors and promote the healthy development of the stock market. Social media platform managers need to moderate content, remove false information, prioritize displaying authentic information, cooperate with experts, provide complete information, and personalize the experience to enhance investor trust and positive attitude. Securities companies need to provide complete, accurate, and updated information about the market and investment products. They can enhance investor trust and positive attitude by developing news channels, interacting with investors, and providing auxiliary services. Listed companies need to take the initiative to improve the quality of information disclosure and ensure clarity, comprehensibility, and regular updates. Use diverse communication channels and improve corporate governance capacity to increase investor trust and positive attitude. Investors need to seek information from reliable sources, compare information from multiple sources, and carefully check the source and author of the information. They should improve their investment knowledge and skills, consult experts, define investment goals, and build a suitable investment portfolio. Recommendation for Researchers: This study synthesized previous research on EWOM, but there is still a gap in the field of securities because each nation has its laws, regulations, and policies. The relationships between the factors in the model are not yet clear, and there is a need to develop a model with more interactive factors. The research results need to be further verified, and more research can be conducted on the influence of investor psychology, investment experience, etc. Impact on Society: This study finds that online word-of-mouth (EWOM) can influence Vietnamese investors’ stock decisions, but information quality is more important. Policymakers should regulate EWOM accuracy, fund managers should use social media to reach investors, and investors should diversify their information sources. Future Research: This study focuses solely on the stock market, while individual investors in Vietnam may engage in various other investment forms such as gold, real estate, or cryptocurrencies. Therefore, future research could expand the scope to include other investment types to gain a more comprehensive understanding of how individual investors in Vietnam utilize electronic word-of-mouth (EWOM) and adopt information in their investment decision-making process. Furthermore, while these findings may apply to other emerging markets with similar levels of financial literacy as Vietnam, they may not fully extend to countries with higher financial literacy rates. Hence, further studies could be conducted in developed countries to examine the generalizability of these findings. Finally, future research could see how EWOM’s impact changes over a longer period. Additionally, a more nuanced understanding of the information adoption process could be achieved by developing a research model with additional factors. http://www.informingscience.org/Publications/5346 Electronic Word-of-Mouth (EWOM) information adoption investment decisions social media groups stock investors eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-16 19 5353 article Kari Eller kari.eller@uga.edu Aim/Purpose: This conceptual review analyzes the designs of global health virtual communities of practice (VCoPs) programming reported in the empirical literature and proposes a new typology of their functioning. The purpose of this review is to provide clarity on VCoP learning stages of (co)evolution and insight into VCoP (re)development efforts to best meet member, organization, and network needs against an ever-evolving landscape of complexity in global health. Background: Since the COVID-19 pandemic, the field of global health has seen an uptick in the use of VCoPs to support continuous learning and improve health outcomes. However, evidence of how different combinations of programmatic designs impact opportunities for learning and development is lacking, and how VCoPs evolve as learning networks has yet to be explored. Methodology: Following an extensive search for literature in six databases, thematic analysis was conducted on 13 articles meeting the inclusion criteria. This led to the development and discussion of a new typology of VCoP phases of learning (co)evolution. Contribution: Knowledge gained from this review and the new categorization of VCoPs can support the functioning and evaluation of global health training programs. It can also provide a foundation for future research on how VCoPs influence the culture of learning organizations and networks. Findings: Synthesis of findings resulted in the categorization of global health VCoPs into five stages (slightly evolving, somewhat revolving, moderately revolving, highly revolving, and coevolving) across four design domains (network development, general member engagement before/after sessions, general member engagement during sessions, and session leadership). All global health VCoPs reviewed showed signs of adaptation and recommended future evolution. Recommendations for Practitioners: VCoP practitioners should pay close attention to how the structured flexibility of partnerships, design, and relationship development/accountability may promote or hinder VcoP’s continued evolution. Practitioners should shift perspective from short to mid- and long-term VCoP planning. Recommendation for Researchers: The new typology can stimulate further research to strengthen the clarity of language and findings related to VCoP functioning. Impact on Society: VCoPs are utilized by academic institutions, the private sector, non-profit organizations, the government, and other entities to fill gaps in adult learning at scale. The contextual implementation of findings from this study may impact VCoP design and drive improvements in opportunities for learning, global health, and well-being. Future Research: Moving forward, future research could explore how VCoP evaluations relate to different stages of learning, consider evaluation stages across the totality of VCoP programming design, and explore how best to capture VCoP (long-term) impact attributed to health outcomes and the culture of learning organizations and networks. http://www.informingscience.org/Publications/5353 global health virtual community of practice continuous learning complexity eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-19 19 5352 article Soukaina Mouhib soukaina.ine@gmail.com Ossama Cherkaoui ossama.cherkaoui@outlook.com Houda Anoun houda.anoun@gmail.com Mohammed Ridouani mohammed.ridouani@gmail.com Aim/Purpose: While existing literature has extensively explored factors influencing the success of big data projects and proposed big data maturity models, no study has harnessed machine learning to predict project success and identify the critical features contributing significantly to that success. The purpose of this paper is to offer fresh insights into the realm of big data projects by leveraging machine-learning algorithms. Background: Previously, we introduced the Global Big Data Maturity Model (GBDMM), which encompassed various domains inspired by the success factors of big data projects. In this paper, we transformed these maturity domains into a survey and collected feedback from 90 big data experts across the Middle East, Gulf, Africa, and Turkey regions regarding their own projects. This approach aims to gather firsthand insights from practitioners and experts in the field. Methodology: To analyze the feedback obtained from the survey, we applied several algorithms suitable for small datasets and categorical features. Our approach included cross-validation and feature selection techniques to mitigate overfitting and enhance model performance. Notably, the best-performing algorithms in our study were the Decision Tree (achieving an F1 score of 67%) and the Cat Boost classifier (also achieving an F1 score of 67%). Contribution: This research makes a significant contribution to the field of big data projects. By utilizing machine-learning techniques, we predict the success or failure of such projects and identify the key features that significantly contribute to their success. This provides companies with a valuable model for predicting their own big data project outcomes. Findings: Our analysis revealed that the domains of strategy and data have the most influential impact on the success of big data projects. Therefore, companies should prioritize these domains when undertaking such projects. Furthermore, we now have an initial model capable of predicting project success or failure, which can be invaluable for companies. Recommendations for Practitioners: Based on our findings, we recommend that practitioners concentrate on developing robust strategies and prioritize data management to enhance the outcomes of their big data projects. Additionally, practitioners can leverage machine-learning techniques to predict the success rate of these projects. Recommendation for Researchers: For further research in this field, we suggest exploring additional algorithms and techniques and refining existing models to enhance the accuracy and reliability of predicting the success of big data projects. Researchers may also investigate further into the interplay between strategy, data, and the success of such projects. Impact on Society: By improving the success rate of big data projects, our findings enable organizations to create more efficient and impactful data-driven solutions across various sectors. This, in turn, facilitates informed decision-making, effective resource allocation, improved operational efficiency, and overall performance enhancement. Future Research: In the future, gathering additional feedback from a broader range of big data experts will be valuable and help refine the prediction algorithm. Conducting longitudinal studies to analyze the long-term success and outcomes of Big Data projects would be beneficial. Furthermore, exploring the applicability of our model across different regions and industries will provide further insights into the field. http://www.informingscience.org/Publications/5352 big data projects success prediction key factors maturity model machine learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-29 19 5354 article Norman A Mooradian norman.mooradian@sjsu.edu Aim/Purpose: The rise of modern artificial intelligence (AI), in particular, machine learning (ML), has provided new opportunities and directions for knowledge management (KM). A central question for the future of KM is whether it will be dominated by an automation strategy that replaces knowledge work or whether it will support a knowledge-enablement strategy that enhances knowledge work and uplifts knowledge workers. This paper addresses this question by re-examining and updating a critical argument against KM by the sociologist of science Steve Fuller (2002), who held that KM was extractive and exploitative from its origins. Background: This paper re-examines Fuller’s argument in light of current developments in artificial intelligence and knowledge management technologies. It reviews Fuller’s arguments in its original context wherein expert systems and knowledge engineering were influential paradigms in KM, and it then considers how the arguments put forward are given new life in light of current developments in AI and efforts to incorporate AI in the KM technical stack. The paper shows that conceptions of tacit knowledge play a key role in answering the question of whether an automating or enabling strategy will dominate. It shows that a better understanding of tacit knowledge, as reflected in more recent literature, supports an enabling vision. Methodology: The paper uses a conceptual analysis methodology grounded in epistemology and knowledge studies. It reviews a set of historically important works in the field of knowledge management and identifies and analyzes their core concepts and conceptual structure. Contribution: The paper shows that KM has had a faulty conception of tacit knowledge from its origins and that this conception lends credibility to an extractive vision supportive of replacement automation strategies. The paper then shows that recent scholarship on tacit knowledge and related forms of reasoning, in particular, abduction, provide a more theoretically robust conception of tacit knowledge that supports the centrality of human knowledge and knowledge workers against replacement automation strategies. The paper provides new insights into tacit knowledge and human reasoning vis-à-vis knowledge work. It lays the foundation for KM as a field with an independent, ethically defensible approach to technology-based business strategies that can leverage AI without becoming a merely supporting field for AI. Findings: Fuller’s argument is forceful when updated with examples from current AI technologies such as deep learning (DL) (e.g., image recognition algorithms) and large language models (LLMs) such as ChatGPT. Fuller’s view that KM presupposed a specific epistemology in which knowledge can be extracted into embodied (computerized) but disembedded (decontextualized) information applies to current forms of AI, such as machine learning, as much as it does to expert systems. Fuller’s concept of expertise is narrower than necessary for the context of KM but can be expanded to other forms of knowledge work. His account of the social dynamics of expertise as professionalism can be expanded as well and fits more plausibly in corporate contexts. The concept of tacit knowledge that has dominated the KM literature from its origins is overly simplistic and outdated. As such, it supports an extractive view of KM. More recent scholarship on tacit knowledge shows it is a complex and variegated concept. In particular, current work on tacit knowledge is developing a more theoretically robust and detailed conception of human knowledge that shows its centrality in organizations as a driver of innovation and higher-order thinking. These new understandings of tacit knowledge support a non-extractive, human enabling view of KM in relation to AI. Recommendations for Practitioners: Practitioners can use the findings of the paper to consider ways to implement KM technologies in ways that do not neglect the importance of tacit knowledge in automation projects (which neglect often leads to failure). They should also consider how to enhance and fully leverage tacit knowledge through AI technologies and augment human knowledge. Recommendation for Researchers: Researchers can use these findings as a conceptual framework in research concerning the impact of AI on knowledge work. In particular, the distinction between replacement and enabling technologies, and the analysis of tacit knowledge as a structural concept, can be used to categorize and analyze AI technologies relative to KM research objectives. Impact on Society: The potential of AI on employment in the knowledge economy is a major issue in the ethics of AI literature and is widely recognized in the popular press as one of the pressing societal risks created by AI and specific types such as generative AI. This paper shows that KM, as a field of research and practice, does not need to and should not add to the risks created by automation-replacement strategies. Rather, KM has the conceptual resources to pursue a (human) knowledge enablement approach that can stand as a viable alternative to the automation-replacement vision. Future Research: The findings of the paper suggest a number of research trajectories. They include: Further study of tacit knowledge and its underlying cognitive mechanisms and structures in relation to knowledge work and KM objectives. Research into different types of knowledge work and knowledge processes and the role that tacit and explicit knowledge play. Research into the relation between KM and automation in terms of KM’s history and current technical developments. Research into how AI arguments knowledge works and how KM can provide an enabling framework. http://www.informingscience.org/Publications/5354 knowledge management knowledge work artificial intelligence automation knowledge enablement tacit knowledge abductive reasoning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-08-29 19 5366 article Wiwin Suwarningsih winak03@gmail.com Nuryani Nuryani nury012@brin.go.id Aim/Purpose: In this study, we developed a recommendation system model designed to support decision-makers in identifying consumers eligible for pay-later options via consensus-based decision-making. This approach was chosen due to the high and complex risks involved, such as delayed payments, challenges in reaching consumers, and issues of bad credit. Background: The “pay-later” option, which allows consumers to postpone payment for e-commerce purchases, offers convenience and flexibility but also introduces several challenges: (i) by enabling payment deferral, merchants face financial risks, including potential delays or defaults in payment, adversely affecting their cash flow and profitability; and (ii) this payment delay can also heighten the risk of fraud, including identity theft and unauthorized transactions. Methodology: This study initiated a risk analysis utilizing the ROAD process. Considering contemporary economic developments and advancements in neural networks, integrating these networks into risk assessment has become crucial. Consequently, model development involved the amalgamation of three deep learning methods – CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), and LSTM (Long Short-Term Memory) – to address various risk alternatives and facilitate multi-stage decision-making recommendations. Contribution: Our primary contribution is threefold. First, our study identified potential consumers by prioritizing those with the smallest associated problem consequence values. Second, we achieved an optimal recall value using a candidate generator. Last, we categorized consumers to assess their eligibility for pay-later rights. Findings: The findings from this study indicate that our multi-stage recommendation model is effective in minimizing the risk associated with consumer debt repayment. This method of consumer selection empowers policymakers to make informed decisions regarding which consumers should be granted pay-later privileges. Recommendations for Practitioners: This recommendation system is proposed to several key parties involved in the development, implementation, and use of pay-later systems. These parties include E-commerce Executive Management for financial analysis and risk evaluation, the Risk Management Team to assess and manage risks related to users utilizing Pay-Later services, and Sales Managers to integrate Pay-Later services into sales strategies. Recommendation for Researchers: Advanced fraud detection mechanisms were implemented to prevent unauthorized transactions effectively. The goal was to cultivate user confidence in the safety of their financial data by ensuring secure payment processing. Impact on Society: Ensuring consumers understand the terms and conditions of pay-later arrangements, including interest rates, repayment schedules, and potential fees, is crucial. Providing clear and transparent information, along with educating consumers about their financial responsibilities, helps prevent misunderstandings and disputes. Future Research: Our future development plans involve the ongoing assessment of the system’s performance to enhance prediction accuracy. This includes updating models and criteria based on feedback and changes in economic or market conditions. Upholding compliance with security and data privacy regulations necessitates the implementation of protective measures to safeguard consumer information. The implementation of such a system requires careful consideration to ensure fairness and adherence to legal standards. Additionally, it is important to acknowledge that algorithms and models may evolve over time through the incorporation of additional data and continuous evaluations. http://www.informingscience.org/Publications/5366 pay-later system recommendation multi-stage analysis ROAD CNN RNN LSTM eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-09-05 19 5367 article Yonathan Dri Handarkho yonathan.handarkha@uajy.ac.id Megia Nofita megia.nofita@staff.debritto.sch.id Paulus Mudjihartono paulus.mudjihartono@uajy.ac.id Aim/Purpose: This study aims to develop a theoretical model based on the SOR (Stimulus – Organism – Response) framework and GETAMEL, which cover environmental, personal, and learning quality aspects to identify factors influencing students’ acceptance of the use of LMS in high schools, especially after COVID-19 pandemic. Background: After the COVID-19 pandemic, many high schools reopened for in-person classes, which led to a decreased reliance on e-learning. The shift from online to traditional face-to-face learning has influenced students’ perceptions of the importance of e-learning in their academic activities. Consequently, high schools are facing the challenge of ensuring that LMS can still be integrated into the teaching-learning process even after the pandemic ends. Therefore, this study proposes a model to investigate the factors that affect students’ actual use of LMS in the high school environment. Methodology: This study used 890 high school students to validate the theoretical model using Structural Equation Modeling (SEM) analysis to deliver direct, indirect, and moderating effect analysis. Contribution: This study combines SOR and acceptance theory to provide a model to explain high school students’ intention to use technology. The involvement of direct, indirect, and moderating effects analysis offers an alternative result and discussion and is considered another contribution of this study from a technical perspective. Findings: The findings show that perceived satisfaction is the most influential factor affecting the use of LMS, followed by perceived usefulness. Meanwhile, from indirect effect analysis, subjective norms and computer self-efficacy were found to indirectly affect actual use through perceived usefulness as a mediator. Content quality was also an indirect predictor of the actual use of LMS through perceived satisfaction. Further, the moderating effect of age influenced perceived satisfaction’s direct effect on actual use. Recommendations for Practitioners: This study provides practical recommendations that can be useful to high schools and other stakeholders in improving the use of LMS in educational environments. Specifically, exploring the implementation of LMS in high schools prior to and following the COVID-19 outbreak can offer valuable insights into the changing educational environment. Recommendation for Researchers: The results of this study present a significant theoretical contribution by employing a comprehensive approach to explain the adoption of LMS among high school students after the COVID-19 pandemic. This contribution extends the GETAMEL framework by incorporating environmental, personal, and learning quality aspects while also analyzing both direct and indirect effects, which have not been previously explored in this context. Impact on Society: This study provides knowledge to high schools for improving the use of LMS in educational environments post-COVID-19, leading to an enhanced teaching-learning process. Future Research: This study, however, is limited to collecting responses exclusively from Indonesian respondents. Therefore, the replication of the finding needs to consider the characteristics and culture similar to Indonesian students, which is regarded as the limitation of this study. http://www.informingscience.org/Publications/5367 SEM Learning Management System (LMS) high school GETAMEL SOR eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-09-12 19 5373 article Yekti Wirani yektiwirani@cs.ui.ac.id Dana Indra Sensuse dana@cs.ui.ac.id Deden Sumirat Hidayat dede025@brin.go.id Erisva Hakiki Purwaningsih erisvaha.kiki@ui.ac.id Yudho Giri Sucahyo yudho@cs.ui.ac.id Aim/Purpose: This research aims to design a website-based group decision support system (DSS) user interface to support an integrated and sustainable waste management plan in Jagatera. The main focus of this research is to design a group DSS to help Jagatera prioritize several waste alternatives to be managed so that Jagatera can make the right decisions to serve the community. Background: The Indonesian government and various stakeholders are trying to solve the waste problem. Jagatera, as a waste recycling company, plays a role as a stakeholder in managing waste. In 2024, Jagatera plans to accept all waste types, which impacts the possibility of increasing waste management costs. If Jagatera does not have a waste management plan, this will impact reducing waste management services in the community. To solve this problem, the group DSS assists Jagatera in prioritizing waste based on aspects of waste management cost. Methodology: Jagatera, an Indonesian waste recycling company, is implementing a group DSS using the soft system methodology (SSM) method. The SSM process involves seven stages, including problem identification, problem explanation using rich pictures, system design, conceptual model design, real-life comparison, changes, and improvement steps. The final result is a prototype user interface design addressing the relationship between actors and the group DSS. The analytical hierarchy process (AHP) method prioritized waste based on management costs. This research obtained primary data from interviews with Jagatera management, a literature review regarding the group DSS, and questionnaires to determine the type of waste and evaluate user interface design. Contribution: This research focuses on determining waste handling priorities based on their management. It contributes the DSS, which uses a decision-making approach based on management groups developed using the SSM and AHP methods focused on waste management decisions. It also contributes to the availability of a user interface design from the DSS group that explains the interactions between actors. The implications of the availability of DSS groups in waste recycling companies can help management understand waste prioritization problems in a structured manner, increase decision-making efficiency, and impact better-quality waste management. Combining qualitative approaches from SSM to comprehend issues from different actor perspectives and AHP to assist quantitative methods in prioritizing decisions can yield theoretical implications when using the SSM and AHP methods together. Findings: This research produces a website-based group DSS user interface design that can facilitate decision-making using AHP techniques. The user interface design from the DSS group was developed using the SSM approach to identify complex problems at waste recycling companies in Indonesia. This study also evaluated the group DSS user interface design, which resulted in a score of 91.67%. This value means that the user interface design has met user expectations, which include functional, appearance, and comfort needs. These results also show that group DSS can enhance waste recycling companies’ decision-making process. The results of the AHP technique using all waste process information show that furniture waste, according to the CEO, is given more priority, and textile waste, according to the Managing Director. Group DSS developed using the AHP method allows user actors to provide decisions based on their perspectives and authority. Recommendations for Practitioners: This research shows that the availability of a group DSS is one of the digital transformation efforts that waste recycling companies can carry out to support the determination of a sustainable waste management plan. Managers benefit from DSS groups by providing a digital decision-making process to determine which types of waste should be prioritized based on management costs. Timely and complete information in the group DSS is helpful in the decision-making process and increases organizational knowledge based on the chosen strategy. Recommendation for Researchers: Developing a group DSS for waste recycling companies can encourage strategic decision-making processes. This research integrates SSM and AHP to support a comprehensive group DSS because SSM encourages a deeper and more detailed understanding of waste recycling companies with complex problems. At the same time, AHP provides a structured approach for recycling companies to make decisions. The group DSS that will be developed can be used to identify other more relevant criteria, such as environmental impact, waste management regulations, and technological capabilities. Apart from more varied criteria, the group DSS can be encouraged to provide various alternatives such as waste paper, metal, or glass. In addition to evaluating the group DSS’s user interface design, waste recycling companies need to consider training or support for users to increase system adoption. Impact on Society: The waste problem requires the role of various stakeholders, one of which is a waste recycling company. The availability of a group DSS design can guide waste recycling companies in providing efficient and effective services so that they can respond more quickly to the waste management needs of the community. The community also gets transparent information regarding their waste management. The impact of good group DSS is reducing the amount of waste in society. Future Research: Future research could identify various other types of waste used as alternatives in the decision-making process to illustrate the complexity of the prioritization process. Future research could also identify other criteria, such as environmental impact, social aspects of community involvement, or policy compliance. Future research could involve decision-makers from other parties, such as the government, who play an essential role in the waste industry. http://www.informingscience.org/Publications/5373 group decision support system analytical hierarchy process soft system methodology waste recycling company user interface design DSS eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-09-20 19 5364 article Chin Wei Chong cwchong@mmu.edu.my Adedapo O Ojo ae0377@coventry.ac.uk Abdulrauf Ali Aboulqassim Salam AbdulraufAliSalam@gmail.com Christine Nya-Ling Tan n.l.tan@massey.ac.nz Aim/Purpose: This study investigates the intention to invest in online peer-to-peer (P2P) lending platforms among the bottom 40% (B40) Malaysian households by income. Background: The B40 group citizens earn less than USD 1,096.00 (i.e., RM 4,850.00) in monthly household income, thereby possessing relatively small capital investments suitable for online P2P lending. Methodology: Drawing on the technology acceptance model (TAM), this research developed and tested the relevant hypotheses with data collected from 216 respondents. The partial least square structural equation modelling (PLS-SEM) technique was employed to analyse the collected data. Contribution: This study contributes to the body of knowledge on financial inclusion by demonstrating the relevance of modified TAM in explaining the intention to invest in online P2P lending platforms among investors with lower disposable income (i.e., the B40 group in Malaysia). Findings: The findings revealed that information quality, perceived risk, and perceived ease of use are relevant to B40 investment intention in P2P online lending platforms. However, contrary to expectations, trust and financial literacy are insignificant predictors of B40 investment intention. Recommendations for Practitioners: The P2P lending platform operators could enhance financial inclusion among the B40 group by ensuring borrowers provide sufficient, relevant, and reliable information with adequate security measures to minimise risk exposure. The financial regulators should also conduct periodic audits to ensure that the operators commit to enhancing information quality, platform security, and usability. Recommendation for Researchers: The intention to invest in online P2P lending platforms among the B40 group could be enhanced by improving information quality and user experience, addressing perceived risks, reassessing trust-building strategies and financial literacy initiatives, and adopting holistic, interdisciplinary approaches. These findings suggest targeted strategies to enhance financial inclusion and investment participation among B40 investors. Impact on Society: The study’s findings hold significant implications for financial regulators and institutions, such as the Securities Commission Malaysia, Bank Negara Malaysia, commercial and investment banks, and insurance companies. By focusing on these key determinants, policymakers can design targeted interventions to improve the accessibility and attractiveness of P2P lending platforms for B40 investors. Enhanced information quality and ease of use can be mandated through regulatory frameworks, while effective risk communication and mitigation strategies can be developed to build investor confidence. These measures can collectively promote financial growth and inclusion, supporting broader economic development goals. Future Research: Future research could expand the sample size to consider older B40 individuals across different countries and use a longitudinal survey to assess the actual investment decision of the B40 investors. http://www.informingscience.org/Publications/5364 behavioural intention B40 group Malaysia online P2P Fintech investment financial inclusion eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-10-09 19 5381 article Pooja Chopra pochopra.pc@gmail.com Prachi Verma drprachiverma@gmail.com Renu Lamba renu.chd@gmail.com Monica Bedi monica@pu.ac.in Aim/Purpose: The last decade has witnessed a tremendous progression in mobile penetration across the world and, most importantly, in developing countries like India. This research aims to investigate and analyze the factors influencing the adoption of mobile payments (M-payments) in the Indian rural population. This, in turn, would bring about positive changes in the lives of people in these countries. Background: A conceptual framework was worked upon using UTAUT as a foundation, which included constructs, namely, facilitating conditions, social influences, performance expectancy, and effort expectancy. The model was further extended by incorporating the awareness construct of m-payments to make it more comprehensive and to understand behavioral intentions and usage behavior for m-payments in rural India. Methodology: A questionnaire-based study was conducted to collect primary data from 410 respondents residing in rural areas in the state of Punjab. Convenience sampling was conducted to collect the data. Structural equation modeling was used to conduct statistical analysis, including exploratory and confirmatory factor analyses. Contribution: A new conceptual model for M-payments adoption in rural India was developed based on the study’s findings. Using the findings of the study, marketers, policymakers, and academicians can gain insight into the factors that motivate the rural population to use M-payments. Findings: The study has found that M-payment Awareness (AW) is the strongest factor within the proposed model for deeper diffusion of M-payments in rural areas in the state of Punjab. Performance expectancy (PE), effort expectancy (EE), social influences (SI), and facilitating conditions (FC) are also positively and significantly related to behavioral intentions for using M-payments among the Indian rural population in the state of Punjab. Recommendations for Practitioners: M-payments are emerging as a new mode of transactions among the Indian masses. The government needs to play a pivotal role in advocating the benefits linked with the usage of M-payments by planning financial literacy and awareness campaigns, promoting transparency and accountability of the intermediaries, and reducing transaction costs of using M-payments. Mobile manufacturing companies should come up with devices that are easy to use and incorporate multilanguage mobile applications, especially for rural areas, as India is a multi-lingual country. A robust regulatory framework will not only shape consumer trust but also prevent privacy breaches. Recommendation for Researchers: It is recommended that a comparative study among different M-payment platforms be conducted by exploring constructs such as usefulness and ease of use. However, the vulnerability of data leakage may result in insecurity and skepticism about its adoption. Impact on Society: India’s rural areas have immense potential for adoption of M-payments. Appropriate policies, awareness drives, and necessary infrastructure will boost faster and smoother adoption of M-payments in rural India to thrive in the digital economy. Future Research: The adapted model can be further tested with moderating factors like age, gender, occupation, and education to understand better the complexities of M-payments, especially in rural areas of India. Additionally, cross-sectional studies could be conducted to evaluate the behavioral intentions of different sections of society. http://www.informingscience.org/Publications/5381 UTAUT rural India facilitating conditions social influences performance expectancy effort expectancy M-payments awareness behavioral intentions usage behavior eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-10-16 19 5369 article Theodosia Yunita Durman yunidurman20@gmail.com Reny Nadlifatin reny.nadlifatin@gmail.com Aim/Purpose: This study investigated factors influencing the intention to engage in green innovation among small and medium enterprises (SMEs) in the tourism sector, using an integrated approach from the pro-environmental planned behavior (PEPB) and technology organization environment (TOE) models. Background: Green innovation is a long-term strategy aimed at addressing environmental challenges in the Indonesian tourism sector, especially those related to SMEs in culinary, accommodation, transportation, and creative industries. While prior research primarily focused on innovation characteristics and various behavioral intentions towards new technologies, this study pioneered an approach to understanding green innovation practices among SMEs by examining behavioral intention and the influence of internal organizational and external environmental factors. This was achieved through the PEPB model, which extends the theory of planned behavior (TPB) by incorporating perceived authority support and perceived environmental concern and integrating it with the TOE model. This comprehensive approach was crucial for understanding SME motivations, needs, and challenges in adopting green innovation, thereby supporting environmental sustainability. Methodology: Data were collected through offline and online questionnaires and interviews with 405 SMEs that had implemented green innovation as respondents. The theoretical model was tested using partial least squares structural equation modeling (PLS-SEM) with top-level constructs. Contribution: This research contributed to the development and validation of an integrated model for green innovation in SMEs, offering insights and recommendations for all stakeholders in the tourism sector to formulate effective green innovation strategies. Findings: This research revealed that the integrated model of pro-environmental planned behavior and technology organization environment successfully explained 71% of the factors influencing the intention to engage in green innovation for SMEs in the tourism sector. Perceived authority support emerged as the strongest factor, while perceived behavioral control was identified as a weaker factor. Recommendations for Practitioners: The research findings recommended that SMEs in the tourism sector focus on customer satisfaction and operational efficiency and optimize the recruitment and training processes of resources to maximize success in adopting environmentally friendly innovations. Meanwhile, for the government, providing support, incentives, and stringent environmental regulations could encourage sustainable business practices. Recommendation for Researchers: The research findings recommended that SMEs in the tourism sector focus on customer satisfaction and operational efficiency and optimize the recruitment and training processes of resources to maximize success in adopting environmentally friendly innovations. Meanwhile, for the government, providing support, incentives, and stringent environmental regulations could encourage sustainable business practices. Impact on Society: Examining the factors influencing the intention to engage in green innovation among SMEs in the tourism sector carried significant social implications. The findings contributed to recommending strategies for businesses and stakeholders such as the government, investors, and tourists to collectively strive to minimize environmental damage in tourist areas through the implementation of green innovation. Future Research: There are several promising avenues to explore to enhance future research. Expanding the scope to include diverse regions and industries and using additional approaches, such as leadership theory and management commitment theories, can increase the R-squared value. Additionally, broadening the profile of interviewees to obtain a more comprehensive understanding of the intention to engage in green innovation should be considered. http://www.informingscience.org/Publications/5369 behavioral intention green innovation PEPB TOE SMEs tourism eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-10-20 19 5371 article Mohammad Azzeh m.azzeh@psut.edu.jo Maher Sami Farouqa mah20198075@std.psut.edu.jo Aim/Purpose: This research utilized a learn-to-rank algorithm to provide medical recommendations to prescribers. The algorithm has been utilized in other domains, such as information retrieval and recommender systems. Background: Ranking the possible medical treatments according to diagnoses of the medical cases is very beneficial for doctors, especially during the coding process. Methodology: We developed two deep learning pointwise learn-to-rank models within one prediction pipeline: one for predicting the top possible active ingredients from disease features, the other for ranking actual medicines codes from diseases and the ingredients features. Contribution: A new learn-to-rank deep learning model has been developed to rank medical procedures based on datasets collected from insurance companies. Findings: We ran 18 cross-validation trials on a confidential dataset from an insurance company. We obtained an average normalized discounted cumulative gain (NDCG@8) of 74% with a 5% standard deviation as a result of all 18 experiments. Our approach outperformed a known approach used in the information retrieval domain in which data is represented in LibSVM format. Then, we ran the same trials using three learn-to-rank models – pointwise, pairwise, and listwise – which yielded average NDCG@8 of 71%, 72%, and 72%, respectively. Recommendations for Practitioners: The proposed model provides an insightful approach to helping to manage the patient’s treatment process. Recommendation for Researchers: This research lays the groundwork for exploring various applications of data science techniques and machine learning algorithms in the medical field. Future studies should focus on the significant potential of learn-to-rank algorithms across different medical domains, including their use in cost-effectiveness models. Emphasizing these algorithms could enhance decision-making processes and optimize resource allocation in healthcare settings. Impact on Society: This will help insurance companies and end users reduce the cost associated with patient treatment. It also helps doctors to choose the best procedure and medicines for their patients. Future Research: Future research is required to investigate the impact of medicine data at a granular level. http://www.informingscience.org/Publications/5371 learn to rank medicine ranking decision making eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-10-22 19 5386 article Budhi Irawan budhiirawan@telkomuniversity.ac.id Nugraha Priya Utama utama@informatika.org Rinaldi Munir rinaldi@informatika.org Ayu Purwarianti ayu@itb.ac.id Aim/Purpose: This study presents a novel deep learning-based framework designed to enhance spontaneous micro-expression recognition by effectively increasing the amount and variety of data and balancing the class distribution to improve recognition accuracy. Background: Micro-expression recognition using deep learning requires large amounts of data. Micro-expression datasets are relatively small, and their class distribution is not balanced. Methodology: This study developed a framework using a deep learning-based model to recognize spontaneous micro-expressions on a person’s face. The framework also includes several technical stages, including image and data preprocessing. In data preprocessing, data augmentation is carried out to increase the amount and variety of data and class balancing to balance the distribution of sample classes in the dataset. Contribution: This study’s essential contribution lies in enhancing the accuracy of micro-expression recognition and overcoming the limited amount of data and imbalanced class distribution that typically leads to overfitting. Findings: The results indicate that the proposed framework, with its data preprocessing stages and deep learning model, significantly increases the accuracy of micro-expression recognition by overcoming dataset limitations and producing a balanced class distribution. This leads to improved micro-expression recognition accuracy using deep learning techniques. Recommendations for Practitioners: Practitioners can utilize the model produced by the proposed framework, which was developed to recognize spontaneous micro-expressions on a person’s face, by implementing it as an emotional analysis application based on facial micro-expressions. Recommendation for Researchers: Researchers involved in the development of a spontaneous micro-expression recognition framework for analyzing hidden emotions from a person’s face are playing an essential role in advancing this field and continue to search for more innovative deep learning-based solutions that continue to explore techniques to increase the amount and variety of data and find solutions to balancing the number of sample classes in various micro-expression datasets. They can further improvise to develop deep learning model architectures that are more suitable and relevant according to the needs of recognition tasks and the various characteristics of different datasets. Impact on Society: The proposed framework could significantly impact society by providing a reliable model for recognizing spontaneous micro-expressions in real-world applications, ranging from security systems and criminal investigations to healthcare and emotional analysis. Future Research: Developing a spontaneous micro-expression recognition framework based on spatial and temporal flow requires the learning model to classify optimal features. Our future work will focus more on exploring micro-expression features by developing various alternative learning models and increasing the weights of spatial and temporal features. http://www.informingscience.org/Publications/5386 micro-expression spatio-temporal data augmentation class balancing 3DCNN vision deep learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-10-23 19 5384 article Basil Alzougool b.alzougool@gmail.com Sumayya Banna sumayya@aou.edu.kw Aim/Purpose: This study aims to explore the use of mobile health applications (mHealth apps) by lay users in Kuwait. Specifically, it seeks to: (i) identify and highlight the impact of factors that contribute to their use of mHealth apps and (ii) validate a model of these users’ usage of mHealth apps. Background: The advancement of information technologies has paved the way for efficiency and effectiveness in healthcare sectors in developed countries. Kuwait has attempted to revolutionise healthcare systems through mobile applications of information technology solutions to educate users on better methods of receiving customised health services. However, end-user usage of mHealth apps remains in the infancy in developing countries, including Kuwait. Lay users are often vulnerable and frequently overlooked by researchers and health technology providers. Methodology: A cross-sectional study was conducted among 225 lay users of mHealth apps in Kuwait using an online questionnaire to achieve the study objectives. A purposive sampling method utilising convenience and snowballing sampling techniques was used in which all the respondents were lay users. Descriptive statistics, Pearson correlation, and regression analyses were employed to analyse the collected data. Contribution: The study contributes to the extant literature on health informatics and mHealth by providing a comprehensive understanding of how technological, social, and functional factors are related to mHealth apps in the context of developing countries. It identifies key drivers of mHealth app use, suggests expanding the TAM model, and facilitates comparisons with developed countries, addressing gaps in mHealth research. Findings: Four factors (i.e., perceived trust (PT), perceived ease of use (PEU) and behaviour control (PBC), perceived usefulness (PU), and subjective norms (SN)) were identified that influence the use of mHealth apps. These four identified factors also contributed to lay users’ use of these mHealth apps. Among these four factors, perceived trust (PT) was the main contributor to lay users’ use of these mHealth apps. Recommendations for Practitioners: Based on the empirical results, this study provides feasible recommendations for the government, healthcare providers, and developers of mHealth apps. The findings urge developers to enhance app functionality by prioritising privacy and security to build user trust while outlining guidelines for future development focused on user-centric design and compliance with data privacy regulations. Additionally, the government should establish supportive policies and funding, ensure regulatory oversight, and promote public awareness to foster trust. Healthcare providers should integrate mHealth apps into their services, train staff for practical use, gather users’ feedback, and collaborate with developers to create tailored healthcare solutions. Future Research: Additional research is required to apply probability sampling techniques and increase the sample size to generate more reliable and generalisable findings. Additionally, the young age segment must be considered here, and research must be extended to consider the moderating role of demographic factors like age, gender, and educational levels to better understand the adoption of mHealth apps. http://www.informingscience.org/Publications/5384 lay users health information mHealth Kuwait mobile health applications eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-11-11 19 5389 article Abhimanyu Pal phd14320210002@stu.srmuniversity.ac.in Upendra Pratap Singh upendrasingh@srmuniversity.ac.in Ashish Kumar ashishdeshwal49@gmail.com Aim/Purpose: This study investigates the factors that affect the repurchase intentions of Generation Z consumers in India’s online shopping industry, focusing on combining the Expectation-Confirmation Model (ECM) and Extended Technology Acceptance Model (E-TAM). The aim is to understand the intricate behaviors that shape technology adoption and sustained usage, which are essential for retaining customers in e-commerce. Background: Social media and other online platforms have significantly influenced daily life and become essential communication tools owing to technological advancements. Online shopping is no exception, offering a range of product choices, information, and convenience compared with traditional commerce. Indian retailers recognize this trend as an opportunity to promote their brands through e-shopping platforms, leading to increased competition. Generation Z comprises 32% of the world’s population and is a significant emerging customer base in India. Numerous studies have been conducted to study customers’ repurchase intention in the online shopping domain, but few studies have explicitly focused on Generation Z as a customer base. This study aims to comprehensively understand the topic and investigate the variables that impact consumers’ online repurchase intention by examining their post-adoption behavioral processes. Methodology: The study employed a quantitative research design with structural equation modeling using AMOS to analyze responses from 410 participants. This method thoroughly examined hypotheses regarding factors affecting repurchase intention (security, ease of use, privacy, and internet self-efficacy) and the mediating role of e-satisfaction. Contribution: This study makes a unique contribution to the field of e-commerce by focusing on Generation Z in India, a rapidly growing demographic in the e-commerce industry. The results on the mediating role of e-satisfaction have significant implications for e-retailers seeking to enhance customer retention strategies and gain a competitive edge in the market. Findings: The research findings underscore the significant influence of security, ease of use, and internet self-efficacy on repurchase intentions, with e-satisfaction playing a pivotal role as a mediating factor. Notably, while privacy concerns did not directly impact repurchase intentions, they displayed considerable influence when mediated by e-satisfaction, highlighting the intricate interplay between these variables in the context of online shopping, which is the unique finding of this study. Recommendations for Practitioners: This study has several significant implications for practitioners. Effectively addressing computer-related individual differences, such as computer self-efficacy, is crucial for boosting online customers’ repurchase intention. For instance, if an e-retailer intends to target Generation Z customers, they should collaborate with IT professionals and develop various computer literacy programs on online streaming platforms, such as YouTube. These programs will enhance target customers’ confidence in online shopping portals and increase their online repeat purchases. Additionally, practitioners should strive to improve the online shopping experience by making the portal user-friendly. Generation Z is accustomed to a fast Internet experience, so they prefer that the process of completing online transactions is swift with fewer clicks. The search for products, payments, and redress should not be tedious. Furthermore, the primary objective of the e-retailer should be to satisfy customers, as satisfied customers repeat their purchases and increase overall profitability. Recommendation for Researchers: The current study was conducted in the Delhi-NCR region of India, and its findings could serve as a basis for future research. For instance, the scale devised in this study could be utilized to examine the impact of cash-on-delivery as a payment method on purchase intention across the country. Alternatively, a comparative analysis could be conducted to compare cash-on-delivery effects in various countries. Impact on Society: The study’s findings enable stakeholders in the online shopping industry to comprehend the post-adoption behavior of Generation Z users and augment existing literature by establishing a correlation between determinants that impact repurchase intention and e-satisfaction, which serves as a mediator. Future Research: This study examines the factors that impact the propensity of Generation Z shoppers to engage in repeat online purchases. This study focuses on India, where the Generation Y (millennial) customer base is also substantial within the online shopping market. Future research could compare the shopping habits of Generation Z and Generation Y customers, as the latter may place greater importance on privacy and security. Additional studies could broaden the scope of this research and explore the comparative viewpoints of both generations. Also, it would be advantageous to conduct in-depth interviews and longitudinal studies to acquire a more in-depth comprehension of the evolving digitalization of shopping. http://www.informingscience.org/Publications/5389 repurchase intention e-satisfaction ease of use security privacy concerns internet self-efficacy Generation Z e-commerce eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-12-08 19 5405 article Sylvain Chartier sylvain.chartier@uottawa.ca Paulo Mauricio Gonçalves Júnior paulogoncalves@recife.ifpe.edu.br Aim/Purpose: This paper describes how to use a multilayer perceptron to improve concept drift recovery in streaming environments. Background: Classifying instances in a data stream environment with concept drift is a challenging topic. The base learner must be adapted online to the current data. Several data mining algorithms have been adapted/used to this type of environment. In this study, two techniques are used to speed up the adaptation of an artificial neural network to the current data, increasing its predictive accuracy while detecting the concept drift sooner. Methodology: Experiments were performed to analyze how some techniques behave in different scenarios and compare them with other classifiers built to deal with data streams and concept drifts. Contribution: This study suggests two techniques to improve the classification results: an embedded concept drift detection method to identify when a change has occurred and setting the learning rate to a higher level whenever a new concept is being learned to give more weight to recent instances, with its value decreased over time. Findings: Results indicate that gradually reducing the learning rate with an embedded concept drift detector has better statistical results than other single classifiers built to deal with data streams and concept drifts. Recommendations for Practitioners: Based on the empirical results, this study provides recommendations on how to improve the multilayer perceptron in data stream environments suffering from concept drifts. Recommendation for Researchers: Researchers should conduct investigations to increase the number of base classifiers used in data stream environments and in situations where concept drifts occur. Impact on Society: The objective of this study is to increase the use of multilayer perceptrons in data stream environments suffering from concept drifts, as nowadays, Hoeffding Trees and Naive Bayes are the base classifiers mostly used. Future Research: Additional research includes adapting the online learning rate by increasing/decreasing it based on the performance of the Multilayer Perceptron. This scheme would allow the removal of parameters that must be set by the user, like learning rate upper bound and number of instances to return to the stable value. http://www.informingscience.org/Publications/5405 data streams concept drift multilayer perceptron online learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-12-15 19 5409 article Irina Zlotnikova zlotnikovai@biust.ac.bw Hlomani Hlomani hlomanihb@biust.ac.bw Tshiamo Sigwele sigwelet@biust.ac.bw Tshepiso L. Mokgetse mt21100029@studentmail.biust.ac.bw Aim/Purpose: The problem addressed by this research is the struggle of Botswana’s livestock sector to implement effective animal traceability systems due to limited interoperability, inadequate data integration, reliance on open grazing systems, and systemic challenges like high mortality, theft, and disease outbreaks. These challenges collectively undermine animal traceability system competitiveness and compliance with international trade standards. Background: The paper addresses the problem by developing the Animal Traceability Ontology (ATO), standardizing data representation, and enabling seamless data sharing among stakeholders in Botswana’s livestock industry. This ontology improves interoperability, real-time data integration, and trade compliance, ultimately enhancing disease management and compliance with international trade standards. Methodology: The paper employed a mixed-methods research design, combining qualitative data collection through interviews and focus groups with stakeholders (such as farmers, veterinarians, and officials) and quantitative data through structured questionnaires. The ontology was developed using METHONTOLOGY, a widely adopted approach for ontology creation, and was evaluated using tools such as Protégé, Apache Jena Fuseki, and the Pellet reasoner. The research sample included key stakeholders in Botswana’s livestock industry, including farmers, veterinary officers, and representatives from the Botswana Meat Commission. Contribution: This research developed the ATO to enhance data quality and interoperability in livestock traceability systems. The ATO’s practical implications include fostering stakeholder collaboration, supporting small-scale farmers, enabling real-time disease management, and driving sustainable livestock practices. It addresses data heterogeneity and limited integration, providing a scalable framework for decision-making and compliance with international trade standards and offering a practical model to improve traceability across diverse systems. Findings: The evaluation of the ATO assessed its structural, usability, and functional aspects, demonstrating its logical adequacy, stakeholder relevance, and performance efficiency. A comparative analysis with the Animal Health Ontology (AHO) revealed the ATO’s superior inheritance richness, relationship diversity, and tailored design for precise traceability applications, ensuring enhanced data integration, semantic clarity, and practical functionality for animal traceability systems. The ATO was, therefore, found to be a robust solution to Botswana’s livestock traceability challenges. The ATO has the potential to enhance Botswana’s livestock traceability by improving data quality, interoperability, real-time processing, and stakeholder collaboration, offering scalable tools for disease management, trade compliance, and sustainable livestock management. Recommendations for Practitioners: Farmers should adopt affordable, user-friendly tools like mobile apps or compatible devices to streamline data entry and tracking. Regulatory agencies should promote training, ensure compliance with traceability standards, and provide subsidies for small-scale farmers. Collaboration among stakeholders will enhance system usability, real-time updates, and alignment with international trade standards. Recommendation for Researchers: The paper recommends that researchers leverage METHONTOLOGY for systematic ontology development, use tools like Protégé for evaluation, apply the ATO framework (or similar frameworks) to improve interoperability in other sectors, investigate its role in compliance and disease management, and examine its real-time data integration capabilities. Impact on Society: The ATO has the potential to positively impact farmers by streamlining livestock management, enabling efficient disease monitoring, reducing mortality rates, and boosting productivity and economic stability. For regulatory agencies, it ensures adherence to international trade standards, facilitates global market access, enhances public health, strengthens food safety, and bolsters national food security. Additionally, the ATO fosters collaboration and seamless data sharing among veterinarians, governmental and parastatal organizations (e.g., the BMC), and law enforcement, enhancing disease management, expanding market opportunities, and mitigating livestock theft. Future Research: Future research should explore the scalability of ATO (or similar ontologies), integrate advanced technologies like blockchain and IoT, develop simplified versions for resource-limited settings, expand research on real-time data analytics, and collaborate with industry stakeholders for practical alignment. http://www.informingscience.org/Publications/5409 ontology-based knowledge management data interoperability livestock traceability systems trade compliance systems integration data quality enhancement eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-12-23 19 5403 article Maheswari N maheswari.n@vit.ac.in Arunachalam V arunachalam3342@gmail.com Aim/Purpose: This study aims to propose an efficient implementation of identifying and detecting offensive and hate comments on social media platforms for Dravidian languages. Background: There has been a notable increase in hate comments on social media platforms in recent years. Hate language and hate speech are expressions of conflicts that arise between different groups, both within and across civilizations. This toxic behavior has a detrimental impact on individuals, resulting in disagreements, arguments, political conflicts, and even mental health issues such as cyberbullying, depression, and anxiety. In recent years, research on offensive detection has expanded beyond English and Hindi languages to include other languages such as Urdu, Spanish, Arabic, and more. An ongoing trend in modern research involves gathering data from prominent social media platforms such as YouTube, Instagram, and Twitter to train models in proposed studies. Methodology: The objective of this work is to identify and detect offensive or hateful comments on social media platforms dedicated explicitly to the Dravidian languages - Tamil, Kannada, and Malayalam. The dataset, HASOC-Offensive Language Identification track in Dravidian Code-Mix FIRE 2021, undergoes several proposed preprocessing procedures on the YouTube comments. Tokens were created to represent the attributes. The pre-trained models utilizing transformers were trained using tokenized data. The efficacy of different binary classifiers has been assessed and analyzed using the embedded vectors derived from the models. The mBert with the classifier model CATBOOST with GSCV achieved F1 scores for Tamil, Malayalam, and Kannada are 0.94, 0.98, and 0.82, respectively. Precision and recall values for Tamil, Malayalam, and Kannada are 0.94, 0.98, and 0.82, and 0.94, 0.98, and 0.83, respectively. Contribution: This research produced an approach to improve the results and F1-score by performing an improved preprocessing method using stemming and stopword removal. The native and English-coded comment data used in this work were not discussed much in the previous works. Findings: The findings of this study indicated that the preprocessing work combined both the native language data and the English-coded language. It describes the improved models and performance of the results in order to detect hate speech. Recommendations for Practitioners: This study is expected to be valuable for social media platforms and other review sites to separate offensive comments from good and bad ones. This is also valuable for content creators and users in improving their ideas and content and also helps in preventing cyber harassment and bullying. Recommendation for Researchers: This study discussed the use of stemming and stopword removal and how it improved the detection of hate comments for both native and codemix comments in social media. Impact on Society: This work helps the users and community to explore the positive side of the internet and content creators to share their ideas without undermining the benefits of online interactions. Future Research: Future research will explore the uniqueness of the linguistics and slang of these three languages. Apart from these languages, future research will be conducted on North-Indian Indian languages like Bengali, Marathi, and Gujarati. http://www.informingscience.org/Publications/5403 BERT NLP F1-Score Dravidian languages Code-mix Hate comment Muril mBERT eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-12-16 18 .i v 5058 article Table of Contents for Volume 18, 2023, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/5058 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-01-16 18 001 029 5067 article Clarita I Nainggolan clarita.nainggolan@gmail.com Putu Wuri Handayani putu.wuri@cs.ui.ac.id Aim/Purpose: This study aims to examine the ten factors from the Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), and Unified Theory of Acceptance and Use of Technology (UTAUT) theories in order to analyze behavioral intentions to use the Indonesian online capital market investment platforms and the effect of behavioral intentions on actual usage. Background: The potential growth of capital market investors in Indonesia is large, and the low use of the Internet for investment purposes makes it necessary for stakeholders to understand the factors that affect people’s intentions to invest, especially through online platforms. Several previous studies have explained the intention to use online investment platforms using the TAM and TPB theories. This study tries to combine TAM, TPB, and UTAUT theories in analyzing behavioral intentions to use an online capital market investment platform in Indonesia. Methodology: The research approach employed is a mixed method, particularly explanatory research, which employs quantitative methods first, followed by qualitative methods. Data were collected by conducting interviews and sending online surveys. This study was successful in collecting information on the users of online capital market investment platforms in Indonesia from 1074 respondents, which was then processed and analyzed using Covariance-Based Structural Equation Modeling (CB-SEM) with the IBM AMOS 26.0 application. Contribution: This study complements earlier theories like TAM, TPB, and UTAUT by looking at the intention to use online capital market investment platforms from technological, human, and environmental viewpoints. This study looks at the intention to use the online capital market investing platform as a whole rather than separately depending on investment instruments. This study also assists practitioners including regulators, the government, developers, and investors by offering knowledge of the phenomena and factors that can increase the capital market’s investment intention in Indonesia. Findings: Attitudes, perceived ease of use, perceived behavioral control, subjective norm, and national pride were found to be significant predictors of the intention to use online investment platforms in Indonesia, whereas perceived usefulness, perceived risk, perceived trust, perceived privacy, and price value were not. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. The government can enact legislation that emphasizes the simplicity and convenience of investment, as well as launch campaigns that encourage people to participate in economic recovery by investing in the capital market. Meanwhile, the developers are concentrating on facilitating the flow of investment transactions through the platform, increasing education and awareness of the benefits of investing in the capital market, and providing content that raises awareness that investing in the capital market can help to restore the national economy. Recommendation for Researchers: Further research is intended to include other variables such as perceived benefits and perceived security, as well as other frameworks such as TRA, to better explain individuals’ behavioral intentions to use online capital investment platforms. Impact on Society: This study can help all stakeholders understand what factors can increase Indonesians’ interest in investing in the capital market, particularly through online investment platforms. This understanding is expected to increase the number of capital market participants and, as a result, have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use an online capital market investment platform, such as perceived benefits and perceived security, as well as the addition of control variables such as age, gender, education, and income. International research across nations is also required to build a larger sample size in order to examine the behavior of investors in developing and developed countries and acquire a more thorough understanding of the online capital market investment platform. http://www.informingscience.org/Publications/5067 behavioral intention to use actual usage financial technology online investment platform capital market eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-01-16 18 031 058 5071 article Ahmad Samed Al-Adwan a.adwan@ammanu.edu.jo Ali Ahmad Trawnih a.tarawneh@ammanu.edu.jo Anas Amayreh anas_amayreh@ammanu.edu.jo Tha’er Majali T_almajali@asu.edu.jo Hamood Mohammed Al-Hattami hattamihamood@gmail.com Aim/Purpose: Social commerce is an emergent topic widely used for product and service sourcing. It helps companies to have frequent interaction with their customers and strive to achieve a competitive advantage. Yet there is only little empirical evidence focusing on social commerce and its adoption in SMEs to date. This study investigates the key factors affecting social commerce adoption in SMEs. This research designed a theoretical model using the Technology, Organization, and Environment (TOE) Model Background: Despite its rapid growth and usage, social commerce is still in its evolution phase and its current conception is vague and restricted. Therefore, considering the benefits of social commerce for consumers and businesses, it is important to explore the concept of social commerce. Methodology: The research floated a self-administered questionnaire and surveyed 218 Jordanian SME businesses. The data was analyzed using smart PLS and the results were drawn that covers the detail of the characteristics of respondents, study descriptive, results of regressions assumptions, e.g., data normality, reliability, validity, common method biases, and description of the measurement model, followed by the findings of hypothesis analysis. Contribution: This study has many significant contributions to the existing studies on firms’ adoption of social commerce. It indicates that organizational readiness from the organizational perspective and consumer pressure from the environmental dimension of the TOE model are significant influential elements in the adoption of social commerce in business, followed by high-level management support and trading partner pressure, respectively. This shows that organizational readiness to adopt social commerce and consumer pressure has a vital role in Jordanian SMEs’ adopting social commerce. Findings: The results were drawn from a survey of 218 Jordanian SMEs, indicating that organizational readiness from an organizational dimension and consumer pressure environmental perspective, followed by top management’s support and trading partner pressure, significantly predicts the adoption intentions of social commerce. However, perceived usefulness and security concerns from a technological context do not significantly impact behavioral intentions to utilize social commerce. Recommendations for Practitioners: Lack of awareness about new technology and its potential benefits are not well diffused in the Jordanian context. In short, both organizational and environmental dimensions of the TOE framework significantly influence the behavioral intentions for social commerce adoption in the Jordanian context whereas the third-dimension technological factors do not affect the behavioral intentions of SMEs to adopt social commerce. In the technological context, SMEs need to invest in technology and must spread awareness among Jordanian consumers about the potential benefits of technology and must encourage them to use social commerce platforms to interact because of the high significance of social commerce for businesses as it facilitates the quick completion of tasks, enhances the productivity, and improves the chances of high profitability. Recommendation for Researchers: First, the study is limited in scope as it discusses the direct links between the TOE framework, behavioral intentions to use social commerce, and the actual usage of social commerce in the Jordanian context rather than testing the mediation, and moderation. Future research may examine the mediators and moderators in the conceptual model. Second, the research examined the behavioral intentions of SMEs rather than consumers to adopt social commerce. Further research might consider the consumer perspective on social commerce. Impact on Society: This research aims to identify the key factor that impact the behavioral intentions of SME businesses to practice social commerce. The theoretical underpinning of the study lies in the TOE model, as using its basic assumptions the conceptual grounds and hypothesis of the study are developed. Future Research: The study findings are not generalizable in different contexts as it was specifically conducted by gathering data from the Jordanian population. However future studies may consider different contexts, sectors, cultures, or countries to examine the model. Lastly, the research collected data using convenience sampling from 218 SMEs in Jordan, which may create difficulty in the generalizability of the research, so needs to examine a larger sample in future studies. http://www.informingscience.org/Publications/5071 perceived usefulness; security concerns; organizational readiness; consumer pressure; top management support; trading partner pressure; social commerce eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-01-28 18 059 086 5072 article Muaadh Mukred muaadh@ukm.edu.my Umi Asma’ Mokhtar umimokhtar@ukm.edu.my Burkan Hawash burkan.hawash@yahoo.com Mohammed Islam Nofal Muhmmad.nofal@uop.edu.jo Aim/Purpose: The use of digital technology, such as an electronic records management system (ERMS), has prompted widespread changes across organizations. The organization needs to support its operations with an automation system to improve production performance. This study investigates ERMS’s potentiality to enhance organizational performance in the oil and gas industry. Background: Oil and gas organizations generate enormous electronic records that lead to difficulties in managing them without any system or digitalization procedure. The need to use a system to manage big data and records affects information security and creates several problems. This study supports decision-makers in oil and gas organizations to use ERMS to enhance organizational performance. Methodology: We used a quantitative method by integrating the typical partial least squares (SEM-PLS) approach, including measurement items, respondents’ demographics, sampling and collection of data, and data analysis. The SEM-PLS approach uses a measurement and structural model assessment to analyze data. Contribution: This study contributes significantly to theory and practice by providing advancements in identity theory in the context of big data management and electronic records management. This study is a foundation for further research on the role of ERMS in operations performance and Big Data Management (BDM). This research makes a theoretical contribution by studying a theory-driven framework that may serve as an essential lens to evaluate the role of ERMS in performance and increase its potentiality in the future. This research also evaluated the combined impacts of general technology acceptance theory elements and identity theory in the context of ERMS to support data management. Findings: This study provides an empirically tested model that helps organizations to adopt ERMS based on the influence of big data management. The current study’s findings looked at the concerns of oil and gas organizations about integrating new technologies to support organizational performance. The results demonstrated that individual characteristics of users in oil and gas organizations, in conjunction with administrative features, are robust predictors of ERMS. The results show that ERMS potentiality significantly influences the organizational performance of oil and gas organizations. The research results fit the big ideas about how big data management and ERMS affect respondents to adopt new technologies. Recommendations for Practitioners: This study contributes significantly to the theory and practice of ERMS potentiality and BDM by developing and validating a new framework for adopting ERMS to support the performance and production of oil and gas organizations. The current study adds a new framework to identity theory in the context of ERMS and BDM. It increases the perceived benefits of using ERMS in protecting the credibility and authenticity of electronic records in oil and gas organizations. Recommendation for Researchers: This study serves as a foundation for future research into the function and influence of big data management on ERMS that support the organizational performance. Researchers can examine the framework of this study in other nations in the future, and they will be able to analyze this research framework to compare various results in other countries and expand ERMS generalizability and efficacy. Impact on Society: ERMS and its impact on BDM is still a developing field, and readers of this article can assist in gaining a better understanding of the literature’s dissemination of ERMS adoption in the oil and gas industry. This study presents an experimentally validated model of ERMS adoption with the effect of BDM in the oil and gas industry. Future Research: In the future, researchers may be able to examine the impact of BDM and user technology fit as critical factors in adopting ERMS by using different theories or locations. Furthermore, researchers may include the moderating impact of demographical parameters such as age, gender, wealth, and experience into this study model to make it even more robust and comprehensive. In addition, future research may examine the significant direct correlations between human traits, organizational features, and individual perceptions of BDM that are directly related to ERMS potentiality and operational performance in the future. http://www.informingscience.org/Publications/5072 big data big data management ERMS potentiality oil and gas digital transformation electronic records eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-02-28 18 087 105 5086 article Van-Ho Nguyen honv@uel.edu.vn Hoang Dang Tran hoangtd21411c@st.uel.edu.vn Ngoc Le ngocltl21413c@st.uel.edu.vn Aim/Purpose: Previous research has generally concentrated on identifying the variables that most significantly influence customer churn or has used customer segmentation to identify a subset of potential consumers, excluding its effects on forecast accuracy. Consequently, there are two primary research goals in this work. The initial goal was to examine the impact of customer segmentation on the accuracy of customer churn prediction in the banking sector using machine learning models. The second objective is to experiment, contrast, and assess which machine learning approaches are most effective in predicting customer churn. Background: This paper reviews the theoretical basis of customer churn, and customer segmentation, and suggests using supervised machine-learning techniques for customer attrition prediction. Methodology: In this study, we use different machine learning models such as k-means clustering to segment customers, k-nearest neighbors, logistic regression, decision tree, random forest, and support vector machine to apply to the dataset to predict customer churn. Contribution: The results demonstrate that the dataset performs well with the random forest model, with an accuracy of about 97%, and that, following customer segmentation, the mean accuracy of each model performed well, with logistic regression having the lowest accuracy (87.27%) and random forest having the best (97.25%). Findings: Customer segmentation does not have much impact on the precision of predictions. It is dependent on the dataset and the models we choose. Recommendations for Practitioners: The practitioners can apply the proposed solutions to build a predictive system or apply them in other fields such as education, tourism, marketing, and human resources. Recommendation for Researchers: The research paradigm is also applicable in other areas such as artificial intelligence, machine learning, and churn prediction. Impact on Society: Customer churn will cause the value flowing from customers to enterprises to decrease. If customer churn continues to occur, the enterprise will gradually lose its competitive advantage. Future Research: Build a real-time or near real-time application to provide close information to make good decisions. Furthermore, handle the imbalanced data using new techniques. http://www.informingscience.org/Publications/5086 churn prediction machine learning banking industry classification models SMOTE eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-03-16 18 107 125 5091 article Gangaram Biswakarma drgrbiswa@gmail.com Poojan Bhandari poojan.bhandari.pb@gmail.com Aim/Purpose: Using the Agile Adoption Framework (AAF), this study aims to examine the agile potential of software development companies in Nepal based on their agile maturity level. In addition, this study also examines the impact of various basic agile practices in determining the maturity level of the agile processes being implemented in the software industry of Nepal. Background: Even if most organizations in the software sector utilize agile development strategies, it is essential to evaluate their performance. Nepal’s software industry did not adopt agile techniques till 2014. The Nepalese industry must always adapt to new developments and discover ways to make software development more efficient and beneficial. The population of the study consists of 1,500 and 2,000 employees of software companies in Nepal implementing agile techniques. Methodology: The sample size considered was 150 employees working in software companies in Nepal. However, only 106 respondents responded after three follow-ups. The sample was collected with purposive sampling. A questionnaire was developed to gain information on Customer Adaptive, Customer Collaboration, Continuous Delivery, Human Centric, and Technical Excellence related to agile practices along with the Agile Maturity Level. Contribution: This research contributes to the understanding of agile practices adopted in software companies in developing countries like Nepal. It also reveals the determinants of the agility of software companies in developing countries. Findings: The results suggest that some of the basic principles of agile have a very significant role in Agile Maturity Level in the Nepali context. In the context of Nepal, human-centered practices have a very high level of correlation, which plays a vital role as a major predictor of the agile maturity level. In addition, Technical Excellence is the variable that has the highest level of association with the Agile Maturity Level, making it the most significant predictor of this quality. Recommendations for Practitioners: As Nepali software companies are mostly offshore or serve outsourcing companies, there is a very thin probability of Nepali developers being able to interact with actual clients and this might be one of the reasons for the Nepali industry not relying on Customer Adaptation and Collaboration as major factors of the Agile methodologies. Continuous Delivery, on the other hand, has a significant degree of correlation with Agile Maturity Level. Human-centric practices have a very high level of correlation as well as being a major predictor in determining the Agile Maturity Level in the context of Nepal. Technical Excellence is the most significant predictor and the variable which has the highest level of correlation with Agile Maturity Level. Practitioners should mainly focus on technical excellence as well as human-centric practices to achieve a higher level of Agile Maturity. Recommendation for Researchers: There has not been any such research in the Nepali context that anyone could rely on, to deep dive into their organizational concerns regarding agile strategies and plans. Researchers will need to focus on a more statistical approach with data-driven solutions to the issues related to people and processes. Researchers will need to cover freelancers as well as academics to get a different perspective on what can be the better practices to achieve a higher level of agile maturity. Impact on Society: This study on Agile work is accessible not only to the software industry but also to the general public. The Agile technique has had a huge impact on society’s project management. It has revolutionized how teams approach project planning, development, and execution. The paper’s findings will further information regarding the Agile methodology, which emphasizes collaboration and communication, fosters teamwork and higher quality work, and promotes the exchange of knowledge, ideas, and the pursuit of common goals. Future Research: Owing to the limitations of this study, it is necessary to analyze agile practices in the Nepalese software sector using additional factors that influence agile maturity. The conclusion that years of agile experience do not serve as a balancing factor for both agile practices and the Agile Maturity Level requires additional research. Whether a software outsourcing firm or not, the organization type had no bearing on the degree of maturity of agile methods; this leaves space for further research. http://www.informingscience.org/Publications/5091 agile practice agile maturity software companies agile adoption framework eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-04-05 18 127 147 5098 article Ari V Alamäki ari.alamaki@haaga-helia.fi Marko Mäki marko.maki@haaga-helia.fi Janne Kauttonen janne.kauttonen@haaga-helia.fi Aim/Purpose: This study aimed to increase our understanding of how the stages of the customer purchase journey, privacy trade-offs, and information sensitivity of different business service sectors affect consumers’ privacy concerns. Background: The study investigated young consumers’ willingness to provide consent to use their personal data at different phases of the customer journey. This study also examined their readiness to provide consent if they receive personal benefits, and how information sensitivity varied between different individuals and business sectors. Methodology: Data was collected by a quantitative survey (n=309) and analyzed with R using the Bayesian linear mixed effect modeling approach. The sample consisted of university students in Finland, who represented a group of young and digitally native consumers. The questionnaire was designed for this study and included constructs with primarily Likert-scale items. Contribution: The study contributed to data privacy and consent management research in information sensitivity, privacy trade-off, and the customer journey. The study underlined the need for a stronger user experience focus and contextuality. Findings: The results showed that readiness to disclose personal data varied at different phases of the customer journey as privacy concerns did not decrease in a linear fashion throughout the purchase process. Perceived benefits affected the willingness to provide consent for data usage, but concerned consumers would be less trade-off oriented. Self-benefit was the most relevant reason for sharing, while customization was the least. There is a connection between the information sensitivity of different business sector information and privacy concerns. No support for gender differences was found, but age affected benefits and business sector variables. Recommendations for Practitioners: The study recommends approaching consumers’ data privacy concerns from a customer journey perspective while trying to motivate consumers to share their personal data with relevant perceived benefits. The self-benefit was the most relevant benefit for willingness to provide consent, while customization was the least. Recommendation for Researchers: The study shows that individual preference for privacy was a major factor directly and via interaction for all three models. This study also showed that consumers’ subjective decision-making in privacy issues is both a situational and a contextual factor. Impact on Society: This study could encourage policymakers and societies to develop guidelines on how to develop privacy practices and consent management to be more user centric as individuals are increasingly concerned about their online privacy. Future Research: This study encourages examining consumers’ motivational factors to provide digital consent for companies with experimental research settings. This study also calls to explore perceived benefits in all age groups from the perspective of different information in various business sectors. This study shows that privacy concern is a contextual and situational factor. http://www.informingscience.org/Publications/5098 data privacy information sensitivity privacy concern trade-offs customer journey eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-04-25 18 149 172 5099 article Atallah AL-Shatnawi atallah@aabu.edu.jo Jehad Imlawi imlawi@aabu.edu.jo Bader M AlFawwaz bm_alfawwaz@aabu.edu.jo Hasan M AL-Shatnawi hsnshatnawi@inu.edu.jo Sultan Al-masaeed s.masaeed@ammanu.edu.jo Aim/Purpose: The aim of this study is to develop and evaluate a comprehensive model that predicts students’ engagement with and intent to continue using mobile-Learning Management Systems (m-LMS). Background: m-LMS are increasingly popular tools for delivering course content in higher education. Understanding the factors that affect student engagement and continuance intention can help educational institutions to develop more effective and user-friendly m-LMS platforms. Methodology: Participants with prior experience with m-LMS were employed to develop and evaluate the proposed model that draws on the Technology Acceptance Model (TAM), Task-Technology Fit (TTF), and other related models. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the model. Contribution: The study provides a comprehensive model that takes into account a variety of factors affecting engagement and continuance intention and has a strong predictive capability. Findings: The results of the study provide evidence for the strong predictive capability of the proposed model and supports previous research. The model identifies perceived usefulness, perceived ease of use, interactivity, compatibility, enjoyment, and social influence as factors that significantly influence student engagement and continuance intention. Recommendations for Practitioners: The findings of this study can help educational institutions to effectively meet the needs of students for interactive, effective, and user-friendly m-LMS platforms. Recommendation for Researchers: This study highlights the importance of understanding the antecedents of students’ engagement with m-LMS. Future research should be conducted to test the proposed model in different contexts and with different populations to further validate its applicability. Impact on Society: The engagement model can help educational institutions to understand how to improve student engagement and continuance intention with m-LMS, ultimately leading to more effective and efficient mobile learning. Future Research: Additional research should be conducted to test the proposed model in different contexts and with different populations to further validate its applicability. http://www.informingscience.org/Publications/5099 engagement continuance intention m-LMS TAM TTF perceived usefulness perceived ease of use interactivity compatibility enjoyment social influence eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-01 18 173 202 5110 article Joshua Dwight joshua.dwight@rmit.edu.vn Aim/Purpose: This research study aimed to explore ecommerce fraud practitioners’ experiences and develop a grounded theory framework to help define an ecommerce fraud incident response process, roles and responsibilities, systems, stakeholders, and types of incidents. Background: With a surge in global ecommerce, online transactions have become increasingly fraudulent, complex, and borderless. There are undefined ecommerce fraud roles, responsibilities, processes, and systems that limit and hinder cyber incident response to fraudulent activities. Methodology: A constructivist grounded theory approach was used to investigate and develop a theoretical foundation of ecommerce fraud incident response based on fraud practitioners’ experiences and job descriptions. The study sample consisted of 8 interviews with ecommerce fraud experts. Contribution: This research contributes to the body of knowledge by helping define a novel framework that outlines an ecommerce fraud incident response process, roles and responsibilities, systems, stakeholders, and incident types. Findings: An ecommerce fraud incident response framework was developed from fraud experts’ perspectives. The framework helps define processes, roles, responsibilities, systems, incidents, and stakeholders. The first finding defined the ecommerce fraud incident response process. The process includes planning, identification, analysis, response, and improvement. The second finding was that the fraud incident response model did not include the containment phase. The next finding was that common roles and responsibilities included fraud prevention analysis, tool development, reporting, leadership, and collaboration. The fourth finding described practitioners utilizing hybrid tools and systems for fraud prevention and detection. The fifth finding was the identification of internal and external stakeholders for communication, collaboration, and information sharing. The sixth finding is that research participants experienced different organizational alignments. The seventh key finding was stakeholders do not have a holistic view of the data and information to make some connections about fraudulent behavior. The last finding was participants experienced complex fraud incidents. Recommendations for Practitioners: It is recommended to adopt the ecommerce fraud response framework to help ecommerce fraud and security professionals develop an awareness of cyber fraud activities and/or help mitigate cyber fraud activities. Future Research: Future research could entail conducting a quantitative analysis by surveying the industry on the different components such as processes, systems, and responsibilities of the ecommerce fraud incident response framework. Other areas to explore and evaluate are maturity models and organizational alignment, collaboration, information sharing, and stakeholders. Lastly, further research can be pursued on the nuances of ecommerce fraud incidents using frameworks such as attack graph generation, crime scripts, and attack trees to develop ecommerce fraud response playbooks, plans, and metrics. http://www.informingscience.org/Publications/5110 cyber incident response ecommerce fraud fraud prevention grounded theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-06 18 203 224 5109 article Khoa Dinh Vu khoa.haui@gmail.com Dat Tho Tran tranthodat@neu.edu.vn Phong Ba Le lebaphong.vn@gmail.com Phuong Thi Lan Tran Phuongttl@neu.edu.vn Aim/Purpose: Given the increasingly important role of knowledge and human resources for firms in developing and emerging countries to pursue innovation, this paper aims to study and explore the potential intermediating roles of knowledge donation and collection in linking high-involvement human resource management (HRM) practice and innovation capability. The paper also explores possible moderators of market turbulence in fostering the influences of knowledge-sharing (KS) behaviors on innovation competence in terms of incremental and radical innovation. Background: The fitness of HRM practice is critical for organizations to foster knowledge capital and internal resources for improving innovation and sustaining competitive advantage. Methodology: The study sample is 309 respondents and Structural Equation Model (SEM) was used for the analysis of the data obtained through a questionnaire survey with the aid of AMOS version 22. Contribution: This paper increases the understanding of the precursor role of high-involvement HRM practices, intermediating mechanism of KS activities, and the regulating influence of market turbulence in predicting and fostering innovation capability, thereby pushing forward the theory of HRM and innovation management. Findings: The empirical findings support the proposed hypotheses relating to the intermediating role of KS in the HRM practices-innovation relationship. It spotlights the crucial character of market turbulence in driving the domination of knowledge-sharing behaviors on incremental innovation. Recommendations for Practitioners: The proposed research model can be applied by leaders and directors to foster their organizational innovation competence. Recommendation for Researchers: Researchers are recommended to explore the influence of different models of HRM practices on innovation to identify the most effective pathway leading to innovation for firms in developing and emerging nations. Impact on Society: This paper provides valuable initiatives for firms in developing and emerging markets on how to leverage the strategic and internal resources of an organization for enhancing innovation. Future Research: Future studies should investigate the influence of HRM practices and knowledge resources to promote frugal innovation models for dealing with resource scarcity. http://www.informingscience.org/Publications/5109 high-involvement HRM knowledge sharing knowledge donating knowledge collecting radical innovation incremental innovation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-07 18 225 249 5107 article Van-Ho Nguyen honv@uel.edu.vn Thanh Ho thanhht@uel.edu.vn Thien Le thienlb.ktl@uel.edu.vn Hoanh-Su Le sulh@uel.edu.vn Dã Thôn Nguyen dant@uel.edu.vn Tu Mai tumtc@uel.edu.vn Anh Tran anhtt@uel.edu.vn Hoai-Phan Truong hoaiphan@uel.edu.vn Aim/Purpose: In this study, the research proposes and experiments with a new model of collecting, storing, and analyzing big data on customer feedback in the tourism industry. The research focused on the Vietnam market. Background: Big Data describes large databases that have been “silently” built by businesses, which include product information, customer information, customer feedback, etc. This information is valuable, and the volume increases rapidly over time, but businesses often pay little attention or store it discretely, not centrally, thereby wasting an extremely large resource and partly causing limitations for business analysis as well as data. Methodology: The study conducted an experiment by collecting customer feedback data in the field of tourism, especially tourism in Vietnam, from 2007 to 2022. After that, the research proceeded to store and mine latent topics based on the data collected using the Topic Model. The study applied cloud computing technology to build a collection and storage model to solve difficulties, including scalability, system stability, and system cost optimization, as well as ease of access to technology. Contribution: The research has four main contributions: (1) Building a model for Big Data collection, storage, and analysis; (2) Experimenting with the solution by collecting customer feedback data from huge platforms such as Booking.com, Agoda.com, and Phuot.vn based on cloud computing, focusing mainly on tourism Vietnam; (3) A Data Lake that stores customer feedback and discussion in the field of tourism was built, supporting researchers in the field of natural language processing; (4) Experimental research on the latent topic mining model from the collected Big Data based on the topic model. Findings: Experimental results show that the Data Lake has helped users easily extract information, thereby supporting administrators in making quick and timely decisions. Next, PySpark big data processing technology and cloud computing help speed up processing, save costs, and make model building easier when moving to SaaS. Finally, the topic model helps identify customer discussion trends and identify latent topics that customers are interested in so business owners have a better picture of their potential customers and business. Recommendations for Practitioners: Empirical results show that facilities are the factor that customers in the Vietnamese market complain about the most in the tourism/hospitality sector. This information also recommends that practitioners reduce their expectations about facilities because the overall level of physical facilities in the Vietnamese market is still weak and cannot be compared with other countries in the world. However, this is also information to support administrators in planning to upgrade facilities in the long term. Recommendation for Researchers: The value of Data Lake has been proven by research. The study also formed a model for big data collection, storage, and analysis. Researchers can use the same model for other fields or use the model and algorithm proposed by this study to collect and store big data in other platforms and areas. Impact on Society: Collecting, storing, and analyzing big data in the tourism sector helps government strategists to identify tourism trends and communication crises. Based on that information, government managers will be able to make decisions and strategies to develop regional tourism, propose price levels, and support innovative programs. That is the great social value that this research brings. Future Research: With each different platform or website, the study had to build a query scenario and choose a different technology approach, which limits the ability of the solution’s scalability to multiple platforms. Research will continue to build and standardize query scenarios and processing technologies to make scalability to other platforms easier. http://www.informingscience.org/Publications/5107 data lake for big data data collection data storage customer feedback topic modeling tourism eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-08 18 251 267 5112 article Khaled Halteh k.halteh@ammanu.edu.jo Hakem Sharari h.sharari@ammanu.edu.jo Aim/Purpose: This paper aims to empirically quantify the financial distress caused by the COVID-19 pandemic on companies listed on Amman Stock Exchange (ASE). The paper also aims to identify the most important predictors of financial distress pre- and mid-pandemic. Background: The COVID-19 pandemic has had a huge toll, not only on human lives but also on many businesses. This provided the impetus to assess the impact of the pandemic on the financial status of Jordanian companies. Methodology: The initial sample comprised 165 companies, which was cleansed and reduced to 84 companies as per data availability. Financial data pertaining to the 84 companies were collected over a two-year period, 2019 and 2020, to empirically quantify the impact of the pandemic on companies in the dataset. Two approaches were employed. The first approach involved using Multiple Discriminant Analysis (MDA) based on Altman’s (1968) model to obtain the Z-score of each company over the investigation period. The second approach involved developing models using Artificial Neural Networks (ANNs) with 15 standard financial ratios to find out the most important variables in predicting financial distress and create an accurate Financial Distress Prediction (FDP) model. Contribution: This research contributes by providing a better understanding of how financial distress predictors perform during dynamic and risky times. The research confirmed that in spite of the negative impact of COVID-19 on the financial health of companies, the main predictors of financial distress remained relatively steadfast. This indicates that standard financial distress predictors can be regarded as being impervious to extraneous financial and/or health calamities. Findings: Results using MDA indicated that more than 63% of companies in the dataset have a lower Z-score in 2020 when compared to 2019. There was also an 8% increase in distressed companies in 2020, and around 6% of companies came to be no longer healthy. As for the models built using ANNs, results show that the most important variable in predicting financial distress is the Return on Capital. The predictive accuracy for the 2019 and 2020 models measured using the area under the Receiver Operating Characteristic (ROC) graph was 87.5% and 97.6%, respectively. Recommendations for Practitioners: Decision makers and top management are encouraged to focus on the identified highly liquid ratios to make thoughtful decisions and initiate preemptive actions to avoid organizational failure. Recommendation for Researchers: This research can be considered a stepping stone to investigating the impact of COVID-19 on the financial status of companies. Researchers are recommended to replicate the methods used in this research across various business sectors to understand the financial dynamics of companies during uncertain times. Impact on Society: Stakeholders in Jordanian-listed companies should concentrate on the list of most important predictors of financial distress as presented in this study. Future Research: Future research may focus on expanding the scope of this study by including other geographical locations to check for the generalisability of the results. Future research may also include post-COVID-19 data to check for changes in results. http://www.informingscience.org/Publications/5112 financial distress prediction COVID-19 ANN MDA Jordan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-11 18 269 300 5103 article Muhammad Mahboob Khurshid mehboob.khursheed@vu.edu.pk Yunis Ali Ahmed yunisali55@gmail.com Aim/Purpose: The primary purpose of this study is to investigate the factors that impact the behavioral intention to use social media (SM) for knowledge sharing (KS) in the disaster relief (DR) context. Background: With the continuing growth of SM for KS in the DR environment, disaster relief organizations across the globe have started to realize its importance in streamlining their processes in the post-implementation phase. However, SM-based KS depends on the willingness of members to share their knowledge with others, which is affected by several technological, social, and organizational factors. Methodology: A survey was conducted in Somalia to gather primary data from DR practitioners, using purposive sampling as the technique. The survey collected 214 valid responses, which were then analyzed with the PLS-SEM approach. Contribution: The study contributes to an understanding of the real-life hurdles faced by disaster relief organizations by expanding on the C-TAM-TPB model with the inclusion of top management support, organizational rewards, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust factors. Additionally, it provides useful recommendations to managers of disaster relief organizations on the key factors to consider. Findings: The findings recorded that perceived usefulness, ease of use, top management support, enjoyment in helping others, knowledge self-efficacy, and interpersonal trust were critical factors in determining behavioral intention (BI) to use SM-based KS in the DR context. Furthermore, the mediator variables were attitude, subjective norms, and perceived behavioral control. Recommendations for Practitioners: Based on the research findings, it was determined that management should create different discussion forums among the disaster relief teams to ensure the long-term use of SM-based KS within DR organizations. They should also become involved in the discussions for disaster-related knowledge such as food supplies, shelter, or medical relief that disaster victims need. Disaster relief managers should consider effective and adequate training to enhance individual knowledge and self-efficacy since a lack of training may increase barriers and difficulties in using SM for KS during a DR process. Recommendation for Researchers: The conceptual model, further empirically investigated, can be employed by other developing countries in fostering acceptance of SM for KS during disaster relief operations. Impact on Society: Disaster relief operations can be facilitated using social media by considering the challenges DR practitioners face during emergencies. Future Research: In generalizing this study’s findings, other national or global disaster relief organizations should consider, when applying and testing, the research instruments and proposed model. The researchers may extend this study by collecting data from managers or administrators since they are different types of users of the SM-based KS system. http://www.informingscience.org/Publications/5103 social media knowledge sharing determinants behavioral intention to use disaster relief developing country eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-11 18 301 319 5111 article Caiyun Zhuang zhuangcaiyun19900@163.com Guohong Chen 54505663@qq.com Juan Liang 271604167@qq.com Yang Zou 627834653@qq.com Si Chen 85951735@qq.com Aim/Purpose: This study investigates the relationship between dual network embedding, dual entrepreneurial bricolage, and knowledge-creation performance. Background: The importance of new ventures for innovation and economic growth has been fully endorsed. Establishing incubation organizations to help new startups overcome constraints and dilemmas has become the consensus of various countries. In particular, the number of Chinese makerspaces has rapidly increased. Startups in the makerspaces form a loosely coupled dual network to cooperate and share resources, especially knowledge. Methodology: By convenience sampling, 400 startups in the makerspaces in Fujian Province, China were selected for the questionnaire survey study. In total, 307 valid responses were collected, yielding a response rate of 76.8%. The survey data were analyzed for hypothesis testing, using the PL-SEM technique with the AMOS20.0 software. Contribution: At the theoretical level, this research supplements the exploration of the influencing factors of the entrepreneurial bricolage of startups at the network level. It deepens the research on the internal mechanism of the dual network embeddedness affecting the knowledge-creation performance. In practice, it provides a theoretical basis and management inspiration for startups in makerspaces to overcome the inherent disadvantage of being too small and weak to explore innovative paths. Findings: First, relational embedding of startups in makerspaces directly affects knowledge-creation performance. Second, dual entrepreneurial bricolage plays a mediating role in diversity. Selective entrepreneurial bricolage plays a partial mediating role between relationship embedding and knowledge-creation performance. Parallel entrepreneurial bricolage plays a complete intermediary role between structural embedding and knowledge-creation performance. Dual entrepreneurial bricolage plays a complete intermediary role between knowledge embedding and knowledge-creation performance. Recommendations for Practitioners: Enterprises in the makerspaces should make dynamic adjustments to the network embedded state and dual entrepreneurial bricolage to improve knowledge-creation performance. When startups conduct selective entrepreneurship bricolage, they should strengthen relational and knowledge embeddedness to improve their relationship strength and tacit knowledge acquisition. When startups conduct parallel entrepreneurship bricolage, structural and knowledge embedding should be strengthened to improve the position of enterprises in the network to acquire diversified knowledge to explore and discover new business opportunities and project resources. Recommendation for Researchers: The heterogeneity of industries and regions may impact the dual network embedding mechanism of startups. Researchers can choose a wider range of regions and industries for sampling. Impact on Society: This study provides a theoretical basis and management inspiration for startups to overcome the inherent disadvantage of being too small and weak to explore innovative paths. It provides a basis to support startups in unleashing innovation vitality and achieving healthy growth. Future Research: Previous studies have shown that network relationships and bricolage behavior have a certain relationship with the enterprise life cycle. Future research can adopt a longitudinal research design across time points, which will increase the explanatory power of research conclusions. http://www.informingscience.org/Publications/5111 makerspace network embedding dual entrepreneurship bricolage startups knowledge-creation performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-05-21 18 321 352 5113 article Ammar Abdallah a.qasaimeh@psut.edu.jo Alain ABRAN alain.abran@etsmtl.ca Malik Qasaimeh mgqasaimeh@just.edu.jo Alaeddin Mohammad Khalaf Ahmad a.ahmed@psut.edu.jo Abdullah Al-Refai a.alrefai@psut.edu.jo Aim/Purpose: This study identifies the scale types and measurement units used in the measurement of enterprise architecture (EA) and analyzes the admissibility of the mathematical operations used. Background: The majority of measurement solutions proposed in the EA literature are based on researchers’ opinions and many with limited empirical validation and weak metrological properties. This means that the results generated by these solutions may not be reliable, trustworthy, or comparable, and may even lead to wrong investment decisions. While the literature proposes a number of EA measurement solutions, the designs of the mathematical operations used to measure EA have not yet been independently analyzed. It is imperative that the EA community works towards developing robust, reliable, and widely accepted measurement solutions. Only then can senior management make informed decisions about the allocation of resources for EA initiatives and ensure that their investment yields optimal results. Methodology: In previous research, we identified, through a systematic literature review, the EA measurement solutions proposed in the literature and classified them by EA entity types. In a subsequent study, we evaluated their metrology coverage from both a theoretical and empirical perspective. The metrology coverage was designed using a combination of the evaluation theory, best practices from the software measurement literature including the measurement context model, and representational theory of measurement to evaluate whether EA measurement solutions satisfy the metrology criteria. The research study reported here presents a more in-depth analysis of the mathematical operations within the proposed EA measurement solutions, and for each EA entity type, each mathematical operation used to measure EA was examined in terms of the scale types and measurement units of the inputs, their transformations through mathematical operations, the impact in terms of scale types, and measurement units of the proposed outputs. Contribution: This study adds to the body of knowledge on EA measurement by offering a metrology-based approach to analyze and design better EA measurement solutions that satisfy the validity of scale type transformations in mathematical operations and the use of explicit measurement units to allow measurement consistency for their usage in decision-making models. Findings: The findings from this study reveal that some important metrology and quantification issues have been overlooked in the design of EA measurement solutions proposed in the literature: a number of proposed EA mathematical operations produce numbers with unknown units and scale types, often the result of an aggregation of undetermined assumptions rather than explicit quantitative knowledge. The significance of such aggregation is uncertain, leading to numbers that have suffered information loss and lack clear meaning. It is also unclear if it is appropriate to add or multiply these numbers together. Such EA numbers are deemed to have low metrological quality and could potentially lead to incorrect decisions with serious and costly consequences. Recommendations for Practitioners: The results of the study provide valuable insights for professionals in the field of EA. Identifying the metrology limitations and weaknesses of existing EA measurement solutions may indicate, for instance, that practitioners should wait before using them until their design has been strengthened. In addition, practitioners can make informed choices and select solutions with a more robust metrology design. This, in turn, will benefit enterprise architects, software engineers, and other EA professionals in decision making, by enabling them to take into consideration factors more adequately such as cost, quality, risk, and value when assessing EA features. The study’s findings thus contribute to the development of more reliable and effective EA measurement solutions. Recommendation for Researchers: Researchers can use with greater confidence the EA measurement solutions with admissible mathematical operations and measurement units to develop new decision-making models. Other researchers can carry on research to address the weaknesses identified in this study and propose improved ones. Impact on Society: Developers, architects, and managers may be making inappropriate decisions based on seriously flawed EA measurement solutions proposed in the literature and providing undue confidence and a waste of resources when based on bad measurement design. Better quantitative tools will ultimately lead to better decision making in the EA domain, as in domains with a long history of rigor in the design of the measurement tools. Such advancements will benefit enterprise architects, software engineers, and other practitioners, by providing them with more meaningful measurements for informed decision making. Future Research: While the analysis described in this study has been explicitly applied to evaluating EA measurement solutions, researchers and practitioners in other domains can also examine measurement solutions proposed in their respective domains and design new ones. http://www.informingscience.org/Publications/5113 Enterprise Architecture (EA) metrology software metrics scale types admissible mathematical operations eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-06-27 18 353 368 5164 article Dan Bouhnik bouhnik@jct.ac.il Maayan Nakash Maayan.Nakash@biu.ac.il Aim/Purpose. COVID-19 was an unprecedented disruptive event that accelerated the shift to remote work and encouraged widespread adoption of digital tools in organizations. This empirical study was conducted from an organizational-strategic perspective, with the aim of examining how the COVID-19 pandemic outbreak affected employees’ use of organizational information systems (IS) as reflected in frequency. Background. To date, only a limited effort has been made, and a rather narrow perspective has been adopted, regarding the consequences of the adoption of new work environments following COVID-19. It seems that the literature is lacking in information regarding employee use of organizational IS since the outbreak of the pandemic. Specifically, this issue has not yet been examined in relation to employees’ perception about the organization’s digital efforts and technological maturity for remote work. The present study bridges this gap. Methodology. The public sector in Israel, which employs about a third of the Israeli work-force, was chosen as a case study of information-intensive organizations. During the first year of COVID-19, 716 questionnaires were completed by employees and managers belonging to four government ministries operating in Israel. The responses were statistically analyzed using a Chi-Square and Spearman’s Rho tests. Contribution. Given that the global pandemic is an ongoing phenomenon and not a passing episode, the findings provide important theoretical and practical contributions. The period prior to the COVID-19 pandemic and the period of the pandemic are compared with regard to organizational IS use. Specifically, the study sheds new light on the fact that employee perceptions motivated increased IS use during an emergency. The results contribute to the developing body of empirical knowledge in the IS field in the era of digital transformation (DT). Findings. More than half of the respondents who reported that they did not use IS before COVID-19 stated that the pandemic did not change this. We also found a significant positive correlation between the perception of the digital efforts made by organizations to enable connection to the IS for remote work and a change in frequency of IS use. This frequency was also found to have a significant positive correlation with the perception of the organization’s technological maturity to enable effective and continuous remote work. Recommendations for Practitioners. In an era of accelerating DT, this paper provides insights that may support chief information officers and chief digital officers in understanding how to promote the use of IS. The results can be useful for raising awareness of the importance of communicating managerial messages for employees regarding the organizational strategy and the resilience achieved through IS not only in routine, but also in particular in emergency situations. Recommendations for Researchers. Considering that the continual crisis has created challenges in IS research, it is appropriate to continue researching the adaptation and acclimation of organizations to the “new normal”. Impact on Society. The COVID-19 pandemic created a sudden change in employment models, which have become more flexible than ever. The research insights enrich the knowledge about the concrete consequences of this critical change. Future Research. We suggest that researchers investigate this core issue in other sectors and/or other countries, in order to be obtain new and complementary empirical insights on a comparative basis. http://www.informingscience.org/Publications/5164 COVID-19 new normal information systems information technology remote work digital transformation workplace environment eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-07-09 18 369 385 5160 article Pivithuru J Kumarasinghe pivithuru@sjp.ac.lk Qiubo Huang qiubo_huang@zjsru.edu.cn Nilmini Rathnayake nilmini.r@sliit.lk Aim/Purpose: Most people use their phones for work and communication. Businesses today require sustainable mobile phones to limit the environmental impact of mobile phones. According to the Environmental Protection Agency (EPA), a green product uses less energy. Green smartphones need low radiation emission, are made from recyclable materials, and are designed to last longer than typical smartphones. Further, the manufacturing process needs to have a low environmental impact. The present study aims to identify the influence of variables (such as Green Awareness, Environmental Concern, Altruism, and Willingness to Pay) on green smartphone purchase intention among academics in the Sri Lankan higher education sector. Background: With the swift technological advances, almost everyone has begun to use smartphones. Simultaneously, smartphone manufacturers have begun to release cutting-edge smartphone models to the general public. As a result, it has generated a significant amount of e-waste for the environment. As a result, therefore, the sustainability of green smartphones has become a major societal concern in the developed world, but this is not yet true in the developing world Methodology: The study used a qualitative research method in which the authors attempted to acquire primary data by conducting in-depth interviews with academics from the Sri Lankan higher education sector using a semi-structured interview guide. Eight interviews were conducted, audio recorded, and word-to-word transcribed for content analysis. Researchers used content analysis to determine the presence, meanings, and linkages of specific words, themes, or concepts. Contribution: The findings provide important environmental insights for smartphone makers and society, such as introducing waste reduction programs and energy-saving practices and creating awareness among people to change their consumption patterns. The study will provide valuable insights into the green smartphone phone purchasing intentions of academics in a developing country, especially helping green smartphone producers and marketers construct effective tactics with the insight of the current study based on university faculty members’ viewpoints. Findings: The current study’s findings revealed that academics acknowledge the need for environmental protection with an awareness of the green concept and environmental concerns. According to the interviews, most participants intended to move from their present smartphone to an ecologically friendly phone, as they explained on altruism. This implies that even academics in underdeveloped countries are worried about environmental issues and have shown a more robust understanding of these issues and how environmentally aware individuals’ activities may assist the earth’s sustainability. Further, academics have a willingness to pay for a green smartphone. Recommendations for Practitioners: Academics prioritize environmental conservation when making purchases. This implies that manufacturers and enterprises should focus on developing and in- novating more environmentally friendly products. Recommendation for Researchers: Using only academics as a sample approach is severely limited if the study’s population comprises people with various qualities. Nevertheless, this study presented only four independent variables, and more factors impacting green smartphone purchasing intention may exist. As a result, it is proposed that future research consider other factors. Impact on Society: It was discovered that most participants displayed altruism in their product purchases, implying that policymakers must strengthen the moral practice of concern for the welfare and happiness of other humans, even in developing countries. Future Research: A further in-depth study focusing on many perspectives such as limits and motivations for purchasing green products in various socioeconomic groups with varying moderating factors such as gender, education, rural-urban, and so on would be advantageous. Individual (emotions, habits, perceived behavioral control, trust, values, personal norm, knowledge) and situational (availability, product attributes, subjective norm, brand, eco-labeling) variables should be included in future research. http://www.informingscience.org/Publications/5160 green awareness environmental concern altruism green smartphones purchase intention eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-07-09 18 387 405 5165 article Chih-Hung Chen Chih_hung.che@nida.ac.th Aim/Purpose: The major challenges for firms to initiate corporate social responsibility (CSR) arise from resource constraints, complexity, and uncertainty. Consuming considerable financial and human resources is the main difficulty for smaller firms or those operating in less profitable industries, and the lack of immediate outputs from CSR initiatives poses a challenge for firms in prioritizing and assessing their effectiveness. Background: To better integrate CSR management into overall business strategy and decision-making processes, Blockchain technology (BCT) could potentially offer a feasible and optimal alternative to CSR reports. Methodology: This study uses the fixed effects regression by way of the Least Squares Dummy Variable (LSDV) approach in STATA to analyze the direct effect of CSR management on business performance and the moderating effect of BCT adoption on this relationship with a panel data set of 5810 observations collected from the 874 listed companies in 2015 in Taiwan Stock Exchange through 2021. Contribution: This study contributes to the literature by shedding light on the organizational factors that influence BCT adoption. Findings: The findings show that firms with high levels of CSR management have better business performance. Additionally, the adoption of BCT strengthens the positive relationship between CSR management and business performance, but it cannot replace the fundamental principles of CSR. Finally, firm size does not significantly affect BCT adoption, indicating that companies of all sizes have an equal opportunity to adopt BCT, which can help to level the playing field in terms of resources available to different firms. Recommendations for Practitioners: This study suggests that firms managing CSR practices have better business performance, and the adoption of BCTs further enhances this positive relationship. However, BCT adoption does not have the same positive effect on business performance as CSR practices. Additionally, this research can help to inform public policy related to BCT adoption and diffusion. Recommendation for Researchers: By exploring the factors that influence BCT adoption, future researchers can provide insights into the key challenges and opportunities faced by organizations of different sizes and help to develop strategies for promoting the effective adoption of BCT. Impact on Society: Given the limitations of current CSR reporting, the understanding gained from BCT applications can provide companies with an alternative mechanism to foster progress in CSR implementation. Future Research: Firstly, while the fixed-effects model might have dampened the power of explanation because it only captures within-unit variation and ignores between-unit variation, the explanatory power is further limited due to only integrating two independent variables in this model. Because of limited data availability, this study only utilizes CSR_Report and firm_size as independent variables. Future studies can consider more key factors and may lead to different results. Additionally, panel data is collected from Taiwan and, therefore, may not be representative of the broader population. Future researchers integrating the Stock Exchange of different countries are recommended. http://www.informingscience.org/Publications/5165 corporate social responsibility blockchain technology business performance fixed-effects model Taiwan Stock Exchange eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-07-20 18 407 434 5167 article Li Meiyi limeiyi492@gmail.com Ree Chan Ho reechan.ho@taylors.edu.my Muslim Amin tengkumuslim@yahoo.com Nelvin XeChung Leow nelvinxechung.leow@taylors.edu.my Aim/Purpose: Based on the stimulus-organism-response (SOR) model, the current study investigated social commerce functions as an innovative retailing technological support by selecting the three most appropriate features for the Chinese online shopping environment with respective value co-creation intentions. Background: Social commerce is the customers’ online shopping touchpoint in the latest retail era, which serves as a corporate technological tool to extend specific customer services. Although social commerce is a relatively novel platform, limited theoretical attention was provided to determine retailers’ approaches in employing relevant functions to improve consumer experience and value co-creation. Methodology: A questionnaire was distributed to Chinese customers, with 408 valid questionnaires being returned and analyzed through Structural Equation Modeling (SEM). Contribution: The current study investigated the new retail concept and value co-creation from the consumer’s perspective by developing a theoretical model encompassing new retail traits and consumer value, which contributed to an alternative theoretical understanding of value creation, marketing, and consumer behaviour in the new retail business model. Findings: The results demonstrated that value co-creation intention was determined by customer experience, hedonic experience, and trust. Simultaneously, the three factors were significantly influenced by interactivity, personalisation, and sociability features. Specifically, customers’ perceptions of the new retail idea and the consumer co-creation value were examined. Resultantly, this study constructed a model bridging new retail characteristics with consumer value. Recommendations for Practitioners: Nonetheless, past new retail management practice studies mainly focused on superficial happiness in the process of human-computer interaction, which engendered a computer system design solely satisfying consumers’ sensory stimulation and experience while neglecting consumers’ hidden value demands. As such, a shift from the subjective perspective to the realisation perspective is required to express and further understand the actual meaning and depth of consumer happiness. Recommendation for Researchers: New retailers could incorporate social characteristics on social commerce platforms to improve the effectiveness of marketing strategies while increasing user trust to generate higher profitability. Impact on Society: The new retail enterprises should prioritise consumers’ acquisition of happiness meaning and deep experience through self-realisation, cognitive improvement, identity identification, and other aspects of consumer experiences and purchase processes. By accurately revealing and matching consumers’ fundamental perspectives, new retailers could continuously satisfy consumer requirements in optimally obtaining happiness. Future Research: Future comparative studies could be conducted on diverse companies within the same industry for comprehensive findings. Moreover, other underlying factors with significant influences, such as social convenience, group cognitive ability, individual family environment, and other external stimuli were not included in the present study examinations. http://www.informingscience.org/Publications/5167 new retail social commerce features consumer value co-creation stimulus-organism-response (SOR) model eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-07-21 18 435 457 5172 article Qusai Shambour q.shambour@ammanu.edu.jo Mahran Al-Zyoud m.zyoud@ammanu.edu.jo Ahmad Abu-Shareha a.abushareha@ammanu.edu.jo Mosleh Abualhaj Moslehabualhaj@yahoo.com Aim/Purpose: This study aims to devise a personalized solution for online healthcare platforms that can alleviate problems arising from information overload and data sparsity by providing personalized healthcare services to patients. The primary focus of this paper is to develop an effective medicine recommendation approach for recommending suitable medications to patients based on their specific medical conditions. Background: With a growing number of people becoming more conscious about their health, there has been a notable increase in the use of online healthcare platforms and e-services as a means of diagnosis. As the internet continues to evolve, these platforms and e-services are expected to play an even more significant role in the future of healthcare. For instance, WebMD and similar platforms offer valuable tools and information to help manage patients’ health, such as searching for medicines based on their medical conditions. Nonetheless, patients often find it arduous and time-consuming to sort through all the available medications to find the ones that match their specific medical conditions. To address this problem, personalized recommender systems have emerged as a practical solution for mitigating the burden of information overload and data sparsity-related issues that are frequently encountered on online healthcare platforms. Methodology: The study utilized a dataset of MC ratings obtained from WebMD, a popular healthcare website. Patients on this website can rate medications based on three criteria, including medication effectiveness, ease of use, and satisfaction, using a scale of 1 to 5. The WebMD MC rating dataset used in this study contains a total of 32,054 ratings provided by 2,136 patients for 845 different medicines. The proposed HSMCCF approach consists of two primary modules: a semantic filtering module and a multi-criteria filtering module. The semantic filtering module is designed to address the issues of data sparsity and new item problems by utilizing a medicine taxonomy that sorts medicines according to medical conditions and makes use of semantic relationships between them. This module identifies the medicines that are most likely to be relevant to patients based on their current medical conditions. The multi-criteria filtering module, on the other hand, enhances the approach’s ability to capture the complexity of patient preferences by considering multiple criteria and preferences through a unique similarity metric that incorporates both distance and structural similarities. This module ensures that patients receive more accurate and personalized medication recommendations. Moreover, a medicine reputation score is employed to ensure that the approach remains effective even when dealing with limited ratings or new items. Overall, the combination of these modules makes the proposed approach more robust and effective in providing personalized medicine recommendations for patients. Contribution: This study addresses the medicine recommendation problem by proposing a novel approach called Hybrid Semantic-based Multi-Criteria Collaborative Filtering (HSMCCF). This approach effectively recommends medications for patients based on their medical conditions and is specifically designed to overcome issues related to data sparsity and new item recommendations that are commonly encountered on online healthcare platforms. The proposed approach addresses data sparsity and new item issues by incorporating a semantic filtering module and a multi-criteria filtering module. The semantic filtering module sorts medicines based on medical conditions and uses semantic relationships to identify relevant ones. The multi-criteria filtering module accurately captures patient preferences and provides precise recommendations using a novel similarity metric. Additionally, a medicine reputation score is also employed to further expand potential neighbors, improving predictive accuracy and coverage, particularly in sparse datasets or new items with few ratings. With the HSMCCF approach, patients can receive more personalized recommendations that are tailored to their unique medical needs and conditions. By leveraging a combination of semantic-based and multi-criteria filtering techniques, the proposed approach can effectively address the challenges associated with medicine recommendations on online healthcare platforms. Findings: The proposed HSMCCF approach demonstrated superior effectiveness compared to benchmark recommendation methods in multi-criteria rating datasets in terms of enhancing both prediction accuracy and coverage while effectively addressing data sparsity and new item challenges. Recommendations for Practitioners: By applying the proposed medicine recommendation approach, practitioners can develop a medicine recommendation system that can be integrated into online healthcare platforms. Patients can then utilize this system to make better-informed decisions regarding the medications that are most suitable for their specific medical conditions. This personalized approach to medication recommendations can ultimately lead to improved patient satisfaction. Recommendation for Researchers: Integrating patient medicine reviews is a promising way for researchers to elevate the proposed medicine recommendation approach. By leveraging patient reviews, the approach can gain a more comprehensive understanding of how certain medications perform for specific medical conditions. Additionally, exploring the relationship between MC-based ratings using an improved aggregation function can potentially enhance the accuracy of medication predictions. This involves analyzing the relationship between different criteria, such as medication effectiveness, ease of use, and satisfaction of the patients, and determining the optimal weighting for each criterion based on patient feedback. A more holistic approach that incorporates patient reviews and an improved aggregation function can enable the proposed medicine recommendation approach to provide more personalized and accurate recommendations to patients. Impact on Society: To mitigate the risk of infection during the COVID-19 pandemic, the promotion of online healthcare services was actively encouraged. This allowed patients to continue accessing care and receiving treatment while adhering to physical distancing guidelines and shielding measures where necessary. As a result, the implementation of personalized healthcare services for patients is expected to be a major disruptive force in healthcare in the coming years. This study proposes a personalized medicine recommendation approach that can effectively address this issue and aid patients in making informed decisions about the medications that are most suitable for their specific medical conditions. Future Research: One way that may enhance the proposed medicine recommendation approach is to incorporate patient medicine reviews. Furthermore, the analysis of MC-based ratings using an improved aggregation function can also potentially enhance the accuracy of medication predictions. http://www.informingscience.org/Publications/5172 medicine recommendation semantic filtering multi-criteria filtering sparsity new item eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-07-25 18 459 486 5166 article Mohammed Rashed Mohamed Al Humaid Alneyadi Mohammed.alneyadi@student.usm.my Md Kassim Normalini normalini_mk@yahoo.com Aim/Purpose: The UAE and other Middle Eastern countries suffer from various cybersecurity vulnerabilities that are widespread and go undetected. Still, many UAE government organizations rely on human-centric approaches to combat the growing cybersecurity threats. These approaches are ineffective due to the rapid increase in the amount of data in cyberspace, hence necessitating the employment of intelligent technologies such as AI cybersecurity systems. In this regard, this study investigates factors influencing users’ intention to adopt AI-based cybersecurity systems in the UAE. Background: Even though UAE is ranked among the top countries in embracing emerging technologies such as digital identity, robotic process automation (RPA), intelligent automation, and blockchain technologies, among others, it has experienced sluggish adoption of AI cybersecurity systems. This selectiveness in adopting technology begs the question of what factors could make the UAE embrace or accept new technologies, including AI-based cybersecurity systems. One of the probable reasons for the slow adoption and use of AI in cybersecurity systems in UAE organizations is the employee’s perception and attitudes towards such intelligent technologies. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 370 participants working in UAE government organizations considering or intending to adopt AI-based cybersecurity systems. The data was analyzed using the PLS-SEM approach. Contribution: The study is based on the Protection Motivation Theory (PMT) framework, widely used in information security research. However, it extends this model by including two more variables, job insecurity and resistance to change, to enhance its predictive/exploratory power. Thus, this research improves PMT and contributes to the body of knowledge on technology acceptance, especially in intelligent cybersecurity technology. Findings: This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. All the hypotheses were accepted. The relationship between the six constructs (perceived vulnerability (PV), perceived severity (PS), perceived response efficacy (PRE), perceived self-efficacy (PSE), job insecurity (JI), and resistance to change (RC)) and the intention to adopt AI cybersecurity systems in the UAE was found to be statistically significant. This paper’s findings provide the basis from which further studies can be conducted while at the same time offering critical insights into the measures that can boost the acceptability and use of cybersecurity systems in the UAE. Recommendations for Practitioners: All practitioners must be able to take steps and strategies that focus on factors that have a significant impact on increasing usage intentions. PSE and PRE were found to be positively related to the intention to adopt AI-based cybersecurity systems, suggesting the need for practitioners to focus on them. The government can enact legislation that emphasizes the simplicity and awareness of the benefits of cybersecurity systems in organizations. Recommendation for Researchers: Further research is needed to include other variables such as facilitating conditions, AI knowledge, social influence, and effort efficacy as well as other frameworks such as UTAUT, to better explain individuals’ behavioral intentions to use cybersecurity systems in the UAE. Impact on Society: This study can help all stakeholders understand what factors can increase users’ interest in investing in the applications that are embedded with security. As a result, they have an impact on economic recovery following the COVID-19 pandemic. Future Research: Future research is expected to investigate additional factors that can influence individuals’ behavioral intention to use cybersecurity systems such as facilitating conditions, AI knowledge, social influence, effort efficacy, as well other variables from UTAUT. International research across nations is also required to build a larger sample size to examine the behavior of users. http://www.informingscience.org/Publications/5166 AI cybersecurity systems UAE protection motivation theory (PMT) intelligent systems cyber threats information security eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-08-04 18 487 519 5177 article Venera Genia venera.genia@ui.ac.id Wahyu Setiawan Wibowo wahyu.setiawan11@ui.ac.id Muhammad Rana Tirtayasa ranatirtayasa@ymail.com Tito Febrian Nugraha tito.febrian@ui.ac.id Imairi Eitiveni imairi@cs.ui.ac.id Tifanny Nabarian nabarian@nurulfikri.ac.id Aim/Purpose: This study aims to evaluate the success of ERP post-implementation and the factors that affect the overall success of the ERP system by integrating the Task Technology Fit (TTF) model into the Information System Success Model (ISSM). Background: Not all ERP implementations provide the expected benefits, as post-implementation challenges can include inflexible ERP systems and ongoing costs. Therefore, it is necessary to evaluate the success after ERP implementation, and this research integrates the Task Technology Fit (TTF) model into the Information System Success Model (ISSM). Methodology: For data analysis and the proposed model, the authors used SmartPLS 3 by applying the PLS-SEM test and one-tailed bootstrapping. The researchers distributed questionnaires online to 115 ERP users at a construction company in Indonesia and successfully got responses from 95 ERP users. Contribution: The results obtained will be helpful and essential for future researchers and Information System practitioners – considering the high failure rate in the use of ERP in a company, as well as the inability of organizations and companies to exploit the benefits and potential that ERP can provide fully. Findings: The results show that Perceived Usefulness, User Satisfaction, and Task-Technology Fit positively affect the Organizational Impact of ERP implementation. Recommendations for Practitioners: The findings can help policymakers and CEOs of businesses in Indonesia’s construction sector create better business strategies and use limited resources more effectively and efficiently to provide a considerably higher probability of ERP deployment. The findings of this study were also beneficial for ERP vendors and consultants. The construction of the industry has specific characteristics that ERP vendors should consider. Construction is a highly fragmented sector, with specialized segments demanding specialist technologies. Several projects also influence it. They can use them to identify and establish several alternative strategies to deal with challenges and obstacles that can arise during the installation of ERP in a firm. Vendors and consultants can supply solutions, architecture, or customization support by the standard operating criteria, implement the ERP system and train critical users. The ERP system vendors and consultants can also collaborate with experts from the construction sector to develop customized alternatives for construction companies. That would be the most outstanding solution for implementing ERP in this industry. Recommendation for Researchers: Future researchers can use this combined model to study ERP post-implementation success on organizational impact with ERP systems in other company information systems fields, especially the construction sector. Future integration of different models can be used to improve the proposed model. Integration with models that assess the level of Information System acceptance, such as Technology Acceptance Model 3 (TAM3) or Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), can be used in future research to deepen the exploration of factors that influence ERP post-implementation success in an organization. Impact on Society: This study can guide companies, particularly in the construction sector, to maintain ERP performance, conduct training for new users, and regularly survey user satisfaction to ensure the ERP system’s reliability, security, and performance are maintained and measurable. Future Research: It is increasing the sample size with a larger population at other loci (private and state-owned) that use ERP to see the factors influencing ERP post-implementation success and using mixed methods to produce a better understanding. With varied modes, it is possible to get better results by adding unique factors to the research, and future integration of other models can be used to improve the proposed model. http://www.informingscience.org/Publications/5177 evaluation enterprise resource planning information system success model task technology fit organizational impact eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-08-04 18 521 545 5162 article Chin Wei Chong cwchong@mmu.edu.my Adedapo O Ojo ae0377@coventry.ac.uk Mohammad Muein Rasheed Shahin 1181400490@student.mmu.edu.my Aim/Purpose: The main aim of this study was to investigate the impact of knowledge-based Human Resources Management (HRM) practices on inbound and outbound open innovation in Jordanian small and medium enterprises (SMEs). Background: SMEs in Jordan lack tangible resources. This insufficiency can be remedied by using knowledge as a resource. According to the Knowledge-Based View (KBV) theory, which posits knowledge as the most valuable resource, SMEs can achieve open innovation by implementing knowledge-based HRM practices that enhance the utilization of knowledge and yield competitiveness. Methodology: This study adopted the quantitative method employing descriptive and exploratory approaches. A total of 500 Jordanian manufacturing SMEs were selected from 2,310 manufacturing SMEs registered lists, according to the Jordan Social Security, by using random sampling. The study’s instrument was a questionnaire that was applied to these SMEs. There were 335 responses that were deemed useful for analysis after filtering out the replies with missing values; this corresponded to a response rate of 67%. The paper utilized structural equation modeling and cross-sectional design to test hypotheses in the proposed research model. Contribution: This study advocates the assumption of the role of KBV in improving innovation practices. This study contributes to the existing strategic HRM research by extending the understanding of knowledge-based HRM practices in the context of SMEs. Thus, this study contributes to the understanding of innovation management by demonstrating the role of knowledge-based HRM practices in boosting inbound and outbound OI practices, thereby enhancing innovation as an essential component of firm competitiveness. Findings: The findings revealed the positive impact of four knowledge-based HRM practices on inbound and outbound open innovation in Jordanian manufacturing SMEs. These practices were knowledge-based recruitment and selection, knowledge-based training and development, knowledge-based compensation and reward, as well as knowledge-based performance assessment. Recommendations for Practitioners: This study is expected to help the stakeholders of SMEs to re-shape the traditional HRM practices into knowledge-based practices which improve managerial skills, innovation practices, and the level of the firm’s competitiveness. Recommendation for Researchers: This study serves as a significant contribution to the research field of innovation practices by building a new association between knowledge-based HRM practices and inbound and outbound open innovation. Impact on Society: The study emphasizes the vital role of knowledge-based HRM practices in enhancing the knowledge and social skills of the human capital in SMEs in Jordan, thus improving the country’s social and economic development. Future Research: Future research could build on this study to include service SMEs. It could also employ a longitudinal study over the long run which would allow for a deeper analysis of the relationships of causality, offering a more comprehensive view of the effect of knowledge-based HRM on open innovation. Furthermore, future research could examine the sample of investigation before and after implementing the knowledge-based HRM practices to provide stronger evidence of their influence on inbound and outbound innovation. http://www.informingscience.org/Publications/5162 knowledge-based HRM practices open innovation inbound open innovation outbound open innovation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-09-04 18 547 581 5186 article Wahyu Setiawan Wibowo wahyu.setiawan11@ui.ac.id Setiadi Yazid setiadi@cs.ui.ac.id Aim/Purpose: Blockchain technology (BCT) has emerged as a potential catalyst for transforming government institutions and services, yet the adoption of blockchain in governments faces various challenges, for which previous studies have yet to provide practical solutions. Background: This study aims to identify and analyse barriers, potential solutions, and their relations in implementing BC for governments through a systematic literature review (SLR). The authors grouped the challenges based on the Technology-Organisation-Environment (TOE) framework while exercising a thematic grouping for the solutions, followed by a comprehensive mapping to unveil the relationship between challenges and solutions. Methodology: This study employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 methodology, combined with the tollgate method, to improve the quality of selected articles. The authors further administer a three-level approach (open coding, axial coding, and selective coding) to analyse the challenges and solutions from the articles. Contribution: The authors argue that this study enriches the existing literature on BC adoption, particularly in the government context, by providing a comprehensive framework to analyse and address the unique challenges and solutions, thus contributing to the development of new theories and models for future research in BC adoption in government settings and fostering deeper exploration in the field. Findings: The authors have unveiled 40 adoption challenges categorised using the TOE framework. The most prevalent technological challenges include security concerns and integration & interoperability, while cultural resistance, lack of support and involvement, and employees’ capability hinder adoption at the organisational level. Notably, the environmental dimension lacks legal and standard frameworks. The study further unveils 28 potential solutions, encompassing legal frameworks, security and privacy measures, collaboration and governance, technological readiness and infrastructure, and strategic planning and adoption. The authors of the study have further mapped the solutions to the identified challenges, revealing that the establishment of legal frameworks stands out as the most comprehensive solution. Recommendations for Practitioners: Our findings provide a big picture regarding BC adoption for governments around the globe. This study charts the problems commonly encountered by government agencies and presents proven solutions in their wake. The authors endeavour practitioners, particularly those in governments, to embrace our findings as the cornerstone of BC/BCT adoption. These insights can aid practitioners in identifying existing or potential obstacles in adopting BC, pinpointing success factors, and formulating strategies tailored to their organisations. Recommendation for Researchers: Researchers could extend this study by making an in-depth analysis of challenges or solutions in specific types of countries, such as developed and developing countries, as the authors believe this approach would yield more insights. Researchers could also test, validate, and verify the mapping in this study to improve the quality of the study further and thus can be a great aid for governments to adopt BC/BCT fully. Impact on Society: This study provides a comprehensive exploration of BC adoption in the government context, offering detailed explanations and valuable insights that hold significant value for government policymakers and decision-makers, serving as a bedrock for successful implementation by addressing roadblocks and emphasising the importance of establishing a supportive culture and structure, engaging stakeholders, and addressing security and privacy concerns, ultimately enhancing the efficiency and effectiveness of BC adoption in government institutions and services. Future Research: Future research should address the limitations identified in this study by expanding the scope of the literature search to include previously inaccessible sources and exploring alternative frameworks to capture dynamic changes and contextual factors in BC adoption. Additionally, rigorous scrutiny, review, and testing are essential to establish the practical and theoretical validity of the identified solutions, while in-depth analyses of country-specific and regional challenges will provide valuable insights into the unique considerations faced by different governments. http://www.informingscience.org/Publications/5186 blockchain distributed ledger blockchain technology government challenge problem solution systematic literature review SLR PRISMA tollgate TOE eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-09-07 18 583 607 5185 article Puspita Kencana Sari puspita.kencana91@ui.ac.id Putu Wuri Handayani putu.wuri@cs.ui.ac.id Achmad Nizar Hidayanto nizar@cs.ui.ac.id Pribadi Wiranda Busro pribadiwb@yahoo.com Aim/Purpose: This study analyzes health professionals’ information security behavior (ISB) as health information system (HIS) users concerning associated information security controls and risks established in a public hospital. This work measures ISB using a complete measuring scale and explains the relevant influential factors from the perspectives of Protection Motivation Theory (PMT) and General Deterrence Theory (GDT) Background: Internal users are the primary source of security concerns in hospitals, with malware and social engineering becoming common attack vectors in the health industry. This study focuses on HIS user behavior in developing countries with limited information security policies and resources. Methodology: The research was carried out in three stages. First, a semi-structured interview was conducted with three hospital administrators in charge of HIS implementation to investigate information security controls and threats. Second, a survey of 144 HIS users to determine ISB based on hospital security risk. Third, a semi-structured interview was conducted with 11 HIS users to discuss the elements influencing behavior and current information security implementation. Contribution: This study contributes to ISB practices in hospitals. It discusses how HIS managers could build information security programs to enhance health professionals’ behavior by considering PMT and GDT elements. Findings: According to the findings of this study, the hospital has implemented particular information security management system (ISMS) controls based on international standards, but there is still room for improvement. Insiders are the most prevalent information security dangers discovered, with certain working practices requiring HIS users to disclose passwords with others. The top three most common ISBs HIS users practice include appropriately disposing of printouts, validating link sources, and using a password to unlock the device. Meanwhile, the top three least commonly seen ISBs include transferring sensitive information online, leaving a password in an unsupervised area, and revealing sensitive information via social media. Recommendations for Practitioners: Hospital managers should create work practices that align with information security requirements. HIS managers should provide incentives to improve workers’ perceptions of the benefit of robust information security measures. Recommendation for Researchers: This study suggests more research into the components that influence ISB utilizing diverse theoretical foundations such as Regulatory Focus Theory to compare preventive and promotion motivation to enhance ISB. Impact on Society: This study can potentially improve information security in the healthcare industry, which has substantial risks to human life but still lags behind other vital sector implementations. Future Research: Future research could look into the best content and format for an information security education and training program to promote the behaviors of healthcare professionals that need to be improved based on this ISB measurement and other influential factors. http://www.informingscience.org/Publications/5185 information security behavior hospital health information system protection motivation deterrence eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-09-18 18 609 643 5188 article Ahmad Samed Al-Adwan a.adwan@ammanu.edu.jo Omar Mohammed Horani o.horani@ammanu.edu.jo Anas RATIB ALSoud a.alsoud@ammanu.edu.jo Jacquline Tham jacquline@msu.edu.my Ali Khatibi alik@msu.edu.my S. M. Ferdous Azam drferdous@msu.edu.my Aim/Purpose: This study utilized a comprehensive framework to investigate the adoption of Business Analytics (BA) and its effects on performance in commercial banks in Jordan. The framework integrated the Technological-Organizational-Environmental (TOE) model, the Diffusion of Innovation (DOI) theory, and the Resource-Based View (RBV). Background: The recent trend of utilizing data for business operations and decision-making has positively impacted organizations. Business analytics (BA) is a leading technique that generates valuable insights from data. It has gained considerable attention from scholars and practitioners across various industries. However, guidance is lacking for organizations to implement BA effectively specific to their business contexts. This research aims to evaluate factors influencing BA adoption by Jordanian commercial banks and examine how its implementation impacts bank performance. The goal is to provide needed empirical evidence surrounding BA adoption and outcomes in the Jordanian banking sector. Methodology: The study gathered empirical data by conducting an online questionnaire survey with senior and middle managers from 13 commercial banks in Jordan. The participants were purposefully selected, and the questionnaire was designed based on relevant and well-established literature. A total of 307 valid questionnaires were collected and considered for data analysis. Contribution: This study makes a dual contribution to the BA domain. Firstly, it introduces a research model that comprehensively examines the factors that influence the adoption of BA. The proposed model integrates the TOE framework, DOI theory, and RBV theory. Combining these frameworks allows for a comprehensive examination of BA adoption in the banking industry. By analyzing the technological, organizational, and environmental factors through the TOE framework, understanding the diffusion process through the DOI theory, and assessing the role of resources and capabilities through the RBV theory, researchers and practitioners can better understand the complex dynamics involved. This integrated approach enables a more nuanced assessment of the factors that shape BA adoption and its subsequent impact on business performance within the banking industry. Secondly, it uncovers the effects of BA adoption on business performance. These noteworthy findings stem from a rigorous analysis of primary data collected from commercial banks in Jordan. By presenting a holistic model and delving into the implications for business performance, this research offers valuable insights to researchers and practitioners alike in the field of BA. Findings: The findings revealed that various technological (data quality, complexity, compatibility, relative advantage), organizational (top management support, organizational readiness), and environmental (external support) factors are crucial in shaping the decision to adopt BA. Furthermore, the study findings demonstrated a positive relationship between BA adoption and performance outcomes in Jordanian commercial banks. Recommendations for Practitioners: The findings suggest that Jordanian commercial banks should enforce data quality practices, provide clear standards, invest in data quality tools and technologies, and conduct regular data audits. Top management support is crucial for fostering a data-driven decision-making culture. Organizational readiness involves having the necessary resources and skilled personnel, as well as promoting continuous learning and improvement. Highlighting the benefits of BA helps overcome resistance to technological innovation and encourages adoption by demonstrating improved decision-making processes and operational efficiency. Furthermore, external support is crucial for banks to adopt Business Analytics (BA). Banks should partner with experienced vendors to gain expertise and incorporate best practices. Vendors also provide training and technical support to overcome technological barriers. Compatibility is essential for optimal performance, requiring managers to modify workflows and IT infrastructure. Complexity, including data, organizational, and technical complexities, is a major obstacle to BA adoption. Banks should take a holistic approach, focusing on people, processes, and technology, and prioritize data quality and governance. Building a skilled team, fostering a data-driven culture, and investing in technology and infrastructure are essential. Recommendation for Researchers: The integration of the TOE framework, the DOI theory, and the RBV theory can prove to be a powerful approach for comprehensively analyzing the various factors that influence BA adoption within the dynamic banking industry. Furthermore, this combined framework enables us to gain deeper insights into the subsequent impact of BA adoption on overall business performance. Impact on Society: Examining the factors influencing BA adoption in the banking industry and its subsequent impact on business performance can have wide-ranging societal implications. It can promote data-driven decision-making, enhance customer experiences, strengthen fraud detection, foster financial inclusion, contribute to economic growth, and trigger discussions on ethical considerations. Future Research: To further advance future research, there are several avenues to consider. One option is to broaden the scope by including a larger sample size, allowing for a more comprehensive analysis. Another possibility is to investigate the impact of BA adoption on various performance indicators beyond the ones already examined. Additionally, incorporating qualitative research methods would provide a more holistic understanding of the organizational dynamics and challenges associated with the adoption of BA in Jordanian commercial banks. http://www.informingscience.org/Publications/5188 business analytics technology adoption banking toe framework data quality diffusion of innovation organizational readiness business performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-09-22 18 645 666 5187 article Mohammad Alsharo mohammad.alsharo@aabu.edu.jo saif Addeen AlRababah saif_r@aabu.edu.jo Mohammed-Issa Riad Jaradat mi_jaradat@aabu.edu.jo Anas Husain anasjh@aabu.edu.jo Aim/Purpose: The objective of this research is to investigate the effect of review consistency between textual content and rating on review helpfulness. A measure of review consistency is introduced to determine the degree to which the review sentiment of textual content conforms with the review rating score. A theoretical model grounded in signaling theory is adopted to explore how different variables (review sentiment, review rating, review length, and review rating variance) affect review consistency and the relationship between review consistency and review helpfulness. Background: Online reviews vary in their characteristics and hence their different quality features and degrees of helpfulness. High-quality online reviews offer consumers the ability to make informed purchase decisions and improve trust in e-commerce websites. The helpfulness of online reviews continues to be a focal research issue regardless of the independent or joint effects of different factors. This research posits that the consistency between review content and review rating is an important quality indicator affecting the helpfulness of online reviews. The review consistency of online reviews is another important requirement for maintaining the significance and perceived value of online reviews. Incidentally, this parameter is inadequately discussed in the literature. A possible reason is that review consistency is not a review feature that can be readily monitored on e-commerce websites. Methodology: More than 100,000 product reviews were collected from Amazon.com and preprocessed using natural language processing tools. Then, the quality reviews were identified, and relevant features were extracted for model training. Machine learning and sentiment analysis techniques were implemented, and each review was assigned a consistency score between 0 (not consistent) and 1 (fully consistent). Finally, signaling theory was employed, and the derived data were analyzed to determine the effect of review consistency on review helpfulness, the effect of several factors on review consistency, and their relationship with review helpfulness. Contribution: This research contributes to the literature by introducing a mathematical measure to determine the consistency between the textual content of online reviews and their associated ratings. Furthermore, a theoretical model grounded in signaling theory was developed to investigate the effect on review helpfulness. This work can considerably extend the body of knowledge on the helpfulness of online reviews, with notable implications for research and practice. Findings: Empirical results have shown that review consistency significantly affects the perceived helpfulness of online reviews. The study similarly finds that review rating is an important factor affecting review consistency; it also confirms a moderating effect of review sentiment, review rating, review length, and review rating variance on the relationship between review consistency and review helpfulness. Overall, the findings reveal the following: (1) online reviews with textual content that correctly explains the associated rating tend to be more helpful; (2) reviews with extreme ratings are more likely to be consistent with their textual content; and (3) comparatively, review consistency more strongly affects the helpfulness of reviews with short textual content, positive polarity textual content, and lower rating scores and variance. Recommendations for Practitioners: E-commerce systems should incorporate a review consistency measure to rank consumer reviews and provide customers with quick and accurate access to the most helpful reviews. Impact on Society: Incorporating a score of review consistency for online reviews can help consumers access the best reviews and make better purchase decisions, and e-commerce systems improve their business, ultimately leading to more effective e-commerce. Future Research: Additional research should be conducted to test the impact of review consistency on helpfulness in different datasets, product types, and different moderating variables. http://www.informingscience.org/Publications/5187 review helpfulness review consistency regression analysis sentiment analysis signaling theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-09-26 18 667 689 5190 article Niko Ibrahim niko.ibrahim@gmail.com Putu Wuri Handayani putu.wuri@cs.ui.ac.id Betty Purwandari bettyp@cs.ui.ac.id Imairi Eitiveni imairi@cs.ui.ac.id Fadhil Dzulfikar fadhil.dzulfikar@tiket.com Aim/Purpose: This study aims to create customer segmentation who use Online Travel Agent (OTA) mobile applications in Indonesia throughout their hotel booking journey. Background: In the context of mobile hotel booking applications, research analyzing the customer experience at each customer journey stage is scarce. However, literature increasingly acknowledges the significance of this stage in comprehending customer behavior and revenue streams. Methodology: This study employs a mixed-method and exploratory approach by doing in-depth interviews with 20 participants and questionnaires from 207 participants. Interview data are analyzed using thematic analysis, while the questionnaires are analyzed using descriptive statistics. Contribution: This study enriches knowledge in understanding customer behavior that considers the usage of mobile apps as a segmentation criterion in the hotel booking journey. Findings: We developed four user personas (no sweat player, spotless seeker, social squad, and bargain hunter) that show customer segmentation based on the purpose, motivation, and actions in each journey stage (inspiration, consideration, reservation, and experience). Recommendations for Practitioners: The resulting customer segmentation enables hospitality firms to improve their current services by adapting to the needs of various segments and avoiding unanticipated customer pain points, such as incomplete information, price changes, no social proof, and limited payment options. Recommendation for Researchers: The quality and robustness of the customer segment produced in this study can be further tested based on the criteria of homogeneity, size, potential benefits, segment stability, segment accessibility, segment compatibility, and segment actionability. Impact on Society: This study has enriched the existing literature by establishing a correlation between user characteristics and how they use smartphones for tourism planning, focusing on hotel booking in mobile applications. Future Research: For future research, each customer segment’s demographic and behavioral factors can be explored further. http://www.informingscience.org/Publications/5190 customer journey customer segmentation mobile hotel booking application online travel agent smartphone eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-10-03 18 691 718 5189 article Zainab Meskaoui zainab.meskaoui@gmail.com Abdelilah ELKHARRAZ aelkharraz@uae.ac.ma Aim/Purpose: The aim of this research paper is to suggest a comprehensive model that incorporates the technology acceptance model with the task-technology fit model, information quality, security, trust, and managerial support to investigate the intended usage of big data analytics (BDA) in banks and insurance companies. Background: The emergence of the concept of “big data,” prompted by the widespread use of connected devices and social media, has been pointed out by many professionals and financial institutions in particular, which makes it necessary to assess the determinants that have an impact on behavioral intention to use big data analytics in banks and insurance companies. Methodology: The integrated model was empirically assessed using self-administered questionnaires from 181 prospective big data analytics users in Moroccan banks and insurance firms and examined using partial least square (PLS) structural equation modeling. The results cover sample characteristics, an analysis of the validity and reliability of measurement models’ variables, an evaluation of the proposed hypotheses, and a discussion of the findings. Contribution: The paper makes a noteworthy contribution to the BDA adoption literature within the finance sector. It stands out by ingeniously amalgamating the Technology Acceptance Model (TAM) with Task-Technology Fit (TTF) while underscoring the critical significance of information quality, trust, and managerial support, due to their profound relevance and importance in the finance domain. Thus showing BDA has potential applications beyond the finance sector. Findings: The findings showed that TTF and trust’s impact on the intention to use is considerable. Information quality positively impacted perceived usefulness and ease of use, which in turn affected the intention to use. Moreover, managerial support moderates the correlation between perceived usefulness and the intention to use, whereas security did not affect the intention to use and managerial support did not moderate the influence of perceived ease of use. Recommendations for Practitioners: The results suggest that financial institutions can improve their adoption decisions for big data analytics (BDA) by understanding how users perceive it. Users are predisposed to use BDA if they presume it fits well with their tasks and is easy to use. The research also emphasizes the importance of relevant information quality, managerial support, and collaboration across departments to fully leverage the potential of BDA. Recommendation for Researchers: Further study may be done on other business sectors to confirm its generalizability and the same research design can be employed to assess BDA adoption in organizations that are in the advanced stage of big data utilization. Impact on Society: The study’s findings can enable stakeholders of financial institutions that are at the primary stage of big data exploitation to understand how users perceive BDA technologies and the way their perception can influence their intention toward their use. Future Research: Future research is expected to conduct a comparison of the moderating effect of managerial support on users with technical expertise versus those without; in addition, international studies across developed countries are required to build a solid understanding of users’ perceptions towards BDA. http://www.informingscience.org/Publications/5189 Big Data Analytics TAM model behavioral intention to use Task Technology Fit information quality finance banks insurance companies security trust managerial support eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-10-03 18 719 737 5192 article Tianpei Xu xutianpei@hlbec.edu.cn Ying Ma marian0225@163.com Changyu Ao aochangyu@jnu.ac.kr Min Qu 220018@jvic.edu.cn XiangHong Meng mxh-hlr@163.com Aim/Purpose: In this paper, we present an RFM model-based telecom customer churn system for better predicting and analyzing customer churn. Background: In the highly competitive telecom industry, customer churn is an important research topic in customer relationship management (CRM) for telecom companies that want to improve customer retention. Many researchers focus on a telecom customer churn analysis system to find out the customer churn factors for improving prediction accuracy. Methodology: The telecom customer churn analysis system consists of three main parts: customer segmentation, churn prediction, and churn factor identification. To segment the original dataset, we use the RFM model and K-means algorithm with an elbow method. We then use RFM-based feature construction for customer churn prediction, and the XGBoost algorithm with SHAP method to obtain a feature importance ranking. We chose an open-source customer churn dataset that contains 7,043 instances and 21 features. Contribution: We present a novel system for churn analysis in telecom companies, which encompasses customer churn prediction, customer segmentation, and churn factor analysis to enhance business strategies and services. In this system, we leverage customer segmentation techniques for feature construction, which enables the new features to improve the model performance significantly. Our experiments demonstrate that the proposed system outperforms current advanced customer churn prediction methods in the same dataset, with a higher prediction accuracy. The results further demonstrate that this churn analysis system can help telecom companies mine customer value from the features in a dataset, identify the primary factors contributing to customer churn, and propose suitable solution strategies. Findings: Simulation results show that the K-means algorithm gets better results when the original dataset is divided into four groups, so the K value is selected as 4. The XGBoost algorithm achieves 79.3% and 81.05% accuracy on the original dataset and new data with RFM, respectively. Additionally, each cluster has a unique feature importance ranking, allowing for specialized strategies to be provided to each cluster. Overall, our system can help telecom companies implement effective CRM and marketing strategies to reduce customer churn. Recommendations for Practitioners: More accurate churn prediction reduces misjudgment of customer churn. The acquisition of customer churn factors makes the company more convenient to analyze the reasons for churn and formulate relevant conservation strategies. Recommendation for Researchers: The research achieves 81.05% accuracy for customer churn prediction with the Xgboost and RFM algorithms. We believe that more enhancements algorithms can be attempted for data preprocessing for better prediction. Impact on Society: This study proposes a more accurate and competitive customer churn system to help telecom companies conserve the local markets and reduce capital outflows. Future Research: The research is also applicable to other fields, such as education, banking, and so forth. We will make more new attempts based on this system. http://www.informingscience.org/Publications/5192 CRM churn prediction feature construction RFM K-means XGBoost SHAP method eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-10-07 18 739 767 5196 article Md Kassim Normalini normalini_mk@yahoo.com Zhu Fei zhufei@student.usm.my Wan Normila Mohamad wanno794@uitm.edu.my Aim/Purpose: This study aims to develop a comprehensive conceptual framework that incorporates personal characteristics, social context, and technological features as significant factors that influence the intention of small-city users in China to use mobile health. Background: Mobile health has become an integral part of China’s health management system innovation, the transformation of the health service model, and a necessary government measure for promoting health service parity. However, mobile health has not yet been widely adopted in small cities in China. Methodology: The study utilized a quantitative approach whereby web-based questionnaires were used to collect data from 319 potential users in China using China’s health management system. The data was analyzed using the PLS-SEM (the partial least squares-structural equation modeling) approach. Contribution: This study integrates the protection motivation theory (PMT), which compensates for the limitations of the unified theory of acceptance and use of technology theory (UTAUT) and is a re-examination of PMT and UTAUT in a small city context in China. Findings: The findings indicate that attitude and perceived vulnerability in the personal characteristic factors, social influence and facilitating conditions in the social context factors, and performance expectancy in the technological feature factors influence users’ intention to use mobile health in small cities in China. Recommendations for Practitioners: This study provides feasible recommendations for mobile health service providers, medical institutions, and government agencies based on the empirical results. Recommendation for Researchers: As for health behavior, researchers should fully explain the intention of mobile health use in terms of holism and health behavior theory. Impact on Society: This study aims to increase users’ intention to use mobile health in small cities in China and to maximize the social value of mobile health. Future Research: Future research should concentrate on the actual usage behavior of users and simultaneously conduct a series of longitudinal studies, including studies on continued usage behavior, abandonment behavior, and abandoned-and-used behavior. http://www.informingscience.org/Publications/5196 mobile health small cities PMT UTAUT personal characteristics eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-10-08 18 769 790 5193 article Raed A Shatnawi raedamin@just.edu.jo Aim/Purpose: To predict the change-proneness of software from the continuous evolution using machine learning methods. To identify when software changes become statistically significant and how metrics change. Background: Software evolution is the most time-consuming activity after a software release. Understanding evolution patterns aids in understanding post-release software activities. Many methodologies have been proposed to comprehend software evolution and growth. As a result, change prediction is critical for future software maintenance. Methodology: I propose using machine learning methods to predict change-prone classes. Classes that are expected to change in future releases were defined as change-prone. The previous release was only considered by the researchers to define change-proneness. In this study, I use the evolution of software to redefine change-proneness. Many snapshots of software were studied to determine when changes became statistically significant, and snapshots were taken biweekly. The research was validated by looking at the evolution of five large open-source systems. Contribution: In this study, I use the evolution of software to redefine change-proneness. The research was validated by looking at the evolution of five large open-source systems. Findings: Software metrics can measure the significance of evolution in software. In addition, metric values change within different periods and the significance of change should be considered for each metric separately. For five classifiers, change-proneness prediction models were trained on one snapshot and tested on the next. In most snapshots, the prediction performance was excellent. For example, for Eclipse, the F-measure values were between 80 and 94. For other systems, the F-measure values were higher than 75 for most snapshots. Recommendations for Practitioners: Software change happens frequently in the evolution of software; however, the significance of change happens over a considerable length of time and this time should be considered when evaluating the quality of software. Recommendation for Researchers: Researchers should consider the significance of change when studying software evolution. Software changes should be taken from different perspectives besides the size or length of the code. Impact on Society: Software quality management is affected by the continuous evolution of projects. Knowing the appropriate time for software maintenance reduces the costs and impacts of software changes. Future Research: Studying the significance of software evolution for software refactoring helps improve the internal quality of software code. http://www.informingscience.org/Publications/5193 software evolution software metrics change-proneness machine learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-11-01 18 791 818 5205 article SUDARSANAM S K sudarsanam.sk@vit.ac.in Venkateswaran Vinod venkateswaran.vinod2017@vitstudent.ac.in Aim/Purpose: Acquisitions play a pivotal role in the growth strategy of a firm. Extensive resources and time are dedicated by a firm toward the identification of prospective acquisition candidates. The Indian manufacturing sector is currently experiencing significant growth, organically and inorganically, through acquisitions. The principal aim of this study is to explore models that can predict acquisitions and compare their performance in the Indian manufacturing sector. Background: Mergers and Acquisitions (M&A) have been integral to a firm’s growth strategy. Over the years, academic research has investigated multiple models for predicting acquisitions. In the context of the Indian manufacturing industry, the research is limited to prediction models. This research paper explores three models, namely Logistic Regression, Decision Tree, and Multilayer Perceptron, to predict acquisitions. Methodology: The methodology includes defining the accounting variables to be used in the model which have been selected based on strong theoretical foundations. The Indian manufacturing industry was selected as the focus, specifically, data for firms listed in the Bombay Stock Exchange (BSE) between 2010 and 2022 from the Prowess database. There were multiple techniques, such as data transformation and data scrubbing, that were used to mitigate bias and enhance the data reliability. The dataset was split into 70% training and 30% test data. The performance of the three models was compared using standard metrics. Contribution: The research contributes to the existing body of knowledge in multiple dimensions. First, a prediction model customized to the Indian manufacturing sector has been developed. Second, there are accounting variables identified specific to the Indian manufacturing sector. Third, the paper contributes to prediction modeling in the Indian manufacturing sector where there is limited research. Findings: The study found significant supporting evidence for four of the proposed hypotheses indicating that accounting variables can be used to predict acquisitions. It has been ascertained that statistically significant variables influence acquisition likelihood: Quick Ratio, Equity Turnover, Pretax Margin, and Total Sales. These variables are intrinsically linked with the theories of liquidity, growth-resource mismatch, profitability, and firm size. Furthermore, comparing performance metrics reveals that the Decision Tree model exhibits the highest accuracy rate of 62.3%, specificity rate of 66.4%, and the lowest false positive ratio of 33.6%. In contrast, the Multilayer Perceptron model exhibits the highest precision rate of 61.4% and recall rate of 64.3%. Recommendations for Practitioners: The study findings can help practitioners build custom prediction models for their firms. The model can be developed as a live reference model, which is continually updated based on a firm’s results. In addition, there is an opportunity for industry practitioners to establish a benchmark score that provides a reference for acquisitions. Recommendation for Researchers: Researchers can expand the scope of research by including additional classification modeling techniques. The data quality can be enhanced by cross-validation with other databases. Textual commentary about the target firms, including management and analyst quotes, provides additional insight that can enhance the predictive power of the models. Impact on Society: The research provides insights into leveraging emerging technologies to predict acquisitions. The theoretical basis and modeling attributes provide a foundation that can be further expanded to suit specific industries and firms. Future Research: There are opportunities to expand the scope of research in various dimensions by comparing acquisition prediction models across industries and cross-border and domestic acquisitions. Additionally, it is plausible to explore further research by incorporating non-financial data, such as management commentary, to augment the acquisition prediction model. http://www.informingscience.org/Publications/5205 Indian manufacturing industry acquisitions mergers and acquisitions modeling predictive modeling machine learning artificial neural networks eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-11-12 18 819 840 5214 article Anbalagan Bhuvaneswari bhuvana.cse14@gmail.com Aim/Purpose: The understanding of disease spread dynamics in the context of air travel is crucial for effective disease detection and epidemic intelligence. The Susceptible-Exposed-Infectious-Recovered-Hospitalized-Critical-Deaths (SEIR-HCD) model proposed in this research work is identified as a valuable tool for capturing the complex dynamics of disease transmission, healthcare demands, and mortality rates during epidemics. Background: The spread of viral diseases is a major problem for public health services all over the world. Understanding how diseases spread is important in order to take the right steps to stop them. In epidemiology, the SIS, SIR, and SEIR models have been used to mimic and study how diseases spread in groups of people. Methodology: This research focuses on the integration of air traffic network data into the SEIR-HCD model to enhance the understanding of disease spread in air travel settings. By incorporating air traffic data, the model considers the role of travel patterns and connectivity in disease dissemination, enabling the identification of high-risk routes, airports, and regions. Contribution: This research contributes to the field of epidemiology by enhancing our understanding of disease spread dynamics through the application of the SIS, SIR, and SEIR-HCD models. The findings provide insights into the factors influencing disease transmission, allowing for the development of effective strategies for disease control and prevention. Findings: The interplay between local outbreaks and global disease dissemination through air travel is empirically explored. The model can be further used for the evaluation of the effectiveness of surveillance and early detection measures at airports and transportation hubs. The proposed research contributes to proactive and evidence-based strategies for disease prevention and control, offering insights into the impact of air travel on disease transmission and supporting public health interventions in air traffic networks. Recommendations for Practitioners: Government intervention can be studied during difficult times which plays as a moderating variable that can enhance or hinder the efficacy of epidemic intelligence efforts within air traffic networks. Expert collaboration from various fields, including epidemiology, aviation, data science, and public health with an interdisciplinary approach can provide a more comprehensive understanding of the disease spread dynamics in air traffic networks. Recommendation for Researchers: Researchers can collaborate with international health organizations and authorities to share their research findings and contribute to a global understanding of disease spread in air traffic networks. Impact on Society: This research has significant implications for society. By providing a deeper understanding of disease spread dynamics, it enables policymakers, public health officials, and practitioners to make informed decisions to mitigate disease outbreaks. The recommendations derived from this research can aid in the development of effective strategies to control and prevent the spread of infectious diseases, ultimately leading to improved public health outcomes and reduced societal disruptions. Future Research: Practitioners of the research can contribute more effectively to disease outbreaks within the context of air traffic networks, ultimately helping to protect public health and global travel. By considering air traffic patterns, the SEIR-HCD model contributes to more accurate modeling and prediction of disease outbreaks, aiding in the development of proactive and evidence-based strategies to manage and mitigate the impact of infectious diseases in the context of air travel. http://www.informingscience.org/Publications/5214 epidemiology SIS-SIR model SEIR-HCD models disease dynamics air traffic networks disease transmission eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-11-25 18 841 869 5215 article Rinto Priambodo rinto.priambodo11@ui.ac.id Putu Wuri Handayani putu.wuri@cs.ui.ac.id Rizal Fathoni Aji rizal@cs.ui.ac.id Aim/Purpose: This paper illustrates the potential of health recommender systems (HRS) to support and enhance maternal care. The study aims to explore the recent implementations of maternal HRS and to discover the challenges of the implementations. Background: The sustainable development goals (SDG) aim to reduce maternal mortality to less than 70 per 100,000 live births by 2030. However, progress is uneven between countries, with primary causes being severe bleeding, infections, high blood pressure, and failed abortions. Regular antenatal care (ANC) visits are crucial for detecting and managing complications, such as hypertensive illnesses, anemia, and gestational diabetes mellitus. Utilizing maternal evaluations during ANC visits can help identify and treat problems early, lowering morbidity and death rates for both mothers and fetuses. Technology-enabled daily health recording can help monitor pregnancy by providing actionable guides to patients and health workers based on patient status. Methodology: A systematic literature review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify maternal HRS reported in studies between November 2022 and December 2022. Information was subsequently extracted to understand the potential benefits of maternal HRS. Titles and abstracts of 1,851 studies were screened for the full-text screening, in which two reviewers independently selected articles and systematically extracted data using a predefined extraction form. Contribution: This study adds to the explorations of the challenges of implementing HRS for maternal care. This study also emphasizes the significance of explainability, data-driven methodologies, automation, and the necessity for integration and interoperability in the creation and deployment of health recommendation systems for maternity care. Findings: The majority of maternal HRS use a knowledge-based (constraint-based) ap-proach with more than half of the studies generating recommendations based on rules defined by experts or available guidelines. We also derived four types of interfaces that can be used for delivering recommendations. Moreover, patient health records as data sources can hold data from patients’ or health workers’ input or directly from the measurement devices. Finally, the number of studies in the pilot or demonstration stage is twice that in the sustained stages. We also discovered crucial challenges where the explainability of the methods was needed to ensure trustworthiness, comprehensibility, and effective enhancement of the decision-making process. Automatic data collection was also required to avoid complexity and reduce workload. Other obstacles were also identified where data integration between systems should be established and decent connectivity must be provided so that complete services can be admin-istered. Lastly, sustainable operations would depend on the availability of standards for integration and interoperability as well as sufficient financial sup-port. Recommendations for Practitioners: Developers of maternal HRS should consider including the system in the main healthcare system, providing connectivity, and automation to deliver better service and prevent maternal risks. Regulations should also be established to support the scale-up. Recommendation for Researchers: Further research is needed to do a thorough comparison of the recommendation techniques used in maternal HRS. Researchers are also recommended to explore more on this topic by adding more research questions. Impact on Society: This study highlights the lack of sustainability studies, the potential for scaling up, and the necessity for a comprehensive strategy to integrate the maternal recommender system into the larger maternal healthcare system. Researchers can enhance and improve health recommendation systems for maternity care by focusing on these areas, which will ultimately increase their efficacy and facilitate clinical practice integration. Future Research: Additional research can concentrate on creating and assessing methods to increase the explainability and interpretability of data-driven health recommender systems and integrating automatic measurement into the traditional health recommender system to enhance the anticipated outcome of antenatal care. Comparative research can also be done to assess how well various models or algorithms utilized in these systems function. Future research can also examine creative solutions to address resource, infrastructure, and technological constraints, such as connectivity and automation to help address the shortage of medical personnel in remote areas, as well as define tactics for long-term sustainability and integration into current healthcare systems. http://www.informingscience.org/Publications/5215 health recommender system maternal care antenatal care systematic literature review eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2023-12-26 18 871 891 5233 article Ismail Bello esmailbello@gmail.com Mazida Ahmad mazida@uum.edu.my Maslinda Mohd Nadzir maslinda@uum.edu.my Aim/Purpose: The purpose of this study is to identify the key determinants hindering Knowledge Transfer (KT) practices for Information Technology Project Managers (ITPMs) Background: The failure rate of IT projects remains unacceptably high worldwide, and KT between project managers and team members has been recognized as a significant issue affecting project success. Therefore, this study tries to identify the determinants of KT within the context of IT projects for ITPMs. Methodology: A systematic review of the literature (SLR) was employed in the investigation. The SLR found 28 primary studies on KT for ITPMs that were published in Scopus and Web of Science databases between 2010 and 2023. Contribution: Social Cognitive Theory (SCT) was used to build a theoretical framework where the determinants were categorized into Personal factors, Environmental (Project organizational) factors, and other factors, such as Technological factors influencing ITPMs (Behavioral factors), to implement in KT practices. Findings: The review identified 11 key determinants categorized into three broad categories: Personal factors (i.e., motivation, absorptive capability, trust, time urgency), Project Organizational factors (i.e., team structure, leadership style, reward system, organizational culture, communication), and Technological factors (i.e., project task collaboration tool and IT infrastructure and support) that influence implementing KT for ITPMs Recommendations for Practitioners: The proposed framework in this paper can be used by project managers as a guide to adopt KT practices within their project organization. Recommendation for Researchers: The review showed that some determinants, such as Technological factors, have not been adequately explored in the existing KT model in the IT projects context and can be integrated with other relevant theories to understand how a project manager’s knowledge can be transferred and retained in the organization using technology in future research. Impact on Society: This study emphasizes the role of individual actions and project organizational and technological matters in shaping the efficacy of KT within project organizations. It offers insight that could steer business owners or executives within project organizations to closely observe the behavior of project managers, thereby securing successful project outcomes. Future Research: The determinant list provided in this paper is acquired from extensive SLR and, therefore, further research should aim to expand and deepen the investigation by validating these determinants from experts in the field of IT and project management. Future studies can also add other external technological determinants to provide a more comprehensive KT implementation framework. Similarly, this research does not include determinants identified directly from the industry, as it relies solely on determinants found in the existing literature. Although a comprehensive attempt has been made to encompass all relevant papers, there remains a potential for overlooking some research in this process. http://www.informingscience.org/Publications/5233 knowledge transfer knowledge transfer determinants project manager information technology project eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2024-02-08 18 893 914 5241 article Imran Mahmud imranmahmud@daffodilvarsity.edu.bd Nusrat Jahan nusrat.swe@diu.edu.bd Afsana Begum afsana.swe@diu.edu.bd Kodisvaran Supramaniam striker.usm@gmail.com Adiba Masud adiba.swe0100.c@diu.edu.bd Aim/Purpose: The study aims to explore the attributes of self-phubbing and partner-phubbing, as well as their impact on marital relationship satisfaction and the quality of communication. Furthermore, it aims to comprehend how these characteristics could impact an individual’s total level of life satisfaction. Background: The study aims to establish a clear association between specific mobile phone usage behaviors and their subsequent impact on relationship satisfaction and the quality of communication. This study investigates the effects of two types of behaviors on interpersonal relationships: self-phubbing, which refers to an individual being deeply absorbed in their own mobile phone use, and partner-phubbing, which refers to witnessing one’s partner being deeply absorbed in a mobile device. Methodology: This study utilizes a quantitative approach. The poll involved 150 smartphone users in Malaysia who are in relationships, and they participated by completing a questionnaire. The data analysis was performed using the Partial Least Squares-based Structural Equation Modeling method. Contribution: This research addresses the gap and gives insight into the consequences of self and partner phubbing and its impact on the relationship and life satisfaction among partners by providing a research model that was validated with primary data. Findings: The results of this survey show that smartphone conflicts harm relationship satisfaction but not communication quality. It was revealed that communication quality does not directly bring a negative impact on life satisfaction, but it directly affects relationship satisfaction, which, in turn, harms life satisfaction. Recommendations for Practitioners: The findings of this study can be used by practitioners to improve relationship counseling and therapy. Through the integration of the notion of phubbing and its impact on relationship happiness, couples can receive guidance on how to reduce the tension that arises from using smartphones. Recommendation for Researchers: Previous research was conducted exclusively on only an individual’s phubbing behavior, but limited work was done on the partner’s phubbing behavior. Future researchers can enhance this model by identifying more factors. Impact on Society: This study addresses broader societal ramifications in addition to the dynamics of particular relationships. This study promotes a more mindful use of smartphones by exposing the complex relationships between technology use, relationship happiness, and general life contentment. This will ultimately lead to healthier relationships and improved societal well-being. Future Research: In the future, we are going to implement an artificial neural network approach to test this data to predict the most important factors that influence phubbing. http://www.informingscience.org/Publications/5241 phubbing cellphone conflicts communication quality relationship satisfaction and life satisfaction eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-01-06 17 .i iv 4901 article Geoffrey Z. Liu geoffrey.liu@sjsu.edu Table of Contents for Volume 17, 2022, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/4901 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-01-06 17 001 033 4896 article Anantha Raj A. Arokiasamy anantharaj.arokiasamy@rmit.edu.vn Greeni Maheshwari greeni.maheshwari@rmit.edu.vn Khanh-Linh Nguyen nklinh_h1a1@yahoo.com Aim/Purpose: ************************************************************************ After its investigation, the Research Ethics, Integrity, and Governance team at RMIT University found that the primary author of this paper breached the Australian Code and/or RMIT Policy and requested that the article be retracted. ************************************************************************** This paper aimed to examine the influence of ethical and transformational leadership on employee creativity in Malaysia’s private higher education institutions (PHEIs) and the mediating role of organizational citizenship behavior. Background: To ensure their survival and success in today’s market, organizations need people who are creative and driven. Previous studies have demonstrated the importance of ethical leadership in fostering employee innovation and good corporate responsibility. Research on ethical leadership and transformational leadership, in particular, has played a significant role in elucidating the role of leadership in relation to organizational citizenship behavior (OCB). In this study, we have focused on ethical and transformational leadership as an antecedent for enhancing employee creativity. Despite an increase in leadership research, little is known about the underlying mechanisms that link ethical leadership and transformational leadership to OCB. Because it sheds light on factors other than ethical leadership and transformational leadership that influence employees’ extra-role activity, this research is relevant theoretically. OCB may have a mediating function between ethical leadership and transformational leadership style and employee creativity because it is associated with the greatest outcomes, but empirical research has yet to prove this. So, one of the study’s goals is to add to the hypotheses about how ethical leadership style and transformational leadership affect employee creativity by using an important mediating variable – OCB. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. A convenient sampling approach was used to gauge 275 employees from Malaysia’s PHEIs. To test the hypotheses and obtain a conclusion, the acquired data was analyzed using the partial least square technique (PLS-SEM). Contribution: The study contributes to leadership literature by advancing OCB as a mediating factor that accounts for the link between ethical and transformational leadership and employee creativity in the higher education sector. Findings: According to the research, OCB has a substantial influence on the creativity of employees. Furthermore, ethical leadership boosted OCB and boosted employee creativity, according to the research. OCB and employee creativity have both been demonstrated to benefit greatly from transformational leadership. Further research revealed that OCB is a mediating factor in the link between leadership styles and creative thinking among employees. Recommendations for Practitioners: Higher education institutions should focus on developing leaders who value transparency and self-awareness in their interactions with followers and who demonstrate an inner moral perspective in addition to balanced information processing to ensure positive outcomes at the individual and organizational levels. Higher education institutions should place a priority on hiring leaders that exhibit ethical and transformational traits to raise awareness of these leadership styles among employees. Recommendation for Researchers: The new study also adds significantly to the body of knowledge by examining the relationship between ethical and transformational leadership and the creativity of the workforce. It aimed to identify the relationship between transformational leadership style and individual creativity in higher education by examining the mediating influence of OCB. Impact on Society: Higher education institutions should devise strategies for developing ethical and transformative leaders who will assist boost OCB and creativity within their workforce. Students and faculty in higher education can benefit from these leadership methods by learning to think in more diverse ways and by developing thought processes that lead to a larger pool of innovative ideas and solutions. As a consequence, employees who show creative behavior may be effectively managed by leaders who utilize ethical and transformational leadership styles and motivate them to show OCB that allow them to solve creative problems creatively. Future Research: A mixed-methods approach should be used in future research, and this should be done in public institutions in developing and developed nations to put the findings to use and generalize them even further. Future research will be able to examine other mediators to learn more about how and why ethical and transformational leadership styles affect PHEI employees’ creativity. http://www.informingscience.org/Publications/4896 ethical leadership transformational leadership employee creativity private higher education institutions Malaysia organizational citizenship behavior eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-01-09 17 035 065 4897 article Niharika Prasanna Kumar niharikaresearch7@gmail.com Aim/Purpose: This paper aims to analyze the availability and pricing of perishable farm produce before and during the lockdown restrictions imposed due to Covid-19. This paper also proposes machine learning and deep learning models to help the farmers decide on an appropriate market to sell their farm produce and get a fair price for their product. Background: Developing countries like India have regulated agricultural markets governed by country-specific protective laws like the Essential Commodities Act and the Agricultural Produce Market Committee (APMC) Act. These regulations restrict the sale of agricultural produce to a predefined set of local markets. Covid-19 pandemic led to a lockdown during the first half of 2020 which resulted in supply disruption and demand-supply mismatch of agricultural commodities at these local markets. These demand-supply dynamics led to disruptions in the pricing of the farm produce leading to a lower price realization for farmers. Hence it is essential to analyze the impact of this disruption on the pricing of farm produce at a granular level. Moreover, the farmers need a tool that guides them with the most suitable market/city/town to sell their farm produce to get a fair price. Methodology: One hundred and fifty thousand samples from the agricultural dataset, released by the Government of India, were used to perform statistical analysis and identify the supply disruptions as well as price disruptions of perishable agricultural produce. In addition, more than seventeen thousand samples were used to implement and train machine learning and deep learning models that can predict and guide the farmers about the appropriate market to sell their farm produce. In essence, the paper uses descriptive analytics to analyze the impact of COVID-19 on agricultural produce pricing. The paper explores the usage of prescriptive analytics to recommend an appropriate market to sell agricultural produce. Contribution: Five machine learning models based on Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Random Forest, and Gradient Boosting, and three deep learning models based on Artificial Neural Networks were implemented. The performance of these models was compared using metrics like Precision, Recall, Accuracy, and F1-Score. Findings: Among the five classification models, the Gradient Boosting classifier was the optimal classifier that achieved precision, recall, accuracy, and F1 score of 99%. Out of the three deep learning models, the Adam optimizer-based deep neural network achieved precision, recall, accuracy, and F1 score of 99%. Recommendations for Practitioners: Gradient boosting technique and Adam-based deep learning model should be the preferred choice for analyzing agricultural pricing-related problems. Recommendation for Researchers: Ensemble learning techniques like Random Forest and Gradient boosting perform better than non-Ensemble classification techniques. Hyperparameter tuning is an essential step in developing these models and it improves the performance of the model. Impact on Society: Statistical analysis of the data revealed the true nature of demand and supply and price disruption. This analysis helps to assess the revenue impact borne by the farmers due to Covid-19. The machine learning and deep learning models help the farmers to get a better price for their crops. Though the da-taset used in this paper is related to India, the outcome of this research work applies to many developing countries that have similar regulated markets. Hence farmers from developing countries across the world can benefit from the outcome of this research work. Future Research: The machine learning and deep learning models were implemented and tested for markets in and around Bangalore. The model can be expanded to cover other markets within India. http://www.informingscience.org/Publications/4897 Machine Learning Classification Logistic Regression K-Nearest Neighbors Support Vector Machine Random Forest Gradient Boosting Deep Learning Artificial Neural Network Deep Neural Network Covid-19 Agriculture eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-01-17 17 067 086 4892 article Chin Wei Chong cwchong@mmu.edu.my Yee Yen Yuen yyyuen@mmu.edu.my Aim/Purpose: The aim of this paper is to examine the influences of KM-centred strategies on innovation capability among Malaysian R&D firms. It also deepens understanding of the pathways and conditions to improve the innovation capability by assessing the mediating role of both KM practices, i.e., knowledge exploration practices, and knowledge exploitation practices. Background: Knowledge is the main organisational resource that is able to generate a competitive advantage through innovation. It is a critical success driver for both knowledge exploration and exploitation for firms to achieve sustainable competitive advantages. Methodology: A total of 320 questionnaires were disseminated to Malaysian R&D firms and the response rate was 47 percent. The paper utilised structural equation modelling and cross-sectional design to test hypotheses in the proposed research model. Contribution: This paper provides useful information and valuable initiatives in exploring the mediating role of knowledge exploration and knowledge exploitation in influencing innovation in Malaysian R&D firms. It helps R&D firms to frame their KM activities to drive the capability of creating and retaining a greater value onto their core business competencies. Findings: The findings indicate that all three KM-centred strategies (leadership, HR practices, and culture) have a direct effect on innovation. In addition, KM exploration practices mediate HR practices on innovation while KM exploitation mediates both leadership and HR practices on innovation. Recommendations for Practitioners: This paper serves as a guide for R&D managers to determine the gaps and appropriate actions to collectively achieve the desired R&D results and national innovation. It helps R&D firms frame their KM activities to enhance the capability of creating and retaining a greater value to their core business competencies. Recommendation for Researchers: This paper contributes significantly to knowledge management and innovation research by establishing new associations among KM-centred strategies, i.e., leadership, HR practices, and culture, both KM practices (knowledge exploration and knowledge exploitation), and innovation. Impact on Society: This paper highlights the important role of knowledge leaders and the practice of effective HR practices to help R&D firms to create a positive environment that facilitates both knowledge exploration and knowledge exploitation in enhancing innovation capabilities. Future Research: Further research could use a longitudinal sample to examine relationships of causality, offering a more comprehensive view of the effect of KM factors on innovation over the long term. Future research should also try to incorporate information from new external sources, such as customers or suppliers. http://www.informingscience.org/Publications/4892 KM-centred strategies knowledge exploration knowledge exploitation innovation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-02-22 17 087 100 4922 article Lusi Li lli57@calstatela.edu Wenlu Zhang wenlu.zhang@csulb.edu Liuliu Fu lfu8@calstatela.edu Aim/Purpose: In this study, we aim to investigate the impact of an important characteristic of textual reviews – the diversity of the review content on review helpfulness. Background: Consumer-generated reviews are an essential format of online Word-of-Month that help customers reduce uncertainty and information asymmetry. However, not all reviews are equally helpful as reflected by the varying number of helpfulness votes received by reviews. From consumers’ perspective, what kind of content is more effective and useful for making purchase decisions is unclear. Methodology: We use a data set consisting of consumer reviews for laptop products on Amazon from 2014 to 2018. A topic modeling technique is implemented to unveil the hidden topics embedded in the reviews. Based on the extracted topics, we compute the text diversity score of each review. The diversity score measures how diverse the content in a review is compared to other reviews. Contribution: In the literature, studies have examined various factors that can influence review helpfulness. However, studies that emphasized the information value of textual reviews are limited. Our study contributes to the extant literature of online word-of-mouth by establishing the connection between the diversity of the review content and consumer perceived helpfulness. Findings: Empirical results show that text diversity plays an important role in consumers’ evaluation of whether the review is helpful. Reviews that contain more diverse content tend to be more helpful to consumers. Moreover, we find a negative interaction effect between text diversity and the text depth. This result suggests that text depth and text diversity have a substitution effect. When a review contains more in-depth content, the impact of text diversity is weakened. Recommendations for Practitioners: For consumers to quickly find the informative reviews, platforms should incorporate measures such as text diversity in the ranking algorithms to rank consumer reviews. Future Research: Future study can extend the current research by examine the impact of text diversity for experienced goods and compare the results with search goods. http://www.informingscience.org/Publications/4922 review helpfulness text diversity latent dirichlet allocation online consumer reviews eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-02-24 17 101 123 4921 article Isaac Asampana isaac.asampana@upsamail.edu.gh Albert Akanlisikum Akanferi albert.akanferi@upsamail.edu.gh Akwetey Henry Matey hmateyakwetey@upsamail.edu.gh Hannah Ayaba Tanye hannah.tanye@upsamail.edu.gh Aim/Purpose: This paper aims to analyze how artisans in Ghana are incorporating mobile commerce into their everyday business and how perceived usefulness, perceived ease of use, subjective norms, age, gender, expertise, and educational level affected the adoption and usage of m-commerce. Background: This study integrates well-established theoretical models to create a new conceptual model that ensures a comprehensive mobile commerce adoption survey. Methodology: A cross-sectional survey was conducted to measure the constructs and their relations to test the research model. Contribution: The study’s findings confirmed previous results and produced a new conceptual model for mobile commerce adoption and usage. Findings: Except for gender, perceived ease of use, and subjective norms that did not have specific effects on mobile commerce adoption, age, educational level, perceived usefulness, expertise, attitude, and behavioral intention showed significant effects. Recommendations for Practitioners: First of all, mobile commerce service providers should strategically pay critical attention to customer-centered factors that positively affect the adoption of mobile commerce innovations than focusing exclusively on technology-related issues. Mobile service providers can attract more users if they carefully consider promoting elements like perceived usefulness and perceived ease of use which directly or indirectly affect the individuals’ decision to adopt information technology from consumer perspectives. Second, mobile commerce service providers should strategically focus more on younger individuals since, per the research findings, they are more likely to adopt mobile commerce innovations than the older folks in Ghana. Third, service providers should also devise strategies to retain actual users of m-commerce by promoting elements like behavioral intentions and attitude, which according to the research findings, have a higher predictive power on actual usage of m-commerce. Recommendation for Researchers: The conceptual model developed can be employed by researchers worldwide to analyze technology acceptance research. Impact on Society: The study’s findings suggested that mobile commerce adoption could promote a cashless society that is convenient for making buying things quicker and easier. Future Research: The research sample size could be increased, and also the study could all sixteen regions in Ghana or any other country for a broader representation. http://www.informingscience.org/Publications/4921 mobile commerce attitude artisans behavioral intention adoption actual use eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-04-28 17 125 149 4948 article Saad Alaklabi salaklabi@su.edu.sa Kyeong Kang kyeong.kang@uts.edu.au Aim/Purpose: The aim of this study was to explore the factors driving individuals’ behavioral intention to use cryptocurrency in Saudi Arabia using the extended TRA model. Background: Despite the great potential of cryptocurrencies and the exponential growth of cryptocurrency use throughout the world, scholarly research on this topic remained scarce. Whereas prior studies are mostly done in developed countries or specific cultural contexts, limiting the generalizability of their results, they mainly used technology adoption models that cannot fully explain the acceptance of new technology involved with financial transactions such as cryptocurrency and provided contradictory evidence. Entire regions have been excluded from the research on this topic, including Saudi Arabia which has a high potential to increase the volume of cryptocurrency use. Methodology: This study extends the theory of reasoned action (TRA) with the factors from technology adoption models that proved relevant for this topic, namely perceived usefulness, perceived enjoyment, perceived innovativeness, and perceived risk with three sub-factors: security, financial, and privacy risk. Data are collected using a quantitative research methodology from 181 respondents residing in Saudi Arabia and then analyzed by several methods, including exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and structural equation modeling (SEM). Contribution: This study contributes to the scientific knowledge by extending the TRA model with a range of factors from the technology adoption field, thus enabling the analysis of this topic from human, financial, and technology perspectives and providing additional empirical evidence on the factors that previously either provided contradictory evidence or were not explored in this field. This research also provides the first empirical data on this topic in Saudi Arabia and enables further research on the topic and a comparison of the results. The study also contributes to practice by enhancing the actual understanding of the phenomena and providing valuable information and recommendations for governments, investors, merchants, developers, and the general population. Findings: The study found attitude, subjective norm, perceived usefulness, perceived enjoyment, personal innovativeness, privacy risk, and financial risk as significant predictors of the intention to use cryptocurrencies, whereas the influence of security risk was not found to be significant in Saudi Arabia. Recommendations for Practitioners: Using this study’s results, governments can create appropriate legal frameworks, developers can design fewer complex platforms, and merchants may create appropriate campaigns that emphasize the benefits of cryptocurrency use and transpire trust in cryptocurrency transactions by enhancing the factors with a positive impact, such as usefulness, enjoyment, and personal innovativeness while reducing concerns of potential users regarding the risky factors. By promoting a positive user experience, they can also improve attitudes and social norms towards cryptocurrencies, thus further stimulating the interest in their use. Recommendation for Researchers: As this study validated the influence of factors from technology, financial, and human-related fields, researchers may follow this approach to ensure a comprehensive analysis of this complex topic, especially as privacy risk was never examined in this context, while personal innovativeness, perceived enjoyment, financial, and security risk were explored in just a few studies. It is also recommended that researchers explore the impact of each part of subjective norms: social media, friends, and family, as well as how information on the benefits of cryptocurrencies affects the perception of the factors included. Impact on Society: Understanding the factors affecting cryptocurrency use can help utilize the full potential of cryptocurrencies, especially their benefits for developing countries reflected in safe, speedy, and low-cost financial transactions with no need for an intermediary. The research model of this study could also be used to investigate this topic in other contexts to discover similarities and differences, as well as to investigate other information systems. Future Research: Future studies should test this research model in similar and different contexts to determine whether its validity and study results depend on cultural and contextual factors. They can also include different or additional variables, or use mixed methods, as interviews would augment the comprehension of this topic. Future studies may also explore whether the impact of variables would remain the same if circumstances changed or use cases expanded, and how the preferences of the target population would change within a longitudinal time frame. http://www.informingscience.org/Publications/4948 cryptocurrency TRA model behavioral intention to use cryptocurrency Saudi Arabia eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-05-01 17 151 190 4954 article Nkosikhona T Msweli nkosikhona.msweli@gmail.com Hossana Twinomurinzi twinoh@gmail.com Mymoena Ismail (was Sharif) mymoena_ismail@icloud.com Aim/Purpose: Systematic literature reviews seek to locate all studies that contain material of relevance to a research question and to synthesize the relevant outcomes of those studies. The primary aim of this paper was to synthesize both research and practice reports on micro-credentials (MCRs). Background: There has been an increase in reports and research on the plausibility of MCRs to support dynamic human skills development for an increasingly impatient and rapidly changing digital world. The integration of fast-paced emerging technologies and digitalization necessitate alternative learning paradigms. MCRs offer time, financial, and space flexibility and can be stacked into a larger qualification, thereby allowing for a broader range of transdisciplinary competencies within a qualification. However, MCRs often lack the academic rigor required for accreditation within existing disciplines. Methodology: The study followed the PRISMA framework (Preferred Reporting Items for Systematic Reviews and Meta Analyses), which offers a rigorous method to enhance reporting quality. The study used both academic research and practice reports. Contribution: The paper makes a theoretical contribution to the discourse about the need for innovation within existing educational paradigms for continued relevance in a changing world. It also contributes to the debate on the role of MCRs in bridging the gap between practice and academia despite the growing difference between their interests, and the role that MCRs play in the social-economic plans of countries. Findings: The key findings are that investments in MCRs are mainly in the Science, Technology, Engineering and Mathematics (STEM) and Education sectors, and have taken place mainly in high-income countries and regions – contexts that particularly value practice-accredited MCRs. Low-income countries, by contrast, remain traditional and insist on MCRs that are formally accredited by a recognized academic institution. This contributes to a widening skills gap between low- and high-income countries or regions, which results in greater global disparities. There is also a growing divide between academia and practice concerning their interest in MCRs (a reflection of the rigor versus relevance debate), which partially explains why many global and larger organizations have gone on to create their own learning institutions. Recommendations for Practitioners: We recommend that educational mechanisms consider the critical importance of MCRs as part of innovative efforts for life-wide (different sectors) and life-long (same sector) learning, especially in low-income countries. MCRs provide dynamic mechanisms to fill skills gaps in an increasing ruthless international battle for talent. Recommendation for Researchers: We recommend focused research into skills and career pathways using MCRs while at the same time remaining responsive to transdisciplinary efforts and sensitive to global and local changes within any sector. Impact on Society: Work and society have transformed over time, and more so in the new digital age, yet academia has been slow in adapting to the changes, forcing organizations to create their own learning institutions or to use MCRs to fill the skills gap. The purpose of education goes beyond preparing individuals for work, extending further to creating an environment where individuals and governments seek their own social and economic outcomes. MCRs provide a flexible means for co-creation between individuals, education, organizations, and government that could stem global rising unemployment, social exclusion, and redundancy. Future Research: Future research should focus on the co-creation of MCRs between practitioners and academia. http://www.informingscience.org/Publications/4954 micro-credentials digital badges online learning credentials education 4.0 COVID-19 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-05-20 17 191 214 4947 article Raphael W Jankeeparsad raphaeljanks@gmail.com Devi Datt Tewari davetewari@gmail.com Aim/Purpose: This paper identified and explored the factors influencing Bitcoin adoption and use in South Africa. Background: Since its introduction in 2008, the value and popularity of Bitcoin has risen exponentially. Captivating the eyes of the world, from regulators to economists, Bitcoin promises to revolutionize the digital currency space. Despite being over 10 years old, the concept of cryptocurrency is fairly new in South Africa, a developing country. South African’s interest in Bitcoin continues to grow with the country constantly ranking within the top 10 in online searches for “Bitcoin” and “cryptocurrency” on Google. The primary objective of this research was to identify adoption factors amongst South African citizens, an area that has not received much research focus in the past. In addition to this, the study aimed to identify how Bitcoin is primarily used in South Africa. Methodology: A survey-based questionnaire was utilized to obtain responses from adopters of Bitcoin in South Africa. The quantitative survey was completed by 204 respondents. Contribution: This research contributes to the body of knowledge relating to Bitcoin adoption, specifically from a developing country. Adoption factors are identified that can be utilized by businesses that intend to adopt cryptocurrency, to strategically prepare for the potential risks or opportunities brought about by Bitcoin and cryptocurrency in general. Findings: The findings of this study indicate that while perceived usefulness, perceived ease of use, subjective norms, and facilitating conditions positively influence intention to adopt Bitcoin, trust was the only construct that is statistically significant and hence is the greatest driver of adoption in South Africa. In terms of its primary use in South Africa, the study revealed that Bitcoin is used as a speculative instrument for short-term trading in South Africa followed by being used as a long-term investment in the crypto-asset class. No respondent indicated that they utilize Bitcoin as a payment method in South Africa. Recommendations for Practitioners: When developing crypto-based investment products, custodians of assets must ensure that a minimum-security protocol is followed to safeguard these assets. This will enhance the trust that potential investors and customers have in their systems and products. Recommendation for Researchers: This study focused on adoption factors for South African citizens. Future studies should be conducted to identify adoption factors by businesses in South Africa. Impact on Society: Bitcoin offers an alternate trading instrument and investment option, with the possibility of large gains over a relatively short period. Bitcoin also presents the possibility of cross-border transactions at a significantly lower cost compared to traditional cross-border transfers of funds. Future Research: Studies should be conducted to explore the factors influencing the adoption of altcoins to determine if the technological differences influence the adoption of one currency over the other. Research should also be conducted comparing the taxation of cryptocurrency in various countries around the world. http://www.informingscience.org/Publications/4947 Bitcoin cryptocurrency South Africa eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-05-26 17 215 234 4979 article Anam Aslam anamaslam20@gmail.com Aamir Aslam aamiraslamr@gmail.com Sunayana Kumar aanam4155@gmail.com Aim/Purpose: The present study examines the effect of perceived organisational and co-worker support on the adjustment of repatriates and its impact on their intention to transfer knowledge in multinational companies (MNCs). It also examines the relationship between perceived organisational support, co-worker support, and knowledge transfer through the mediating role of repatriate adjustment. Background: The ability of acquiring and utilising international knowledge is one of the core competitive advantages of MNCs. This knowledge is transferred by MNCs across their subsidiaries efficiently through repatriates, which will result in superior performance when compared to their local competitors. But in MNCs the expatriation process has been given more emphasis than the repatriation process; therefore, there is limited knowledge about repatriation knowledge transfer. Practically, the knowledge transferred by repatriates is not managed properly by the MNCs. Methodology: The proposed model was supported by Uncertainty Reduction Theory, Organisational Socialisation Theory, Organisational Support Theory, and Socialisation Resource Theory. The data were gathered from 246 repatriates working in Indian MNCs in the manufacturing and information technology sectors who had been on an international assignment for at least one year. The data obtained were analysed using Structural Equation Modeling (SEM) using AMOS 21 software. Contribution: The present study expands prior research on repatriate knowledge transfer by empirically investigating the mediating role of repatriate adjustment between perceived support and repatriate knowledge transfer in MNCs. The present study also highlights that organisational and co-worker support during repatriation is beneficial for repatriate knowledge transfer. It is important that MNCs initiate support practices during repatriation to motivate repatriates to transfer international knowledge. Findings: The results revealed that both perceived organisational and co-worker support had a significant role in predicting repatriate adjustment in MNCs. Furthermore, the results also revealed that perceived organisational and co-worker support increases repatriate knowledge transfer through repatriate adjustment in MNCs. Recommendations for Practitioners: This study indicates the role of management in motivating repatriates to transfer their knowledge to the organisation. The management of MNCs develop HR policies and strategies leading to high perceived organisational support, co-worker support, and repatriate adjustment. They need to pay particular attention to the factors that affect the repatriates’ intention to share knowledge with others in the organisation. Recommendation for Researchers: Researchers can use the validated measurement instrument which could be essential for the advancement of future empirical research on repatriate knowledge transfer. Impact on Society: The present study will assist MNCs in managing their repatriates during the repatriation process by developing an appropriate repatriation support system. This will help the repatriates to better adjust to their repatriation process which will motivate them to transfer the acquired knowledge. Future Research: Future research can adopt a longitudinal style to test the different levels of the adjustment process which will help in better understanding the repatriate adjustment process. Additionally, this model can be tested with the repatriates of other countries and in diverse cultures to confirm its external validity. Furthermore, future research can be done with the repatriates who go on an international assignment through their own initiative (self-initiated expatriates). http://www.informingscience.org/Publications/4979 repatriates repatriate adjustment co-worker support organisational support repatriate knowledge transfer structural equation modelling eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-06-03 17 235 258 4972 article Nasruddin Hassan nas@ukm.edu.my Mazlan Hassan mazlanhs@upm.edu.my Haslinda Hashim haslinda@upm.edu.my Zeti Suzila Mat Jusoh ztysuzila@gmail.com Aim/Purpose: This research aims to analyze the effect of human resource management on humanitarian operations performance, using humanitarian organizations in Malaysia as a case. Background: Humanitarian organizations need to develop and continue effective on-the-job human resource management, such as training and development and managing employee performance to enhance the performance of their humanitarian operations. Methodology: The sampling technique that was conducted is probability sampling. In particular, the technique is called stratified sampling. This technique is chosen because it is involving the division of a population into a smaller group, called “strata”. The questionnaire survey was distributed to humanitarian organizations in Malaysia to collect research data, and PLS-SEM analysis was conducted to validate the conceptual model. Contribution: This research focuses on the effect of human resource management on humanitarian operations performance in humanitarian organizations with consistent training to ensure successful humanitarian operations. Findings: The results of PLS-SEM analysis confirmed that Training and Employee Development, Recruitment and Employee Selection, and Communicative Management Style are significantly correlated with humanitarian operations performance, giving 75.7% variations which means that these human resource management are critical factors for increasing humanitarian operations performance in Malaysian humanitarian organizations. Recommendations for Practitioners: This research will enhance humanitarian operations performance for humanitarian organizations, in-line policies outlined under the Malaysia National Security Council Directive No. 20, and benefit the field of disaster management. Recommendation for Researchers: This research can be used by the authorized individual involved in humanitarian operations to satisfy the needs of the victims, which ultimately contributes to the performance of these humanitarian organizations. Impact on Society: This research highlighted the human resource management that is vital for humanitarian organizations, which will increase humanitarian operations performance in an organization. Future Research: This study is conducted in the context of humanitarian organizations in Malaysia. It is unclear whether the key findings of this study can be generalized. Therefore, it is suggested that, in future research, the current research model should be extended to include different countries for validation. http://www.informingscience.org/Publications/4972 PLS-SEM humanitarian operations performance human resource management humanitarian organizations eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-06-06 17 259 285 4971 article Heba Alhajjaj heb20188105@std.psut.edu.jo Alaeddin Mohammad Khalaf Ahmad a.ahmed@psut.edu.jo Aim/Purpose: This study aimed to explore the impact of environmental drivers and trust on consumers’ adoption of Fintech services in the Jordanian context. It had also evaluated the mediating role of trust on the relation between environmental drivers and consumers adoption of Fintech services. Background: The reviewed studies on Fintech adoption demonstrated a lack of focus on the role of external or environmental drivers on consumers’ intentions to use and continue to use of Fintech services. Amongst the analyzed studies, the majority had examined the role of consumers perception of services usefulness and ease of use while few had included some environmental variables within the investigated variables such as social influence and government support. Furthermore, shortage of Fintech adoption related research in the developing countries, especially the Jordanian context was noted. Methodology: The study conceptual model was derived from Social Cognitive Theory (SCT) and Technological Personal Environmental (TPE) framework. This study was a quantitative one that employed survey method to empirically address its research questions and test the proposed hypotheses. Jordanian residents over the age of 18 who are familiar with Fintech were targeted, and convenience sampling was applied to get representative sample. Data was assembled from 323 respondents using an online questionnaire. Partial Least Squares Structure Equation Modeling (PLS-SEM) was applied to analyze the gathered data through SMART-PLS software. Contribution: This article adds to the existing literature on multiple stands, as it adds to literature related to Fintech adoption, as well as the interaction between consumer environment and their level of adoption. It also enriches the limited literature on the influence of COVID-19 to drive consumer usage of innovative services. Moreover, it supplements the scarce literature on Fintech adoption in the Jordanian settings. Findings: The main findings revealed the positive influence of both environmental drivers and trust as predictors of consumer intention to use Fintech services. It had also asserted the positive mediating effect of trust on the relationship amongst environmental drivers and consumer usage intent. Recommendations for Practitioners: By understanding the importance of consumer environment and trust on encouraging consumer to adopt Fintech services, governments, policy makers and practitioners can utilize this knowledge to adopt their offered services. They need to work on enhancing the technological infrastructure, as well as establishing general technological knowledge. They also need to highlight the role of Fintech service in fighting Covid-19, by adhering to the social distancing rules. Moreover, they need to guarantee the security and reliability of the developed services to increase their level of trust in the offered services. Recommendation for Researchers: This research has confirmed the positive influence of consumer environment represented by social influence, government support, technological readiness, and COVID-19 on their adoption of Fintech services. It has also established the mediating influence of consumer trust on the relation between environmental drivers and consumer intent to use Fintech services. This area is unexplored and needs more validation. Impact on Society: By understanding the factors affecting the Jordanian society in adopting Fintech services, this research provides set of recommendation to the Jordanian government and policy makers that can lead for more adoption of the developed Fintech services, which in turn would lead to better services provided to the society as well as increasing the financial inclusion level in the Jordanian society. Future Research: Future research can explore other environmental variables that were not included in the current research. Future research can also investigate the moderating effect of personal attributes such as consumer’s demographics, or more personal attributes such as self-efficacy, inherit innovativeness or risk aversion. It can also examine the moderating effect of financial literacy and/ or technological background. http://www.informingscience.org/Publications/4971 environmental drivers Fintech adoption Jordan COVID-19 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-06-25 17 287 313 4981 article Isaac Asampana isaac.asampana@upsamail.edu.gh Albert Akanlisikum Akanferi albert.akanferi@upsamail.edu.gh Hannah Ayaba Tanye hannah.tanye@upsamail.edu.gh Akwetey Henry Matey hmateyakwetey@upsamail.edu.gh Aim/Purpose: Mobile commerce adoption is low in developing countries; hence, public servants may not consider mobile commerce and mobile payments. Understanding the factors that influence mobile commerce and mobile payments in their context will aid in promoting those services. Background: The study investigates the factors that influence public servants’ mobile commerce and mobile payments in Ghana. Hence, it provides some understanding of the various aspects of mobile commerce and mobile payments adoption, such as acceptance, use, and eventual adoption into the user’s daily life, and how that affects their behaviour. Methodology: The research was conducted by surveying the factors influencing public servants’ adoption of mobile commerce and payments in Ghana. A cross-sectional survey was undertaken to put the research model to the test to measure the constructs and their relationships. Contribution: The study confirmed previous findings and created a new conceptual model for mobile commerce and mobile payment adoption and usage in the Ghanaian context. Findings: The variables of performance expectancy, trust, and facilitating conditions have a significant positive influence on behavioural intention. The factors of effort expectation and social influence have a significant negative impact. Price value and perceived reliability are latent variables that do not affect behavioural intention. Behavioural intention and facilitating conditions significantly influence the actual use behaviour of mobile commerce and mobile payment users. Recommendations for Practitioners: Mobile commerce is emerging as a new mode of transactions, with firms providing enabling platforms for users. Mobile commerce could become the most acceptable application for the next generation of mobile platform applications. This study offers insights into the fluidity of the mobile environment, with implications that spell out what will be effective mobile commerce services that will continue to be relevant. Mobile applications are attractive to people because they provide a better user experience. These mobile applications have been optimised to provide a fast, easy and delightful experience. Mobile commerce and mobile payment service providers can attract and retain more users if attention is paid to performance expectancy, trust, and facilitating conditions since they influence individuals’ decisions to adopt. Mobile technology is almost ubiquitous, influencing both online sales and in-store sales. With the right mobile commerce platform and features, businesses can expect to increase in-store and online sales, catering to a more extensive clientele. Mobile devices are the primary means that most customers use to look up information about products they see in stores, such as product reviews and pricing options. This study indicates that mobile commerce service providers can achieve a more extensive customer base by promoting performance expectancy, trust, and behavioural intentions. Recommendation for Researchers: Despite the numerous studies in the mobile commerce literature, few have used integrated models of perceived reliability, trust, and price value or methods to evaluate these factors in the emerging mobile commerce industry. Also, it combines mobile commerce and mobile payments, which very few that we know of have done. Impact on Society: Ghana is already in a cash-lite economy. Thus, the study is appropriate with the result of trust being a significant factor. It implies that people will begin using mobile commerce and mobile payments with a bit of drive to bring about this drive quickly. Future Research: Future research could further test the adapted model with moderating factors of age, gender, and education to delve deeper into the complexities of mobile commerce and mobile payments. http://www.informingscience.org/Publications/4981 mobile commerce Ghanaian public servants trust behavioural intention adoption eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-06-25 17 315 338 4984 article Ashraf Ahmed Fadelelmoula asahfaab@gmail.com Aim/Purpose: This study aims to examine the roles of key traits of m-university services and their users in promoting two crucial post-adoption outcomes of these services; namely, continuance usage intention and perceived value. Background: M-university (i.e., a university providing services via mobile technologies) has gained a great interest in the higher education sector as a driver of new business models and innovative service offerings. However, its assessment has been greatly overlooked, especially in evaluating the factors that drive the stakeholders’ continuance intention to use it and the determinants of its post-adoption perceived value. Consequently, research efforts undertaking such assessment facets empirically are highly required. Methodology: An integrated research model that enables such assessment was developed and evaluated using a quantitative research methodology. Accordingly, data were collected using a formulated closed-ended survey questionnaire. The target population consisted of the academic staff of a Saudi public university that has witnessed an extensive adoption of m-university services. The obtained data (i.e., 207 fully completed responses) were evaluated using the structural equation modeling approach. Contribution: To the best of our knowledge, this is the first study that gains the chance to provide the research community and m-service providers with new knowledge and understanding about the predictors that drive the continuance usage intention and value of m-university services. Findings: The findings showed that all of the examined traits of m-university services and their users (i.e., reliability, usability, customization, self-efficacy, and involvement) are having positive roles in promoting the continuance intention to use these services, while only two traits (i.e., reliability and involvement) contribute significantly to augmenting the perceived value. Recommendations for Practitioners: The study recommends developing effective design and implementation specifications that strengthen the contributions of the examined traits in the post-adoption stage of m-university services. Recommendation for Researchers: Further studies should be devoted to addressing the notable need to assess the factors influencing the adoption of m-university services, as well as to explore which ones are having significant roles in the attainment of post-adoption outcomes. Impact on Society: The empirical insights provided by the present study are essential for both university stakeholders and mobile service providers in their endeavors to improve the key aspects of the anticipated post-adoption outcomes of the provided services. Future Research: Further empirical investigations are needed to examine the roles of more m-university services and user traits in achieving a broad range of post-adoption outcomes of such services. http://www.informingscience.org/Publications/4984 m-university faculty-oriented m-university services m-university service trait user trait continuance usage intention perceived value eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-07-04 17 339 359 4994 article Dmaithan Abdelkarim Almajali almjalidmaithan@yahoo.com Aim/Purpose: This study identifies the elements that influence intentions to purchase from the most popular Arabic online classifieds platform, OpenSooq.com. Background: Online purchasing has become popular among consumers in the past two decades, with perceived risk and trust playing key roles in consumers’ intention to purchase online. Methodology: A questionnaire survey was conducted of Internet users from three Jordanian districts to investigate how they used the OpenSooq platform in their e-commerce activities. In total, 202 usable responses were collected, and the data were analyzed with PLS-SEM for hypothesis testing and model validation. Contribution: Though online trading is increasingly popular, the factors that impact the behavior of consumers when purchasing high-value products have not been adequately investigated. Therefore, this study examined the factors affecting perceived risk, and the potential impact of privacy concerns on the perceived risk of online smartphone buyers. The study framework can help explore online behavior in various situations to ascertain similarities and differences and probe other aspects of online buying. Findings: Perceived risk negatively correlates with online purchasing behavior and trust. However, privacy concern and perceived risk, transaction security and trust, and trust and online purchasing behavior exhibited positive correlations. Recommendations for Practitioners: Customers can complete and retain online purchases in a range of settings illuminated in this study’s methods and procedures. Moreover, businesses can manage their IT arrangements to make Internet shopping more convenient and build processes for online shopping that allow for engagement, training, and ease of use, thus improving their customers’ online purchasing behavior. Recommendation for Researchers: Given the insight into the understanding and integration of variables including perceived risk, privacy issues, trust, transaction security, and online purchasing behavior, academics can build on the groundwork of this research paradigm to investigate underdeveloped countries, particularly Jordan, further. Impact on Society: Understanding the characteristics that influence online purchasing behavior can help countries realize the full potential of online shopping, particularly the benefits of safe, fast, and low-cost financial transactions without the need for an intermediary. Future Research: Future research can examine the link between online purchase intent, perceived risk, privacy concerns, trust, and transaction security to see if the findings of this study in Jordan can be applied to a broader context in other countries. http://www.informingscience.org/Publications/4994 online purchasing trust transaction security perceived risk privacy concern eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-07-26 17 361 385 5003 article Zaenal Akbar zaenal.akbar@lipi.go.id Dadan Ridwan Saleh dadan.ridwan.saleh@lipi.go.id Yulia Aris Kartika yulia.aris.kartika@lipi.go.id Widya Fatriasari widya.fatriasari@biomaterial.lipi.go.id Adila A Krisnadhi adila@cs.ui.ac.id Deded Sarip Nawawi dsnawawi@apps.ipb.ac.id Aim/Purpose: Although the significance of data provenance has been recognized in a variety of sectors, there is currently no standardized technique or approach for gathering data provenance. The present automated technique mostly employs workflow-based strategies. Unfortunately, the majority of current information systems do not embrace the strategy, particularly biodiversity information systems in which data is acquired by a variety of persons using a wide range of equipment, tools, and protocols. Background: This article presents an automated technique for producing temporal data provenance that is independent of biodiversity information systems. The approach is dependent on the changes in contextual information of data items. By mapping the modifications to a schema, a standardized representation of data provenance may be created. Consequently, temporal information may be automatically inferred. Methodology: The research methodology consists of three main activities: database event detection, event-schema mapping, and temporal information inference. First, a list of events will be detected from databases. After that, the detected events will be mapped to an ontology, so a common representation of data provenance will be obtained. Based on the derived data provenance, rule-based reasoning will be automatically used to infer temporal information. Consequently, a temporal provenance will be produced. Contribution: This paper provides a new method for generating data provenance automatically without interfering with the existing biodiversity information system. In addition to this, it does not mandate that any information system adheres to any particular form. Ontology and the rule-based system as the core components of the solution have been confirmed to be highly valuable in biodiversity science. Findings: Detaching the solution from any biodiversity information system provides scalability in the implementation. Based on the evaluation of a typical biodiversity information system for species traits of plants, a high number of temporal information can be generated to the highest degree possible. Using rules to encode different types of knowledge provides high flexibility to generate temporal information, enabling different temporal-based analyses and reasoning. Recommendations for Practitioners: The strategy is based on the contextual information of data items, yet most information systems simply save the most recent ones. As a result, in order for the solution to function properly, database snapshots must be stored on a frequent basis. Furthermore, a more practical technique for recording changes in contextual information would be preferable. Recommendation for Researchers: The capability to uniformly represent events using a schema has paved the way for automatic inference of temporal information. Therefore, a richer representation of temporal information should be investigated further. Also, this work demonstrates that rule-based inference provides flexibility to encode different types of knowledge from experts. Consequently, a variety of temporal-based data analyses and reasoning can be performed. Therefore, it will be better to investigate multiple domain-oriented knowledge using the solution. Impact on Society: Using a typical information system to store and manage biodiversity data has not prohibited us from generating data provenance. Since there is no restriction on the type of information system, our solution has a high potential to be widely adopted. Future Research: The data analysis of this work was limited to species traits data. However, there are other types of biodiversity data, including genetic composition, species population, and community composition. In the future, this work will be expanded to cover all those types of biodiversity data. The ultimate goal is to have a standard methodology or strategy for collecting provenance from any biodiversity data regardless of how the data was stored or managed. http://www.informingscience.org/Publications/5003 temporal data provenance biodiversity ontology rule-based reasoning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-09-18 17 387 411 5015 article Priscilla I Maliwichi pmaliwichi@must.ac.mw Wallace Chigona wallace.chigona@uct.ac.za Aim/Purpose: The aim of the study is to explore factors that affect how healthcare clients in rural areas use infomediaries in maternal mHealth interventions. The study focuses on maternal healthcare clients who do not own mobile phones but use the mHealth intervention. Background: Maternal mHealth interventions in poor-resource settings are bedevilled by inequalities in mobile phone ownership. Clients who do not own mobile phones risk being excluded from benefiting from the interventions. Some maternal mHealth providers facilitate the access of mobile phones for those who do not own them using “infomediaries”. Infomediaries, in this case, refer to individuals who have custody of mobile phones that other potential beneficiaries may use. However, the use of infomediaries to offer access to the “have nots” may be influenced by a number of factors. Methodology: The study uses a case of a maternal mHealth intervention project in Malawi, as well as a qualitative research method and interpretive paradigm. Data was collected using secondary data from the implementing agency, semi-structured interviews, and focus group discussions. Empirical data was collected from maternal healthcare clients who do not own mobile phones and infomediaries. Data were analysed inductively using thematic analysis. Contribution: The study proposed a theoretical framework for studying infomediaries in ICT4D. The study may inform mHealth designers, implementers, and policymakers on how infomediaries could be implemented in a rural setting. Consequently, understanding the factors that affect the use of infomediaries may inform mHealth intervention implementers on how they could overcome the challenges by implementing mHealth interventions that reduce the challenges on the mHealth infomediaries side, and the maternal healthcare clients’ side. Findings: Characteristics of the maternal healthcare client, characteristics of the mHealth infomediary, perceived value of mHealth intervention, and socio-environmental factors affect maternal healthcare clients’ use of mHealth infomediaries. Recommendations for Practitioners: Implementers of interventions ought to manage the use of infomediaries to avoid volunteer fatigue and infomediaries who may not be compatible with the potential users of the intervention. Implementers could leverage traditional systems of identifying and using infomediaries instead of reinventing the wheel. Recommendation for Researchers: This research adopted a single case study to develop the theoretical framework for mHealth infomediary use. We recommend future studies are conducted in order to test and develop this framework further, not only in ICT4D, but also in other areas of application. Impact on Society: People still lack access. The lack of ownership of technology may still exclude them from participating in an information society. The use of infomediaries may help to provide access to technologies to those who do not have them thereby bridging the digital divide gap. Future Research: We propose herein that traditional systems may offer a good starting point for designing a system that would work for communities. We, therefore, recommend that future research may explore these possibilities. http://www.informingscience.org/Publications/5015 infomediaries mHealth maternal mHealth interventions volunteers eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-09-18 17 413 442 5019 article Dr. Khai Wah Khaw khaiwah@usm.my Ali Shakir Zaidan sha3883@student.usm.my Alhamzah Alnoor alhamzah.malik@stu.edu.iq Aim/Purpose: This study examines the impact of decision-making, crisis management, and decision-making on sustainability through the mediation of open innovation in the energy sector. Background: Public companies study high-performance practices, requiring overcoming basic obstacles such as financial crises that prevent the adoption and development of sustainability programs. Methodology: Due to the COVID-19 pandemic, which has led to the closure of businesses in Iraq, a survey was distributed. To facilitate responses, free consultations were offered to help complete the questionnaire quickly. Of the 435 questionnaires answered, 397 were used for further analysis. Contribution: The impact of crises that impede the energy sector from adopting sustainable environmental regulations is investigated in this study. Its identification of specific constraints to open innovation leads to the effectiveness of adopting environmentally friendly policies and reaching high levels of sustainable performance. Findings: The impacts of risk-taking, crisis management, and decision-making on sustainability have been explored. Results show that open innovation fully mediates the relationship between the factors of risk-taking, crisis management, decision-making, and sustainability. Recommendations for Practitioners: The proposed model can be used by practitioners to develop and improve sustainable innovation practices and achieve superior performance. Recommendation for Researchers: Researchers are recommended to conduct in-depth studies of the phenomenon based on theoretical and empirical foundations, especially in light of the relationship between crisis management, decision-making, and risk-taking and their impact on sustainability based on linear and non-compensatory relationships. Impact on Society: This study provides a reference for organizations with similar cultural backgrounds in adopting sustainable practices to minimize pollution in the Iraqi context. Future Research: A more in-depth study can be performed using a larger sample, which not only includes the energy industry but also other industries. http://www.informingscience.org/Publications/5019 crisis management innovation decision-making environment sustainable performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-09-29 17 443 470 5023 article Ahmad Samed Al-Adwan a.adwan@ammanu.edu.jo Amro Al-Madadha a.almadadha@psut.edu.jo Mohammad Hamdi Al Khasawneh m.alkhasaawneh@psut.edu.jo Ola Al Haddid o.alhaddid@psut.edu.jo Aim/Purpose: Currently, the world faces unprecedented challenges due to COVID-19, particularly concerning individuals’ health and livelihood and organizations and industrial performance. Indeed, the pandemic has caused rapid intensifying socio-economic effects. For instance, organizations are shifting from traditional working patterns toward telecommuting. By adopting remote working, organizations might mitigate the impact of COVID-19 on their workforce, explicitly concerning their safety, wellbeing, mobility, work-life balance, and self-efficiency. From this perceptive, this study examines the factors that influence employees’ behavioral intention to adopt telecommuting in the banking industry. Background: The study’s relevance stems from the fact that telecommuting and its benefits have been assumed rather than demonstrated in the banking sector. However, the pandemic has driven the implementation of remote working, thereby revealing possible advantages of working from home in the banking industry. The study investigated the effect of COVID-19 in driving organizations to shift from traditional working patterns toward telecommuting. Thereby, the study investigates the banking sector employees’ behavioral intention to adopt telecommuting. Methodology: The study employed a survey-based questionnaire, which entails gathering data from employees of twelve banks in Jordan, as the banking sector in Jordan was the first to transform from traditional working to telecommuting. The sample for this research was 675 respondents; convenience sampling was employed as a sampling technique. Subsequently, the data were analyzed with the partial least square structural equation modeling (PLS-SEM) to statistically test the research model. Contribution: Firstly, this study provides a deep examination and understanding of facilitators of telecommuting in a single comprehensive model. Secondly, the study pro-vides a deeper insight into the factors affecting behavioral intention towards telecommuting from the employees’ perspective in the banking sector. Finally, this study is the first to examine telecommuting in the emerging market of Jordan. Thereby, this study provides critical recommendations for managers to facilitate the implementation of telecommuting. Findings: Using the Technology Acceptance Model (TAM), this study highlights significant relationships between telecommuting systems, quality, organizational support, and the perceived usefulness and ease of use in telecommuting. Employees who perceive telecommuting systems to be easy and receive supervision and training for using these systems are likely to adopt this work scheme. The results present critical theoretical and managerial implications regarding employees’ behavioral intentions toward telecommuting. Recommendations for Practitioners: This study suggests the importance of work-life balance for employees when telecommuting. Working from home while managing household duties can create complications for employees, particularly parents. Therefore, flexibility in terms of working hours is needed to increase employees’ acceptance of telecommuting as they will have more control over their life. These increase employees’ perceived self-efficacy with telecommuting, which smooths the transition toward remote working in the future. In addition, training will allow employees to solve technical issues that can arise from using online systems. Recommendation for Researchers: This study focused on the context of the banking sector. The sensitivity of data and transactions in this sector may influence employers’ and employees’ willingness to work remotely. In addition, the job descriptions of employees in banks moderate specific factors outlined in this model, including work-life balance. For instance, executive managers may have a higher overload in banks in contrast to front-line employees. Thus, future studies should explore different contexts, including manufacturing and consultation, to understand the industry’s effect on remote working. Similarly, future research should concentrate on the influence of job descriptions on employees’ intentions toward telecommuting. Impact on Society: The COVID-19 pandemic created a sudden shift towards telecommuting, which made employees struggle to adopt new work schemes. Therefore, managers had to provide training for their employees to be well prepared and increase their acceptance of telecommuting. Furthermore, telecommuting has a positive effect on work-life balance, it provides employees with the flexibility to organize their daily schedule into more activities. Along the same line, the study highlighted the correlation between work-life balance and telecommuting. Such a relationship provides further evidence for the need to understand employees’ lifestyles in facilitating the adoption of telecommuting. Moreover, the study extends the stream of literature by outlining critical factors affecting employees’ acceptance of telecommuting. Future Research: Future studies should explore different contexts, including manufacturing and consultation, to understand the industry’s effect on remote working. Similarly, future research should concentrate on the influence of job descriptions on employees’ intentions toward telecommuting. Furthermore, the research team conducted the study by surveying 12 banks. Future research recommends surveying the whole banking industry to add more validation to the model. http://www.informingscience.org/Publications/5023 telecommuting Technology Acceptance Model (TAM) employee’s self-efficacy behavioral intentions banking eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-10-03 17 471 496 5021 article Chin Wei Chong cwchong@mmu.edu.my Audrey Poh Choo Cheak pccheak@mmu.edu.my Yee Yen Yuen yyyuen@mmu.edu.my Irene Yoke Chu Leong irene@uitm.edu.my Aim/Purpose: This study examined the relationship between critical success factors (CSFs), perceived benefits, and usage intention of Mobile Knowledge Management Systems (MKMS) via an integrated Technology Acceptance Model (TAM) and Information Systems Success Model (ISSM). Background: This study investigates the CSFs (i.e., Strategic Leadership, Employee Training, System Quality, and Information Quality) that impact the usage intention of KMS in mobile contexts which have been neglected. Since users normally consider the usefulness belief in a system before usage, this study examines the role of perceived benefits as a mediator between the CSFs and usage intention. Methodology: A survey-based research approach in the Malaysian semiconductor industry was employed via an integrated model of TAM and ISSM. At a response rate of 59.52%, the findings of this study were based on 375 usable responses. The data collected was analyzed using the Partial Least Squares with SmartPLS 3.0. Contribution: This study contributes to the body of knowledge in the areas of mobile technology acceptance and knowledge management. Specifically, it helps to validate the integrated model of TAM and ISSM with the CSFs from knowledge management and information system. In addition, it provides the would-be adopters of MKMS with valuable guidelines and insights to consider before embarking on the adoption stage. Findings: The findings suggest that Employee Training and Information Quality have a positive significant relationship with Perceived MKMS Benefits. On the contrary, Strategic Leadership, System Quality, and Perceived User-friendliness showed an insignificant relationship with Perceived MKMS Benefits. Additionally, Employee Training and Information Quality have an indirect relationship with MKMS Usage Intention which is mediated by Perceived MKMS Benefits. Recommendations for Practitioners: The findings are valuable for managers, engineers, KM practitioners, KM consultants, MKMS developers, and mobile device producers to enhance MKMS usage intention. Recommendation for Researchers: Researchers would be able to conduct more inter-disciplinary studies to better understand the relevant issues concerning both fields – knowledge management and mobile computing disciplines. Additionally, the mediation effect of TAM via Perceived Usefulness (i.e., perceived MKMS benefits) on usage intention of MKMS should be further investigated with other CSFs. Future Research: Future studies could perhaps include other critical factors from both KM and IS as part of the external variables. Furthermore, Perceived Ease of Use (i.e., Perceived User-friendly) should be tested as a mediator in the future, together with Perceived Usefulness (i.e., perceived MKMS Benefits) to compare which would be a more powerful predictor of usage intention. Moreover, it may prove interesting to find out how the research framework would fit into other industries to verify the findings of this study for better accuracy and generalizability. http://www.informingscience.org/Publications/5021 Technology Acceptance Model Information Systems Success Model mobile knowledge management systems strategic leadership employee training system quality information quality perceived benefits perceived user-friendly usage intention eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-10-04 17 497 521 5022 article Shehu Malami SarkinTudu stjabo@gmail.com Alawiyah Abd Wahab alawiyah@uum.edu.my Huda H Ibrahim huda753@uum.edu.my Aim/Purpose: The aim of this study was to identify the critical predictors affecting project desertion in Blockchain projects. Background: Blockchain is one of the innovations that disrupt a broad range of industries and has attracted the interest of software developers. However, despite being an open-source software (OSS) project, the maintenance of the project ultimately relies on small core developers, and it is still uncertain whether the technology will continue to attract a sufficient number of developers. Methodology: The study utilized a systematic literature review (SLR) and an expert review method. The SLR identified 21 primary studies related to project desertion published in Scopus databases from the year 2010 to 2020. Then, Blockchain experts were asked to rank the importance of the identified predictors of project desertion in Blockchain. Contribution: A theoretical framework was constructed based on Social Cognitive Theory (SCT) constructs; personal, behavior, and environmental predictors and related theories. Findings: The findings indicate that the 12 predictors affecting Blockchain project desertion identified through SLR were important and significant. Recommendations for Practitioners: The framework proposed in this paper can be used by the Blockchain development community as a basis to identify developers who might have the tendency to abandon a Blockchain project. Recommendation for Researchers: The results show that some predictors, such as code testing tasks, contributed code decoupling, system integration and expert heterogeneity that are not covered in the existing developer turnover models can be integrated into future research efforts. Impact on Society: This study highlights how an individual’s design choices could determine the success or failure of IS projects. It could direct Blockchain crypto-currency investors and cyber-security managers to pay attention to the developer’s behavior while ensuring secure investments, especially for crypto-currencies projects. Future Research: Future research may employ additional methods, such as a meta-analysis, to provide a comprehensive picture of the main predictors that can predict project desertion in Blockchain. http://www.informingscience.org/Publications/5022 blockchain project open source software project desertion expert review eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-10-09 17 523 541 5025 article Niko Ibrahim niko.ibrahim@gmail.com Putu Wuri Handayani putu.wuri@cs.ui.ac.id Aim/Purpose: The main goal of this systematic literature review was to look for studies that provide information relevant to business intelligence’s (BI) framework development and implementation in the tourism sector. This paper tries to classify the tourism sectors where BI is implemented, group various BI functionalities, and identify common problems encountered by previous research. Background: There has been an increased need for BI implementation to support decision-making in the tourism sector. Tourism stakeholders such as management of destination, accommodation, transportation, and public administration need a guideline to understand functional requirements before implementation. This paper addresses the problem by comprehensively reviewing the functionalities and issues that need to be considered based on previous business intelligence framework development and implementation in tourism sectors. Methodology: We have conducted a systematic literature review using the Preferred Reporting Items for Systematic Reviews and Guidelines for Meta-Analysis (PRISMA) method. The search is conducted using online academic database platforms, resulting in 543 initial articles published from 2002 to 2022. Contribution: The paper could be of interest to relevant stakeholders in the tourism industry because it provides an overview of the capabilities and limitations of business intelligence for tourism. To our knowledge, this is the first study to identify and classify the BI functionalities needed for tourism sectors and implementation issues related to organizations, people, and technologies that need to be considered. Findings: BI functionalities identified in this study include basic functions such as data analysis, reports, dashboards, data visualization, performance metrics, and key performance indicator, and advanced functions such as predictive analytics, trend indicators, strategic planning tools, profitability analysis, benchmarking, budgeting, and forecasting. When implementing BI, the issues that need to be considered include organizational, people and process, and technological issues. Recommendations for Practitioners: As data is a major issue in BI implementation, tourism stakeholders, especially in developing countries, may need to build a tourism data center or centralized coordination regulated by the government. They can implement basic functions first before implementing more advanced features later. Recommendation for Researchers: We recommend further studying the BI implementation barriers by employing a perspective of an adoption framework such as the technology, organization, and environment (TOE) framework. Impact on Society: This research has a potential impact on improving the tourism industry’s performance by providing insight to stakeholders about what is needed to help them make more accurate decisions using business intelligence. Future Research: Future research may involve collaboration between practitioners and academics in developing various BI architectures specific to each tourism industry, such as destination management, hospitality, or transportation. http://www.informingscience.org/Publications/5025 business intelligence framework functionalities literature review tourism eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-12-03 17 543 575 5032 article Eslam Nazemi nazemi@sbu.ac.ir Ramina Farshadi farshadiramina@gmail.com Neda Abdolvand n.abdolvand@alzahra.ac.ir Aim/Purpose: The aim of this study is to identify Critical Success Factors (CSF) of Business Intelligence (BI) and provide a framework to classify CSF into layers or perspectives using an enterprise architecture approach, then rank CSF within each perspective and evaluate the importance of each perspective at different BI maturity levels as well. Background: Although the implementation of the BI project has a significant impact on creating analytical and competitive capabilities, the lack of evaluation of CSF holistically is still a challenge. Moreover, the BI maturity level of the organization has not been considered in the BI implementation project. Identifying BI critical success factors and their importance can help the project team to move to a higher maturity level in the organization. Methodology: First, a list of distinct CSF is identified through a literature review. Second, a framework is provided for categorizing these CSF using enterprise architecture. Interviewing is the research method used to evaluate the importance of CSF and framework layers with two questionnaires among experts. The first questionnaire was done by Analytical Hierarchy Process (AHP), a quantitative method of decision-making to calculate the weight of the CSF according to the importance of CSF in each of the framework layers. The second one was conducted to evaluate framework layers at different BI maturity levels using a Likert scale. Contribution: This paper contributes to the implementation of BI projects by identifying a comprehensive list of CSF in the form of a holistic multi-layered framework and ranking the importance of CSF and layers at BI maturity levels. Findings: The most important CSF in BI implementation projects include senior management support, process identification, data quality, analytics quality, hardware quality, security standards, scope management, documentation, project team skills, and customer needs transformation, which received the highest scores in framework layers. In addition, it was observed that as the organization moves to higher levels of maturity, the average importance of strategic business and security perspectives or layers increases. But the average importance of data, applications, infrastructure, and network, the project management layers in the proposed framework is the same regardless of the level of business intelligence maturity. Recommendations for Practitioners: The results of this paper can be used by academicians and practitioners to improve BI project implementation through understanding a comprehensive list of CSF and their importance. This awareness causes us to focus on the most important CSF and have better planning to reach higher levels of maturity according to the maturity level of the organization. Future Research: For future research, the interaction of critical success factors of business intelligence and framework layers can be examined with different methods. http://www.informingscience.org/Publications/5032 business intelligence critical success factor maturity model enterprise architecture eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-12-08 17 577 600 5039 article Minna Saunila minna.saunila@lut.fi Sariseelia Sore Sariseelia.Sore@lab.fi Juhani Ukko juhani.ukko@lut.fi Aim/Purpose: This study focuses on the connection between IT-producing firms’ digital service capabilities and the digital service performance of IT-consuming firms, especially online shop operators. Background: The acquisition and integration of knowledge regarding digital service capabilities and performance can increase the level at which employees assimilate information, organize with IT-consuming firms, and cooperate with them to develop the delivery of services and customize services to fill their needs. Exploring capabilities that may enable this process is a prerequisite for all businesses offering digital services and, thus, an engrossing and ongoing interest of practitioners and scholars. However, there is a lack of research on the relationship between IT-producing firms’ digital service capabilities and the digital service performance of IT-consuming firms in the business-to-business (B2B) context. Methodology: The study builds on a survey conducted among small firms that have an online shop in use and are located in Finland. Contribution: The study offers empirical evidence for the capabilities valued by IT-consuming firms, providing a model for IT-producing firms to use when deciding on a future focus. The study was executed in a B2B setting from the viewpoint of online shop operators, presenting a novel understanding of influential digital service capabilities. Findings: Adaptability, determined by capabilities related to utilizing information gained via the integration of a digital product into other digital tools (e.g., marketing, personalization, and analytics), statistically significantly affects all three aspects of an IT-consuming firm’s digital service performance (financial, operational, and sales). Another product capability, availability, which includes aspects such as security, different aspects of functioning, and mobile adaptation, affects one aspect of digital performance, namely operational. The results also suggest that the role of service process-related capabilities in determining service comprehensiveness significantly influences two aspects of IT-consuming firms’ digital service performance: financial (negative effect) and operational (positive effect). The results show that the capabilities associated with the relationship between the producing firm and the consuming firm do not affect IT-consuming firms’ performance to the same extent. Recommendations for Practitioners: The study results suggest that IT-producing firms should concentrate on leveraging service comprehensiveness, as there has been a shift in the B2B context from merely selling a digital product and associated services. It seems that usability-related issues are now taken for granted, and the emphasis is on features that support the use of information to create value. Recommendation for Researchers: The results contribute to the capabilities literature by showing that the shift in focus from technical product-related capabilities to relationship-related capabilities is not yet evident among small online store operators. Impact on Society: In addition to offering tools with different integration possibilities, supporting IT-consuming firms in making the most of the possibilities would be very helpful. Future Research: The comprehension of the relationship between digital service capabilities and digital service performance would benefit from future research that takes into account additional control variables. The theoretical model of this study can be further studied by using other performance measures, such as market performance, as dependent variables. http://www.informingscience.org/Publications/5039 product capabilities service capabilities relationship capabilities digital service performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-12-09 17 601 624 5045 article Lindung Parningotan Manik lind008@brin.go.id Nufri Wilis 14002443@nusamandiri.ac.id Aim/Purpose: This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background: Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology: This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution: This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings: Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations for Practitioners: Fresh and innovative features, such as new game items or themes, should be frequently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendation for Researchers: Visual appeal in this study did not influence the perceived ease of use or usefulness. However, it could affect enjoyment. Thus, it would be worth revisiting the relationship between visual appeal and enjoyment. At the same time, perceived ease of use is a strong driver for the continued use of most online games, but not in this study. It could indicate significant differences between mobile esports and typical online games, one of which is the different purposes. Users might play online games for recreational intention, but players would use mobile esports to compete, win, or even get monetary rewards. Therefore, although users might find mobile esports challenging and hard to use, they tend to keep playing it. Thus, monetary rewards could be considered a determinant of the continuation of use. Impact on Society: Nowadays, users are being paid for playing games. It also would be an excel-lent job if they become professional esports athletes. This study investigated factors that could affect the continued use of mobile esports. Like other jobs, playing games professionally in the long term could make the players tedious and tired. Therefore, responsible parties, like mobile esports providers or governments, could use the recommendations of this study to promote positive behavior among the players. They will not feel like working and still con-sider playing mobile esports a hobby if they happily do the job. In the long run, the players could also make a nation’s society proud if they can be a champion in prestigious competitions. Future Research: A larger sample size will be needed to generalize the results, such as for a nation. It is also preferable if the sample is randomized systematically. Future works should also investigate whether the same results are acquired in other mobile esports. Furthermore, to extend our knowledge and deepen our understanding of the variables that influence mobile esports adoption, the subsequent research could look at other mobile esports acceptability based on characteristics of system functionality and moderator effects. Finally, longitudinal data-collecting approaches are suggested for future studies since behavior can change over time. http://www.informingscience.org/Publications/5045 esports technology acceptance model mobile eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-12-09 17 625 643 5043 article Ayushi Tandon ayushitandon@iima.ac.in Yogini Joglekar yjoglekar@edstutia.com Sabra E. Brock sabraebrock@gmail.com Aim/Purpose: This study examines the impact of transitioning from in-person classrooms to remote online business education and provides analysis of key factors impacting course and instructor ratings as well as strategies for higher education institutions to provide engaging instruction. Background: “Zoom”ing into teaching and moving out of traditional classrooms during the COVID-19 pandemic has been a path full of twists and has impacted student perceptions of courses as well as instructors. One challenge has been to make the quality of synchronous online instruction perceived by students as positive as classroom-delivered ones. Methodology: We analyze primary data collected in the course evaluation process from Business & Accounting students over six semesters between Fall 2019 to Spring 2022, covering pre-pandemic instruction in the classroom and the conversion to virtual instruction via Zoom. A total of 1782 observations for 38 courses were examined using mean comparison, regression and correlation analyses, and pairwise comparisons. Contribution: We provide insights from the evaluation of those instructors who were able to make their Zoom-delivered courses perceived by students as equivalent or better than room-delivered ones. Specifically, clear presentation, stimulating delivery, providing feedback and encouraging discussion were positively correlated with successful online classes. Findings: We find that there is a clear downward shift in course and instructor ratings as the change to synchronous online delivery was made. However, in the Spring of 2022, even though instructors and students were still not completely back in the classroom, both instructor and course ratings moved back closer to the pre-pandemic levels. The parameters associated with instructor ratings, such as providing feedback, clear presentations, stimulating sessions, and encouraging discussion, showed similar downward fluctuations. Also, aspects related to course content were affected by the transition to online modality, including training on critical thinking quantitative analysis, research and writing abilities, and overall usefulness of the content. Moore’s model of Transactional Distance helps explain these changes. Recommendations for Practitioners: We recommend that practitioners allow sufficient time for students and faculty to learn through online instruction delivery and supply training for both populations in adapting to learning in this delivery mode. Recommendation for Researchers: The disruption in higher education caused by COVID-19 has provided a wealth of information on the pluses and minuses of online delivery. Careful inspection of trends can help provide guidance to higher education leaders. Impact on Society: One of the many changes the COVID-19 pandemic brought was the opportunity to try alternate ways of connecting and learning. This study shows how this experience can be used to guide the future of higher education. Future Research: Further research is needed to explore the in-depth reactions of students and faculty to the switch from classroom to online delivery, to explore whether these findings can be more broadly applied to other subjects and other types of universities. http://www.informingscience.org/Publications/5043 online teaching student evaluations teaching and learning eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-01-18 16 .i iv 4689 article Geoffrey Z. Liu Geoffrey.Liu@sjsu.edu Table of Contents for Volume 16, 2021, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/4689 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-01-18 16 001 038 4675 article Anshul Jain anshuljain13@gmail.com Tanya Singh tsingh2@amity.edu Satyendra Kumar Sharma skpacific323@gmail.com Vikas Prajapati vikasprajapati1998@gmail.com Aim/Purpose: 5G and IoT are two path-breaking technologies, and they are like wall and climbers, where IoT as a climber is growing tremendously, taking the support of 5G as a wall. The main challenge that emerges here is to secure the ecosystem created by the collaboration of 5G and IoT, which consists of a network, users, endpoints, devices, and data. Other than underlying and hereditary security issues, they bring many Zero-day vulnerabilities, which always pose a risk. This paper proposes a security solution using network slicing, where each slice serves customers with different problems. Background: 5G and IoT are a combination of technology that will enhance the user experience and add many security issues to existing ones like DDoS, DoS. This paper aims to solve some of these problems by using network slicing and implementing an Intrusion Detection System to identify and isolate the compromised resources. Methodology: This paper proposes a 5G-IoT architecture using network slicing. Research here is an advancement to our previous implementation, a Python-based software divided into five different modules. This paper’s amplification includes induction of security using pattern matching intrusion detection methods and conducting tests in five different scenarios, with 1000 up to 5000 devices in different security modes. This enhancement in security helps differentiate and isolate attacks on IoT endpoints, base stations, and slices. Contribution: Network slicing is a known security technique; we have used it as a platform and developed a solution to host IoT devices with peculiar requirements and enhance their security by identifying intruders. This paper gives a different solution for implementing security while using slicing technology. Findings: The study entails and simulates how the IoT ecosystem can be variedly deployed on 5G networks using network slicing for different types of IoT devices and users. Simulation done in this research proves that the suggested architecture can be successfully implemented on IoT users with peculiar requirements in a network slicing environment. Recommendations for Practitioners: Practitioners can implement this solution in any live or production IoT environment to enhance security. This solution helps them get a cost-effective method for deploying IoT devices on a 5G network, which would otherwise have been an expensive technology to implement. Recommendation for Researchers: Researchers can enhance the simulations by amplifying the different types of IoT devices on varied hardware. They can even perform the simulation on a real network to unearth the actual impact. Impact on Society: This research provides an affordable and modest solution for securing the IoT ecosystem on a 5G network using network slicing technology, which will eventually benefit society as an end-user. This research can be of great assistance to all those working towards implementing security in IoT ecosystems. Future Research: All the configuration and slicing resources allocation done in this research was performed manually; it can be automated to improve accuracy and results. Our future direction will include machine learning techniques to make this application and intrusion detection more intelligent and advanced. This simulation can be combined and performed with smart network devices to obtain more varied results. A proof-of-concept system can be implemented on a real 5G network to amplify the concept further. http://www.informingscience.org/Publications/4675 IoT 5G network slicing 5G security IoT security IoT ecosystem intrusion detection system eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-01-28 16 039 054 4692 article Yahel Giat yahel@jct.ac.il Dan Bouhnik Dan.Bouhnik@biu.ac.il Aim/Purpose: The first goal is to develop a decision support system for pricing and production amounts for a firm facing high levels of product returns. The second goal is to improve the management of the product returns process. Background: This study was conducted at a food importer and manufacturer in Israel facing a very high rate of product returns, much of which is eventually discarded. The firm’s products are commonly considered to be a low-cost generic alternative and are therefore popular among low-income families. Methodology: A decision support module was added to the plant’s business information system. The module is based on a supply chain pricing model and uses the sales data to infer future demand’s distribution. Ergonomic models were used to improve the design of the returns warehouse and the handling of the returns. Contribution: The decision support system allows to improve the plant’s pricing and quantity planning. Consequently, it reduced the size of product returns. The new design of the returns process is expected to improve worker’s productivity, reduces losses and results in safer outcomes. This study also demonstrates a successful integration and of a theoretical economical model into an information system. Findings: The results show the promise of incorporating pricing supply chain models into informing systems to achieve a practical business task. We were able to construct actual demand distributions from the data and offer actual pricing recommendations that reduce the number of returns while increasing potential profits. We were able to identify key deficiencies in the returns operations and added a module to the decisions support system that improves the returns management and links it with the sales and pricing modules. Finally, we produced a better warehouse design that supports efficient and ergonomic product returns handling. Recommendations for Practitioners: This work can be replicated for different suppliers, manufacturers and retailers that suffer from product returns. They will benefit from the reduction in returns, as well as the decrease in the losses associated with these returns. Recommendation for Researchers: It is worthwhile to research whether decision support systems can be applied to other aspects of the organizations’ operations. Impact on Society: Product returns is a lose-lose situation for producers, retailers and customers. Moreover, mismanagement of these returns is harmful for the environment and may result in the case of foods, in health hazards. Reducing returns and improving the handling improves sustainability and is beneficial for society. Future Research: The decision support system’s underlying pricing model assumes a specific business setting. This can be extended using other pricing models and applying them in a similar fashion to the current application. http://www.informingscience.org/Publications/4692 supply chain pricing model Israel food industry product returns decision support system ergonomics eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-02-07 16 055 075 4693 article Ejikeme Emmanuel Isichei isichei_ejike@yahoo.com Adlin Ugo-Agharanya adnwaneri@yahoo.co.uk Anthony Igwe educationalheight@gmail.com Aim/Purpose: The need to explore leaders’ role as a mediating factor between knowledge sharing and firms’ competitiveness was the focus of this paper. Further, gaps related to knowledge sharing influence on firms’ competitiveness from an emerging economy perspective was a major driver of this study. Background: The relevance of knowledge sharing is today crucial for firms that seek to harness internal resource innovation towards ensuring increased competitiveness. The link between the actions of leaders and outcomes from sharing knowledge towards increased competitiveness would further advance theory on knowledge sharing and provide managerial implication that is instrumental for an improved organisational outcome. Methodology: The study sample was 282 participants and Partial least square structural equation model was used for the analysis of the data obtained through a questionnaire survey with the aid of SmartPLSv3.9. Contribution: The study contributes to knowledge management literature through advancing leadership as a mediating factor that accounts for the link between knowledge sharing and firms’ competitiveness, most especially from an emerging economy perspective. Findings: Knowledge sharing was found to have a positive effect on firms’ competitiveness. The study found that leadership behaviour mediates the relationship between knowledge sharing and a firm’s competitiveness. Recommendations for Practitioners: The study recommends that, when supported with the right attitude from leaders in the organisation, knowledge sharing will be beneficial towards the firm gaining competitiveness most especially. Future Research: Future studies should be carried out in other sectors aside from the manufacturing sector using the same measures used to measure knowledge sharing. Also, a comparative analysis of knowledge sharing and firms’ competitiveness using leaders’ behaviour as a mediator should be researched in other developing economies. http://www.informingscience.org/Publications/4693 leaders’ behaviour knowledge sharing competitiveness Nigeria manufacturing firms eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-02-14 16 077 099 4695 article Carolina F Abrantes carolinafelix@ua.pt Óscar Mealha oem@ua.pt Diogo Gomes dgomes@ua.pt João Paulo Barraca jpbarraca@ua.pt Carlos Ferreira cviana@gocontact.pt Aim/Purpose: In this work, the authors propose an augmented model for human-centered Unified Communications & Collaboration (UC&C) product design and evaluation, which is supported by previous theoretical work. Background: Although the goal of implementing UC&C in an organization is to promote and mediate group dynamics, increasing overall productivity and collaboration; it does not seem to provide a solution for effective communication. It is clear that there is still a lack of consideration for human communication processes in the development of such products. Methodology: This paper is sustained by existing research to propose and test the application of an augmented model capable of supporting the design, development and evaluation of UC&C services that can be driven by the human communication process. To test the application of the augmented model in UC&C service development, a proof-of-concept mobile prototype was elaborated upon and evaluated, making use of User Experience (UX) and user-centred methods and techniques. A total of nine testing sessions were carried out in an organizational communication setup and recorded with eye tracking technology. Contribution: The authors argue that UC&C services should look at the user’s (human) natural processes to improve effective infocommunication and thus enhance collaboration. Authors believe this augmented version of the model will pave the way improving the research and development of useful and practical infocommunication products, capable of truly serving users’ needs. Findings: On evaluation of the prototype, qualitative data analysis uncovered structural problems in the proposed prototype which hindered the augmented model’s elements and subsequently, the user experience. Five out of eighteen identified interaction issues are highlighted in this paper to demonstrate the proposed augmented model’s validity, applied in UC&C services evaluation. Recommendations for Practitioners: Considering and respecting the user’s natural communication processes, practitioners should be able to propose and develop innovative solutions that truly enable and empower effective organizational collaboration. UC&C functionalities should be designed, taking the augmented model’s proposed elements and their pertinence in representing the human interpersonal communication phenomena into consideration, namely: Social Presence; Immediacy of Communication; Concurrency and Synchronicity. Recommendation for Researchers: This paper intends to demonstrate that the adoption and use of UTAUT technology characteristics, in conjunction with Synchronicity proposition, can be considered as a reference for human-centric design and the evaluation of UC&C systems. Impact on Society: To highlight the need to develop further research on this important topic of human collaboration mediated by technology inside organizations. Future Research: This research focused its attention on communication functionalities. However, collaboration can potentially be affected by other services that may be included in a UC&C system, such as scheduling, meetings or task management. Future research could consider employing this augmented model to evaluate such systems or proof-of-concept prototypes. http://www.informingscience.org/Publications/4695 human-computer interaction organizational communication and collaboration human-centred design interpersonal communication empirical study eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-04-05 16 101 124 4736 article Maria L Goyayi goyayim@ukzn.ac.za Lizzy O Ofusori ofusoril@ukzn.ac.za Paul Kariuki kariukip@ukzn.ac.za Moses Okpeku okpekum@ukzn.ac.za Prabhakar Rontala Subramanniam prabhakarr@ukzn.ac.za Aim/Purpose: The paper’s objective is to examine the challenges of using the mobile phone to mine location data for effective contact tracing of symptomatic, pre-symptomatic, and asymptomatic individuals and the implications of this technology for public health governance. Background: The COVID-19 crisis has created an unprecedented need for contact tracing across South Africa, requiring thousands of people to be traced and their details captured in government health databases as part of public health efforts aimed at breaking the chains of transmission. Contact tracing for COVID-19 requires the identification of persons who may have been exposed to the virus and following them up daily for 14 days from the last point of exposure. Mining mobile phone location data can play a critical role in locating people from the time they were identified as contacts to the time they access medical assistance. In this case, it aids data flow to various databases designated for COVID-19 work. Methodology: The researchers conducted a review of the available literature on this subject drawing from academic articles published in peer-reviewed journals, research reports, and other relevant national and international government documents reporting on public health and COVID-19. Document analysis was used as the primary research method, drawing on the case studies. Contribution: Contact tracing remains a critical strategy in curbing the deadly COVID-19 pandemic in South Africa and elsewhere in the world. However, given increasing concern regarding its invasive nature and possible infringement of individual liberties, it is imperative to interrogate the challenges related to its implementation to ensure a balance with public governance. The research findings can thus be used to inform policies and practices associated with contact tracing in South Africa. Findings: The study found that contact tracing using mobile phone location data mining can be used to enforce quarantine measures such as lockdowns aimed at mitigating a public health emergency such as COVID-19. However, the use of technology can expose the public to criminal activities by exposing their locations. From a public governance point of view, any exposure of the public to social ills is highly undesirable. Recommendations for Practitioners: In using contact tracing apps to provide pertinent data location caution needs to be exercised to ensure that sensitive private information is not made public to the extent that it compromises citizens’ safety and security. The study recommends the development and implementation of data use protocols to support the use of this technology, in order to mitigate against infringement of individual privacy and other civil liberties. Recommendation for Researchers: Researchers should explore ways of improving digital applications in order to improve the acceptability of the use of contact tracing technology to manage pandemics such as COVID-19, paying attention to ethical considerations. Impact on Society: Since contact tracing has implications for privacy and confidentiality it must be conducted with caution. This research highlights the challenges that the authorities must address to ensure that the right to privacy and confidentiality is upheld. Future Research: Future research could focus on collecting primary data to provide insight on contact tracing through mining mobile phone location data. Research could also be conducted on how app-based technology can enhance the effectiveness of contact tracing in order to optimize testing and tracing coverage. This has the potential to minimize transmission whilst also minimizing tracing delays. Moreover, it is important to develop contact tracing apps that are universally inter-operable and privacy-preserving. http://www.informingscience.org/Publications/4736 COVID-19 contact tracing public governance South Africa eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-04-05 16 125 145 4739 article Elan N Purwanto elannurhadi@gmail.com Ernie T Sule ernie.tisnawati.fe@unpad.ac.id Imas Soemaryani imas.soemaryani@unpad.ac.id Yudi Azis yudi.azis@unpad.ac.id Aim/Purpose: The aim of this study is to develop a research model derived from relevant literature to guide empirical efforts. Background: Companies struggle to innovate, which is essential for improving their performance, surviving in competition, and growing. A number of studies have discussed company innovation capability, stating that innovation capability is influenced by several variables such as cooperation and knowledge management. Therefore, further research is necessary to identify factors playing a role in enhancing innovation capability. Methodology: This study is based on systematic literature review. The stages are: (1) research scope review, (2) comprehensive online research, (3) journal quality assessment, (4) data extraction from journals, (5) journal synthesis, and (6) comprehensive report. The online research used Google Scholar database, by browsing titles, abstracts, and keywords to locate empirical research studies in peer-reviewed journals published in 2010-2020. Furthermore, 62 related articles were found, of which 38 articles were excluded from further analysis and 24 articles were selected because they were more related to the topic. Contribution: The results of this study enrich the research in the field of knowledge management, cooperation, and innovation capability by developing a conceptual framework of innovation capability. The proposed theoretical model may be fundamental in addressing the need of a research model to guide further empirical efforts. Findings: This study provides a research model derived from systematically reviewing relevant literature. The proposed theoretical model was done by incorporating the aspects of knowledge management, cooperation, and innovation capability. The model shows that knowledge management and cooperation are essential aspects of innovation capability. Furthermore, this study also provides the dimensions and sub dimensions of each variable that was established after synthesizing the literature review. Recommendations for Practitioners: Business practitioners can use the identified predictors of innovation capability and the dimensions of each variable to explore their company’s innovation capability. They can also take the relevant variables into consideration when making policies regarding innovation. Recommendation for Researchers: The theoretical model proposed in this study needs validation with further empirical investigation. Impact on Society: Readers of this paper can obtain an understanding that knowledge management and cooperation are essential aspects to consider in enhancing innovation capability. Future Research: Future studies should explore other dimensions of knowledge management and cooperation through alternative approaches and perspectives. http://www.informingscience.org/Publications/4739 knowledge management cooperation innovation capability eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-04-16 16 147 172 4743 article Fahad Sawaean ZP03485@siswa.ukm.edu.my Khairul A. M. Ali kabma@ukm.edu.my Aim/Purpose: This paper aimed to examine the impact of learning orientation on organizational performance of small and medium enterprises (SMEs) via the mediating role of total quality management (TQM) practices and the moderating role of innovation culture. Background: SMEs’ organizational performance in developing countries, particularly in Kuwait, remains below expectation due to increasing competition and inadequate managerial practices that negatively impact their performance. Although several studies had revealed a significant effect of learning orientation on SMEs’ performance, the direct impact of learning orientation on their performance is still unclear. Thus, the link between learning orientation and organizational performance remains inconclusive and requires further examination. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. The data were collected by distributing a survey questionnaire to the owners and Chief Executive Officers (CEOs) of Kuwaiti SMEs using online and on-hand instruments with 384 useable data obtained. Furthermore, the partial least square-structural equation modeling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: This study bridged the significant gap in the role of learning orientation on SMEs’ performance in developing countries, specifically Kuwait. In this sense, a conceptual model was introduced, comprising a learning orientation, TQM practices, innovation culture, and organizational performance. In addition, this study confirmed the significant influence of TQM practices and innovation culture as intermediate variables in strengthening the relationship between learning orientation and organizational performance, which has not yet been verified in Kuwait. Findings: The results in this study revealed that learning orientation had a significant impact on organizational performance of SMEs in Kuwait. It could be observed that TQM practices play an important role in mediating the relationship between learning orientation and performance of SMEs, as well as that innovation culture plays an important moderating role in the same relation. Recommendations for Practitioners: This study provided a framework for the decision-makers of SMEs on the significant impact of the antecedents that enhanced the level of organizational performance. Hence, owners/CEOs of SMEs should improve their awareness and knowledge of the importance of learning orientation, TQM practices, and innovation culture since it could significantly influence their performance to achieve success and sustainability when adopted and managed systematically. The CEOs should also consider building an innovation culture in the internal environment, which enables them to transform new knowledge and ideas into innovative methods and practices. Recommendation for Researchers: The results in this study highlighted the mediating effect of TQM practices on the relationship between learning orientation (the independent variable) and organizational performance (the dependent variable) of SMEs and the moderating effect of innovation culture in the same nexus. These relationships were not extensively addressed in SMEs and thus required further validation. Impact on Society: This study also influenced the management strategies and practices adopted by entrepreneurs and policymakers working in SMEs in developing countries, which is reflected in their development and the national economy. Future Research: Future studies should apply the conceptual framework of this study and assess it further in other sectors, including large firms in developing and developed countries, to generalize the results. Additionally, other mechanisms should be introduced as significant antecedents of SMEs’ performance, such as market orientation, technological orientation, and entrepreneurial orientation, which could function with learning orientation to influence organizational performance effectively. http://www.informingscience.org/Publications/4743 small and medium enterprises learning orientation total quality management practices innovation culture organizational performance resource-based view Kuwait eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-04-28 16 173 211 4746 article Ahmad A. Rabaa'i ahmad_rabaai@yahoo.com Xiaodi Zhu xzhu@njcu.edu Aim/Purpose: The aim of this study is to determine the variables which affect the intention to use Near Field Communication (NFC)-enabled smart wearables (e.g., smartwatches, rings, wristbands) payments. Background: Despite the enormous potential of wearable payments, studies investigating the adoption of this technology are scarce. Methodology: This study extends the Technology Acceptance Model (TAM) with four additional variables (Perceived Security, Trust, Perceived Cost, and Attractiveness of Alternatives) to investigate behavioral intentions to adopt wearable payments. The moderating role of gender was also examined. Data collected from 311 Kuwaiti respondents were analyzed using Structural Equation Modeling (SEM) and multi-group analysis (MGA). Contribution: The research model provided in this study may be useful for academics and scholars conducting further research into m-payments adoption, specifically in the case of wearable payments where studies are scarce and still in the nascent stage; hence, addressing the gap in existing literature. Further, this study is the first to have specifically investigated wearable payments in the State of Kuwait; therefore, enriching Kuwaiti context literature. Findings: This study empirically demonstrated that behavioral intention to adopt wearable payments is mainly predicted by attractiveness of alternatives, perceived usefulness, perceived ease of use, perceived security and trust, while the role of perceived cost was found to be insignificant. Recommendations for Practitioners: This study draws attention to the importance of cognitive factors, such as perceived usefulness and ease of use, in inducing users’ behavioral intention to adopt wearable payments. As such, in the case of perceived usefulness, smart wearable devices manufacturers and banks enhance the functionalities and features of these devices, expand on the financial services provided through them, and maintain the availability, performance, effectiveness, and efficiency of these tools. In relation to ease of use, smart wearable devices should be designed with an easy to use, high quality and customizable user interface. The findings of this study demonstrated the influence of trust and perceived security in motivating users to adopt wearable payments, Hence, banks are advised to focus on a relationship based on trust, especially during the early stages of acceptance and adoption of wearable payments. Recommendation for Researchers: The current study validated the role of attractiveness of alternatives, which was never examined in the context of wearable payments. This, in turn, provides a new dimension about a determinant factor considered by customers in predicting their behavioral intention to adopt wearable payments. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other m-payments methods, such as m-wallets and P2P payments. Future Research: Future studies should investigate the proposed model in a cross-country and cross-cultural perspective with additional economic, environmental, and technological factors. Also, future research may conduct a longitudinal study to explain how temporal changes and usage experience affect users’ behavioral intentions to adopt wearable payments. Finally, while this study included both influencing factors and inhibiting factors, other factors such as social influence, perceived compatibility, personal innovativeness, mobility, and customization could be considered in future research. http://www.informingscience.org/Publications/4746 gender mobile payment near field communication smart wearables wearable payment Kuwait eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-05-07 16 213 253 4740 article Ghilan Al-Madhagy Taufiq-Hail towfeeq2k5@gmail.com Ayed Rheal A. Alanzi a.alanzi@mu.edu.sa Shafiz A Mohd Yusof ShafizMohdYusof@uowdubai.ac.ae Madallah M Alruwaili Madallah@ju.edu.sa Aim/Purpose: This study aims to propose and empirically validate a model and investigates the factors influencing acceptance and use of Software as a Services cloud computing services (SaaS) from individuals’ perspectives utilizing an integrative model of Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) with modifications to suit the objective of the study. Background: Even though SaaS cloud computing services has gained the acceptance in its educational and technical aspects, it is still expanding constantly with emerging cloud technologies. Moreover, the individual as an end-user of this technology has not been given the ample attention pertaining to SaaS acceptance and adoption (AUSaaS). Additionally, the higher education sector needs to be probed regarding AUSaaS perception, not only from a managerial stance, but also the individual. Hence, further investigation in all aspects, including the human factor, deserves deeper inspection. Methodology: A quantitative approach with probability multi-stage sampling procedure conducted utilizing survey instrument distributed among students from three public Malaysian universities. The valid collected responses were 289 Bachelor’s degree students. The survey included the demographic part as well as the items to measure the constructs relationships hypothesized. Contribution: The empirical results disclosed the appropriateness of the integrated model in explaining the individual’s attitude (R2 = 57%), the behavior intention (R2 = 64%), and AUSaaS at the university settings (R2 = 50%). Also, the study offers valuable findings and examines new relationships that considered a theoretical contribution with proven empirical results. That is, the subjective norms effect on attitude and AUSaaS is adding empirical evidence of the model hypothesized. Knowing the significance of social effect is important in utilizing it to promote university products and SaaS applications – developed inside the university – through social media networks. Also, the direct effect of perceived usefulness on AUSaaS is another important theoretical contribution the SaaS service providers/higher education institutes should consider in promoting the usefulness of their products/services developed or offered to students/end-users. Additionally, the research contributes to the knowledge of the literature and is considered one of the leading studies on accepting SaaS services and applications as proliferation of studies focus on the general and broad concept of cloud computing. Furthermore, by integrating two theories (i.e., TPB and TAM), the study employed different factors in studying the perceptions towards the acceptance of SaaS services and applications: social factors (i.e., subjective norms), personal capabilities and capacities (i.e., perceived behavioral control), technological factors (i.e., perceived usefulness and perceived ease of use), and attitudinal factors. These factors are the strength of both theories and utilizing them is articulated to unveil the salient factors affecting the acceptance of SaaS services and applications. Findings: A statistically positive significant influence of the main TPB constructs with AUSaaS was revealed. Furthermore, subjective norms (SN) and perceived usefulness (PU) demonstrated prediction ability on AUSaaS. Also, SN proved a statically significant effect on attitude (ATT). Specifically, the main contributors of intention are PU, perceived ease of use, ATT, and perceived behavioral control. Also, the proposed framework is validated empirically and statistically. Recommendation for Researchers: The proposed model is highly recommended to be tested in different settings and cultures. Also, recruiting different respondents with different roles, occupations, and cultures would likely draw more insights of the results obtained in the current research and its generalizability Future Research: Participants from private universities or other educational institutes suggested in future work as the sample here focused only on public sector universities. The model included limited number of variables suggesting that it can be extended in future works with other constructs such as trialability, compatibility, security, risk, privacy, and self-efficacy. Comparison of different ethnic groups, ages, genders, or fields of study in future research would be invaluable to enhance the findings or reveal new insights. Replication of the study in different settings is encouraged. http://www.informingscience.org/Publications/4740 common method bias PLS-SEM SaaS cloud computing subjective norms technology acceptance TPB and TAM integrated model eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-07-11 16 255 283 4807 article Sally Saad Fadhil sallysaad.upsi@gmail.com Ramlee Ismail ramlee@fpe.upsi.edu.my Alhamzah Alnoor alhamzah.malik@stu.edu.iq Aim/Purpose: This research investigates the influence of soft skills on graduates’ employability in the technology industry, using the technology industry sector in Malaysia as a case. Background: Organizations are looking for appropriate mechanisms to hire qualified employees with strong soft skills and hard skills. This requires that job candidates possess a set of qualifications and skills which impact their employability. Methodology: Fuzzy Delphi analysis was conducted as preliminary study to identify the critical soft skills required by technology industry sector. The preliminary study produced ten critical soft skills to form a conceptual model of their influence on employability. Then, an online questionnaire survey was distributed in two industry companies in Malaysia to collect research data, and regression analysis was conducted to validate the conceptual model. Contribution: This research focuses on the influence of soft skills on graduate employability in the technology industry sector, since the selection of the best candidate in the industry will improve employee performance and lead to business success. Findings: The results of regression analysis confirmed that Communication skills, Attitude, Integrity, Learnability, Motivation, and Teamwork are significantly correlated with employability, which means that these soft skills are the critical factors for employability in Malaysian technology companies. Recommendations for Practitioners: The model proposed in this article can be used by employers to give better assessment of candidates’ compatibility with the jobs available. Impact on Society: This research highlights the critical soft skills required by technology industry sector, which will reduce the unemployment percentages among graduates. Future Research: More studies are required to examine the soft skills found in the literature and to define the most important skills from a general perspective of the industry. Future research should assess the moderating role of other variables, such as skills gap, employee performance, and employee knowledge. Furthermore, it is recommended to conduct similar studies of soft skills for employability in other countries. http://www.informingscience.org/Publications/4807 soft skills human development unemployment industry employability human resource eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-07-20 16 285 306 4821 article Eli Sumarliah 2761514566@qq.com Safiatou S Maiga safiatoumaiga21@yahoo.com Kamila Usmanova kami88@mail.ru Daoping Wang dpwang@ustb.edu.cn Kawthar Mousa mousakawthar@yahoo.com Aim/Purpose: The study attempts to analyse the influences of knowledge management capacity on company performance and supply chain practices. It also examines whether supply chain practices significantly and positively impact company performance. Background: Knowledge management capacity is an essential tactical resource that enables the integration and coordination among supply chain stakeholders, but research examining the link between knowledge management capacity and supply chain practices and their impacts on company performance remains scarce. Methodology: The study uses correlation analysis and factor analysis to confirm the theoretical framework’s validity and structural equation modelling to test hypotheses. The data are obtained from 115 halal food firms in China (with a response rate of 82.7%). Contribution: This study’s findings contribute to the Social Capital Theory by presenting the impacts of different supply chain practices on company performance. The findings also suggest the impact of intangible resources on enhancing company performance, contributing to the Resource-based View Theory. These results are a crucial contribution to both academicians and corporate managers working in the Halal food industry. Managers can apply these findings to discover and adopt knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Findings: This study is an initial effort that provides empirical evidence regarding the relationships among supply chain, knowledge management, and company performance from the perspective of China’s halal food industry. The results prove that knowledge management capacity is the supply chains’ primary success determinant and influencer. Besides, knowledge management capacity positively influences company performance, and supply chain practices directly influence company performance. Recommendations for Practitioners: Managers can apply these study findings to determine and increase knowledge management capacity with practical anticipation that these concepts will align with their company strategies. Also, the research motivates managers to concentrate their knowledge management on enhancing companies’ supply chain practices to achieve improved company performance. Recommendation for Researchers: The study presents a new theoretical framework and empirical evidence for surveying halal food businesses in China. Impact on Society: These results are a significant contribution to the research field and industry focusing on halal foods. Future Research: First, this research focuses only on halal food businesses in China; thus, it is essential to re-examine the hypothesized relations between the constructs in other Chinese business segments and regions. Next, the effect of variables and practices on the theorized framework should be taken into account and examined in other industries and nations. http://www.informingscience.org/Publications/4821 knowledge management capacity company performance supply chain practices China halal food industry eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-07-27 16 307 330 4837 article Khaled Shuaib k.shuaib@uaeu.ac.ae Maitha Al Ketbi 201101198@uaeu.ac.ae Ezedin Barka ebarka@uaeu.ac.ae Marton Gergely mgergely@uaeu.ac.ae Aim/Purpose: The aim of this paper is to propose a new information security controls framework for blockchain technology, which is currently absent from the National and International Information Security Standards. Background: Blockchain technology is a secure and relatively new technology of distributed digital ledgers, which is based on inter-linked blocks of transactions, providing great benefits such as decentralization, transparency, immutability, and automation. There is a rapid growth in the adoption of blockchain technology in different solutions and applications and within different industries throughout the world, such as finance, supply chain, digital identity, energy, healthcare, real estate, and the government sector. Methodology: Risk assessment and treatments were performed on five blockchain use cases to determine their associated risks with respect to security controls. Contribution: The significance of the proposed security controls is manifested in complementing the frameworks that were already established by the International and National Information Security Standards in order to keep pace with the emerging blockchain technology and prevent/reduce its associated information security risks. Findings: The analysis results showed that the proposed security controls herein can mitigate relevant information security risks in blockchain-based solutions and applications and, consequently, protect information and assets from unauthorized disclosure, modification, and destruction. Recommendations for Practitioners: The performed risk assessment on the blockchain use cases herein demonstrates that blockchain can involve security risks that require the establishment of certain measures in order to avoid them. As such, practitioners should not blindly assume that through the use of blockchain all security threats are mitigated. Recommendation for Researchers: The results from our study show that some security risks not covered by existing Standards can be mitigated and reduced when applying our proposed security controls. In addition, researchers should further justify the need for such additional controls and encourage the standardization bodies to incorporate them in their future editions. Impact on Society: Similar to any other emerging technology, blockchain has several drawbacks that, in turn, could have negative impacts on society (e.g., individuals, entities and/or countries). This is mainly due to the lack of a solid national and international standards for managing and mitigating risks associated with such technology. Future Research: The majority of the blockchain use cases in this study are publicly published papers. Therefore, one limitation of this study is the lack of technical details about these respective solutions, resulting in the inability to perform a comprehensive risk identification properly. Hence, this area will be expanded upon in our future work. In addition, covering other standardization bodies in the area of distributed ledger in blockchain technology would also prove fruitful, along with respective future design of relevant security architectures. http://www.informingscience.org/Publications/4837 blockchain technology standards security controls information security security governance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-07-27 16 331 369 4838 article Anshul Jain anshuljain13@gmail.com Tanya Singh tsingh2@amity.edu Satyendra Kumar Sharma skpacific323@gmail.com Aim/Purpose: The primary purpose of this study is to provide a cost-effective and artificial intelligence enabled security solution for IoT enabled healthcare ecosystem. It helps to implement, improve, and add new attributes to healthcare services. The paper aims to develop a method based on an artificial neural network technique to predict suspicious devices based on bandwidth usage. Background: COVID has made it mandatory to make medical services available online to every remote place. However, services in the healthcare ecosystem require fast, uninterrupted facilities while securing the data flowing through them. The solution in this paper addresses both the security and uninterrupted services issue. This paper proposes a neural network based solution to detect and disable suspicious devices without interrupting critical and life-saving services. Methodology: This paper is an advancement on our previous research, where we performed manual knowledge-based intrusion detection. In this research, all the experiments were executed in the healthcare domain. The mobility pattern of the devices was divided into six parts, and each one is assigned a dedicated slice. The security module regularly monitored all the clients connected to slices, and machine learning was used to detect and disable the problematic or suspicious devices. We have used MATLAB’s neural network to train the dataset and automatically detect and disable suspicious devices. The different network architectures and different training algorithms (Levenberg–Marquardt and Bayesian Framework) in MATLAB software have attempted to achieve more precise values with different properties. Five iterations of training were executed and compared to get the best result of R=99971. We configured the application to handle the four most applicable use cases. We also performed an experimental application simulation for the assessment and validation of predictions. Contribution: This paper provides a security solution for the IoT enabled healthcare system. The architectures discussed suggest an end-to-end solution on the sliced network. Efficient use of artificial neural networks detects and block suspicious devices. Moreover, the solution can be modified, configured and deployed in many other ecosystems like home automation. Findings: This simulation is a subset of the more extensive simulation previously performed on the sliced network to enhance its security. This paper trained the data using a neural network to make the application intelligent and robust. This enhancement helps detect suspicious devices and isolate them before any harm is caused on the network. The solution works both for an intrusion detection and prevention system by detecting and blocking them from using network resources. The result concludes that using multiple hidden layers and a non-linear transfer function, logsig improved the learning and results. Recommendations for Practitioners: Everything from offices, schools, colleges, and e-consultation is currently happening remotely. It has caused extensive pressure on the network where the data flowing through it has increased multifold. Therefore, it becomes our joint responsibility to provide a cost-effective and sustainable security solution for IoT enabled healthcare services. Practitioners can efficiently use this affordable solution compared to the expensive security options available in the commercial market and deploy it over a sliced network. The solution can be implemented by NGOs and federal governments to provide secure and affordable healthcare monitoring services to patients in remote locations. Recommendation for Researchers: Research can take this solution to the next level by integrating artificial intelligence into all the modules. They can augment this solution by making it compatible with the federal government’s data privacy laws. Authentication and encryption modules can be integrated to enhance it further. Impact on Society: COVID has given massive exposure to the healthcare sector since last year. With everything online, data security and privacy is the next most significant concern. This research can be of great support to those working for the security of health care services. This paper provides “Security as a Solution”, which can enhance the security of an otherwise less secure ecosystem. The healthcare use cases discussed in this paper address the most common security issues in the IoT enabled healthcare ecosystem. Future Research: We can enhance this application by including data privacy modules like authentication and authorisation, data encryption and help to abide by the federal privacy laws. In addition, machine learning and artificial intelligence can be extended to other modules of this application. Moreover, this experiment can be easily applicable to many other domains like e-homes, e-offices and many others. For example, e-homes can have devices like kitchen equipment, rooms, dining, cars, bicycles, and smartwatches. Therefore, one can use this application to monitor these devices and detect any suspicious activity. http://www.informingscience.org/Publications/4838 IoT Network Slicing Software Defined Network (SDN) IoT Ecosystem IoT Security Healthcare Intrusion Detection System (IDS) Machine Learning (ML) Artificial Neural Network (ANN) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-08-07 16 371 395 4841 article Imran Mahmud imranmahmud@daffodilvarsity.edu.bd Mohamed Emran Hossain emran@daffodilvarsity.edu.bd Rozhan M Idrus rozhanmidrus@gmail.com Aim/Purpose: The main aim of this study is to identify the factors that influence the continuance intention of use of innovative systems by non-academic employees of a private university and associated academic institutions in Bangladesh. Background: The targeted academic institutions have introduced many new online services aimed at improving students’ access to information and services, including a new online library, ERP or online forum, and the jobs-tracking system (JTS). This research is focused only on the JTS for two reasons. First, it is one of the most crucial systems for the Daffodil Family, as it enables efficient working across many institutes spread across the country and abroad. Second, it is employed in a wide variety of organisational institutes, not just the university. This study aims to discover negative factors that lead to a decrease in users’ intentions to continue using the system. The ultimate goal is to improve the motivation among administrative staff to use technology-related innovation by reducing or eliminating the problems. Methodology: G* power analysis was employed to determine the expected sample size. A questionnaire survey was conducted of 211 users of a new job tracking system from a private university in Bangladesh, to collect data for testing the suggested research model. The data was analysed using the structural equation technique, which is a powerful multivariate analysis mechanism. Contribution: This research contributes to the body of literature and helps better understand users’ continuance intention in the post-implementation phase of the JTS. It complements the micro-level examinations of continuance intention of using IT, by building on our understanding of the phenomenon at the individual level. Specifically, this study examines the role of technostress where organisations invest in IT to make their users more comfortable with innovative and new technologies like the JTS. Findings: This research develops a theoretical advancement of the expectation-confirmation theory, with implications for IT managers and senior management dealing with IT-related behaviour. All proposed hypotheses were supported. Specifically, the predictors of exhaustion – work overload, work–life balance, and role ambiguity – are significant. The core factors for satisfaction, perceived usefulness, and confirmation, are also found to be significant. Finally, satisfaction and exhaustion significantly influence continuance intention, in both positive and negative ways. Recommendations for Practitioners: This study gives an idea about some of the difficulties that people face when implementing new and innovative IT, particularly in academia in Bangladesh. It offers insights into strategies the management may want to follow when implementing new technology like the JTS. This study suggests strategies to increase satisfaction and reduce technostress among new users to enhance organisational support for change. Recommendation for Researchers: Methodologically, the study provides researchers about the technique that reduces the threat of the common method bias. First, it created a psychological separation between criterion and predictor variables. Second, the threat of common method variance was actively controlled by modelling a latent method factor and by using marker variables that researchers can use in their work. This study complements the micro-level examinations of continuance intention of using IT by building on our understanding of the phenomenon at the individual level. Researchers can extend this model by integrating other theories. Impact on Society: The findings of the study indicate that work overload, work–life conflict, and role ambiguity create tiredness, leading to lower user satisfaction with the system. Perceived usefulness and confirmation have an increasingly similar effect on users’ satisfaction with the system and their subsequent continuance intention. These findings tell university administrators what measures they should take to improve continuance intention of using innovative technology. Future Research: Future studies could conceptualise a five-factor personality model from the personal perspective of users. This model can also be extended by including the dimensions of absorptive capacity, i.e., the dynamic capabilities of users. Absorptive capacity of understanding, assimilating, and applying might influence the user’s perception of usefulness and confirmation of using JTS. http://www.informingscience.org/Publications/4841 continuance intention technostress business intelligence Bangladesh eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-08-08 16 397 434 4842 article Ahmad A. Rabaa'i ahmad_rabaai@yahoo.com Shareef Abu ALmaati smaati@auk.edu.kw Xiaodi Zhu xzhu@njcu.edu Aim/Purpose: This study aims at investigating the factors that influence students’ continuous intention to use Moodle, as an exemplar of learning management systems (LMSs), in the post-adoption phase. Background: Higher education institutions (HEIs) have invested heavily in learning management systems (LMSs), such as Moodle and BlackBoard, as these systems enhance students’ learning and improve their interactions with the educational systems. While most studies on LMSs have focused on the pre-adoption or acceptance phases of this technology, the determinant factors that influence students’ continuance intention to use LMSs have received less attention in the information systems (IS) literature. Methodology: The theoretical model for this study was primarily drawn from the expectation-confirmation model (ECM). A total of 387 Kuwaiti students, from a private American University in the State of Kuwait, participated in this study. Partial least squares (PLS) was employed to analyze the data. Contribution: This study contributes to the existing scientific knowledge in different ways. First, this study extends the expectation confirmation model (ECM) by integrating factors that are important to students’ continuous intention to use LMSs, including system interactivity, effort expectancy, attitude, computer anxiety, self-efficacy, subjective norms, and facilitating conditions. Second, this study adds on a Kuwaiti literature context by focusing on the continuous intention to use LMSs, which is, to the best of our knowledge, the first study that extends and empirically assesses the applicability of the ECM in the LMSs context in a developing country – Kuwait. Third, this study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM, and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Finally, this study aims to assist HEIs, faculty members, and systems’ developers in understanding the main factors that influence students’ continuance use intention of LMSs. Findings: While subjective norms were not significant, the results mainly showed that students’ continuous intention to use Moodle is significantly influenced by performance expectancy, effort expectancy, attitude, satisfaction, self-efficacy and facilitating conditions. The study’s results also confirmed that satisfaction and attitude are two conceptually and empirically different constructs, conflicting with the views that these constructs can be taken as interchangeable factors in the ECM. Recommendations for Practitioners: This study offers several useful practical implications. First, given the significant influence of system interactivity on performance expectancy and satisfaction, faculty members should modify their teaching approach by enabling communication and interaction among instructors, students, and peers using the LMS. Second, given the significant influence of performance expectancy, satisfaction, and attitude on continuous intention to use the LMS, HEIs should conduct training programs for students on the effective use of the LMS. This would increase students’ awareness regarding the usefulness of the LMS, enhance their attitude towards the LMS, and improve their satisfaction with the system. Third, given the significant role of effort expectancy in influencing performance expectancy, attitude, and students’ continuous intention to use Moodle, developers and system programmers should design the LMS with easy to use, high quality, and customizable user interface. This, in turn, will not only motivate students’ performance expectancy, but will also influence their attitude and continuous intention to use the system. Recommendation for Researchers: This study conceptually and empirically differentiates between satisfaction and attitude, as two separate affect constructs, which were taken as interchangeable factors in ECM and were disregarded by a large number of prior ECM studies concerned with continuous use intention. Hence, it is recommended that researchers include these two constructs in their research models when investigating continuous intention to use a technology. Impact on Society: This study could be used in other countries to compare and verify the results. Additionally, the research model of this study could also be used to investigate other LMSs, such as Blackboard. Future Research: This study focused on how different factors affected students’ continuous intention to use Moodle but did not consider all determinants of successful system, such as system quality, information quality, and instructional as well as course content quality. Thus, future research should devote attention to the effects of these quality characteristics of LMS. http://www.informingscience.org/Publications/4842 continuance use expectation confirmation model (ECM) Kuwait learning management systems (LMS) Moodle eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-10-15 16 435 457 4873 article Anantha Raj A. Arokiasamy anantharaj.arokiasamy@rmit.edu.vn Hoa Thi Nhu Nguyen hoa.nguyenthinhu@stu.edu.vn Khanh-Linh Nguyen s3911921@rmit.edu.vn Aim/Purpose: ******************************************************************************************** After its investigation, the Research Ethics, Integrity, and Governance team at RMIT University found that the primary author of this paper breached the Australian Code and/or RMIT Policy and requested that the article be retracted. ********************************************************************************************* This paper aimed to examine the impact of knowledge management on firm innovativeness of multinational enterprises (MNEs) via the mediating role of innovative culture in Malaysia. Background: Inadequate management practices and growing competition among MNEs operating in developing nations, notably in Malaysia, have hindered their organizational success. Although several studies have shown that knowledge management has a substantial impact on MNEs’ success, it is not apparent if innovation at the company level has a direct impact on their performance. Thus, there is no definitive evidence between knowledge management with business innovativeness and organizational success. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather the data in a specific period. A convenient sampling approach was used to select 296 respondents from Malaysia-dependent MNEs of different industries. One of the advantages of this study methodology is that the sample targeted many fields. Afterward, SPSS AMOS 24.0 software package analysis was performed to test the hypotheses. Contribution: The study contributes to knowledge management and firm innovativeness literature through advancing innovative culture as a mediating factor that accounts for the link between these two constructs, especially from an emerging economy perspective. The research findings also offer managerial implications for organizations in their quest to improve firm innovativeness. Findings: The results support that innovative culture significantly affects MNEs’ performance. Innovative culture enhances the capability of MNEs to be innovative that finally leads to the superior performance of firm innovativeness. Recommendations for Practitioners: According to this research, companies that exhibit an innovative culture, the acquisition of new information, the conversion of tacit knowledge into explicit knowledge, the application of knowledge, and the safeguarding of knowledge, all have a positive effect on their innovativeness. This means that for organizations to run an innovative MNE in Malaysia, a creative culture must be fostered since the current study has shown how it is seen as a catalyst that facilitates learning, transformation, and implementation of relevant knowledge. Recommendation for Researchers: Future studies should be carried out in other sectors aside from the manufacturing sector using the same scales used to measure knowledge management. Furthermore, a comparative analysis of knowledge management and firm innovativeness using innovative culture as a mediator should be researched in other developing economies. Impact on Society: While the main aim of this study was to better understand how and why MNEs operate the way they do, it had an indirect impact on the business and political tactics taken by CEOs and managers working in MNEs in developing countries, as this research has shown. Future Research: Future research should employ the methodology presented in this study and pursue this in other sectors, such as emerging and developed nations’ major businesses, to validate the results and further generalize the conclusions. Other methods should also be incorporated to investigate the other dimensions of MNEs’ performance, including market orientation, technology orientation, and entrepreneurial orientation. http://www.informingscience.org/Publications/4873 knowledge management firm innovativeness innovative culture MNEs Malaysia eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-12-13 16 459 489 4887 article Khairul A. M. Ali kabma@ukm.edu.my Fahad Awad Sawaean ZP03485@siswa.ukm.edu.my Ahmad Awad Alenezi Ahmadalenzi272@hotmail.com Aim/Purpose: This study aimed to investigate the impact of innovation management and learning orientation as the mechanisms playing the role of an intermediate relationship between entrepreneurial leadership and organisational performance of small and medium enterprises (SMEs) in Kuwait. Background: SMEs are currently among the principal economic instruments in most industrialised and developing countries. The contribution of SMEs can be viewed from various perspectives primarily related to the crucial role they play in developing entrepreneurial activities, employment generation, and improving innovativeness. Developing countries, including Kuwait and other countries, in the Gulf Cooperation Council (GCC), have recognised the key role played by SMEs as a strong pillar of growth. Consequently, many governments have formulated policies and programmes to facilitate the growth and success of SMEs. Unfortunately, the organisational performance of SMEs in developing countries, particularly in Kuwait, remains below expectations. The lagged growth could be due to a lack of good managerial practices and increasing competition that negatively impact their performance. Numerous researchers discovered the positive effect of entrepreneurial leadership on SMEs’ performance. However, a lack of clarity remains regarding the direct impact of entrepreneurial leadership on SMEs’ performance, especially in developing countries. Therefore, the nexus between entrepreneurial leadership and organisational performance is still indecisive and requires further studies. Methodology: This study adopted a quantitative approach based on a cross-sectional survey and descriptive design to gather data within a specific period. The data were collected by distributing a survey questionnaire to Kuwaiti SMEs’ owners and Chief Executive Officers (CEOs) via online and on-hand instruments. A total of 384 useable questionnaires were obtained. Moreover, the partial least square-structural equation modelling (PLS-SEM) analysis was performed to test the hypotheses. Contribution: The current study contributed to the existing literature by developing a moderated mediation model integrating entrepreneurial leadership, innovation management, and learning orientation. The study also investigated their effect on the organisational performance of SMEs. The study findings also bridged the existing significant literature gap regarding the role of these variables on SMEs’ performance in developing countries, particularly in Kuwait, due to the dearth of studies linking these variables in this context. Furthermore, this study empirically confirmed the significant effect of innovation management and learning orientation as intermediate variables in strengthening the relationship between entrepreneurial leadership and organisational performance in the settings of Kuwait SMEs, which has not been verified previously. Findings: The study findings showed the beneficial and significant impact of entrepreneurial leadership and innovation management on SME’s organisational performance. The relationship between entrepreneurial leadership and SMEs’ organisational performance is fundamentally mediated by innovation management and moderated by learning orientation. Recommendations for Practitioners: The present study provides valuable insights and information regarding the factors considered by the government, policymakers, SMEs’ stakeholders, and other authorities in the effort to increase the organisational performance level and facilitate the growth of SMEs in Kuwait. SMEs’ owners or CEOs should improve their awareness and knowledge of the importance of entrepreneurial leadership, innovation management, and learning orientation. These variables will have beneficial effects on the performance and assets to achieve success and sustainability if adopted and managed systematically. This study also recommends that SMEs’ entrepreneurs and top management should facilitate supportive culture by creating and maintaining an organisational climate and structure that encourages learning behaviour and innovation mindset among individuals. The initiative will motivate them towards acquiring, sharing, and utilising knowledge and increasing their ability to manage innovation systemically in all production processes to adapt to new technologies, practices, methods, and different circumstances. Recommendation for Researchers: The study findings highlighted the mediating effect of innovation management on the relationship between entrepreneurial leadership (the independent variable) and SMEs’ organisational performance (the dependent variable) and the moderating effect of learning orientation in the same nexus. These relationships were not extensively addressed in SMEs of developing countries and require further validation. Impact on Society: This study aims to influence the management strategies and practices adopted by entrepreneurs and policymakers who work in SMEs in developing countries. The effect will be reflected in the development of their firms and the national economy in general. Future Research: Future research should investigate the conceptual research framework against the backdrop of other developing economies and in other business settings to generalise the results. Future investigation should seek to establish the effect of entrepreneurial leadership style on other mechanisms, such as knowledge management processes, which could function with entrepreneurial leadership to improve SMEs’ performance efficiently. In addition, future studies may include middle and lower-level managers and employees, leading to more positive outcomes. http://www.informingscience.org/Publications/4887 small and medium enterprises entrepreneurial leadership innovation management learning orientation organisational performance Resource-Based View Kuwait eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2021-12-22 16 491 503 4891 article Yahel Giat yahel@jct.ac.il Amichai Mitelman mamichai@gmail.com Aim/Purpose: This paper reports a case study of organizational transition from a non-competitive selection method to a novel bidding method for the selection of consultants in the Architectural and Engineering (A/E) industry. Background: Public procurement agencies are increasingly relying on external consultants for the design of construction projects. Consultant selection can be based on either competitive bidding, or quality-based criteria, or some combination between these two approaches. Methodology: Different sources of information were reviewed: internal documents, and quantitative data from the enterprise software platform (ERP). In addition, informal and unstructured interviews were conducted with relevant officials. Contribution: As there are mixed opinions in the scientific literature regarding the use of competitive bidding for the selection of consultants in the A/E industry, this paper contributes a detailed review of a transition to a competitive selection method and provides a financial and qualitative comparison between the two methods. In addition, the method implemented is novel, as it delegates most of the responsibility of hiring and managing consultants to one main contractor. Findings: While the new selection method was intended to reduce bureaucratic overload, it has unexpectedly also succeeded to reduce costs as well. Recommendations for Practitioners: It may be more efficient and profitable to adopt the selection method described in this study. Recommendation for Researchers: Similar methods can be applied to other industries successfully. Impact on Society: Our method was applied in a public organization and resulted in a better outcome, both financial and managerial. Adopting this approach can benefit public budgets. Future Research: The selection, data storage, and analysis methods are interrelated components. Future analysis of these components can help better shape the consultant selection process. http://www.informingscience.org/Publications/4891 A/E services consultant selection public procurement design management team building eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2022-01-07 16 505 527 4895 article Qiubo Huang qiubo_huang@zjsru.edu.cn Qing Xia 434634996@qq.com Rukmal Nishantha Weerasinghe rukmal@sjp.ac.lk Aim/Purpose: The purpose of this study is to investigate the mechanism of the front/back-office structure affecting new service development (NSD) performance and examine the role of knowledge transfer in the relationship between front/back-office structure and NSD. Background: The separation of front and back-office has become the prevailing trend of the organizational transformation of modern service enterprises in the digital era. Yet, the influence of front and back-office separation dealing with new service development has not been widely researched. Methodology: Building on the internal social capital perspective, a multivariate regression analysis was conducted to investigate the impact of front/back-office structure on the NSD performance through knowledge transfer as an intermediate variable. The data was collected through a survey questionnaire from 198 project-level officers in the commercial banking industry of China. Contribution: This study advances the understanding of front/back-office structure’s influence mechanism on new service development activity. It reveals that knowledge transfer plays a critical role in bridging the impact of front and back-office separation to NSD performance under the trend of digitalization of service organizations. Findings: This study verified the positive effects of front/back-office social capital on NSD performance. Moreover, knowledge transfer predicted the variation in NSD performance and fully mediated the effect of front/back-office social capital on NSD performance. Recommendations for Practitioners: Service organizations should optimize knowledge transfer by promoting the social capital between front and back-office to overcome the negative effect organizational separation brings to NSD. Service and other organizations could explore developing an internal social network management platform, by which the internal social network could be visualized and dynamically managed. Recommendation for Researchers: The introduction of information and communications technology not only divides the organization into front and back-office, but also reduces the face-to-face customer contact. The impacts of new forms of customer contact to new service development and knowledge transfer between customer and service organizations call for further research. Along with the digital servitization, some manufacturing organizations also separate front and back-offices. The current model can be applied and assessed further in manufacturing and other service sectors. Impact on Society: The conclusion of this study guides us to pay attention to the construction of social capital inside organizations with front/back-office structure and implicates introducing and developing sociotechnical theory in front/back-office issue undergoing technological revolution. Future Research: As this study is based on the retail banking industry, similar studies are called upon in other service sectors to identify differences and draw more general conclusions. In addition, as the front and back-offices are being replaced increasingly by information technology such as artificial intelligence (AI), it is necessary to advance the research on front/back-office research with a new theoretical perspective, such as sociotechnical theory. http://www.informingscience.org/Publications/4895 new service development NSD front and back-office social capital knowledge transfer eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-01-23 15 .i iii 4494 article Geoffrey Z. Liu Geoffrey.Liu@sjsu.edu June Lu luj@uhv.edu Table of Contents for Volume 15, 2020, of the Interdisciplinary Journal of Information, Knowledge, and Management http://www.informingscience.org/Publications/4494 IJIKM contents Interdisciplinary Journal of Information Knowledge and Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-01-23 15 001 023 4492 article Chunjiang Yang ycj@ysu.edu.cn Aobo Chen 849604425@qq.com Aim/Purpose: Based on the social exchange theory, this study aimed to explore the underlying mechanisms and boundary conditions between organizational socialization and knowledge sharing. Background: With the advent of the era of the knowledge economy, knowledge has been replacing traditional resources such as capital, labor, and land to become the critical resources of enterprises. The competitiveness of an organization depends much on the effectiveness of its knowledge management; the success of its knowledge management largely relies upon employees’ motivation and willingness to engage in knowledge sharing. Methodology: This study is a longitudinal analysis of data collected from 281 newcomers in Chinese enterprises at two-time points with a one-month interval. Structural equation modeling (SEM) was conducted to test hypotheses by calculating standardized path coefficients and their significance levels. Contribution: The study examined models linking organizational socialization and knowledge sharing that included organizational links and sacrifice as mediators and trust as a moderator. Findings: Results show that the influences of organizational socialization on knowledge sharing change regularly over time. In the role management stage, coworker support and prospects for the future impact the practices of knowledge sharing through links and sacrifice. Moreover, the findings show that trust moderates the effect of links and sacrifice on employees’ knowledge sharing. Recommendations for Practitioners: This study can help enterprises develop targeted human resource management strategies, improve the degree of job embeddedness within the organization, and thus encourage more knowledge sharing among employees. Recommendation for Researchers: First, researchers could pay attention to more underlying mechanisms and boundary conditions in the relationship between organizational socialization and knowledge sharing. Second, focusing on specific cultural context and dimension of concepts may provide a new insight for the future study and help add greater theoretical precision to knowledge sharing. Impact on Society: First, this study suggests that coworker support and prospects for the future improve knowledge sharing within the organization. Second, understanding how job embeddedness (organizational links and organizational sacrifice) acts as a mediator enhancing knowledge sharing, managers should consider raising their attachment relationship to organizations from two aspects: links and sacrifice. Third, knowledge sharing takes place in a team-oriented context, where the success of the team requires high-quality relationships among individual team members within the team as a whole. Future Research: Researchers in the future should employ experimental research design or utilize longitudinal data to ensure that the findings reveal causation. In addition, future research can investigate how the initial level and later changes of organizational socialization are associated with knowledge sharing beyond the observational scope of traditional cross-sectional and lagged research designs. http://www.informingscience.org/Publications/4492 organizational socialization job embeddedness trust knowledge sharing eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-02-07 15 025 037 4503 article Uzoma Heman Ononye ononye.uz@gmail.com Anthony Igwe igweunec@yahoo.com Aim/Purpose: This study investigates social media use and its effect on knowledge sharing. Based on the review of related literature, we hypothesised that social media use has a significant effect on outward and inward knowledge sharing. Background: While the notion of social media use in work organisations has been progressively developed, empirical studies linking social media to the context of knowledge sharing have only begun to emerge. Even so, literature on social media use and its impact on public organisation is still tentative and remains a developing area. Methodology: The partial least square method was utilised in testing of hypotheses with data collected from 103 employees, who by virtue of their position and job function(s) interface with the public for the purpose of sharing knowledge via the social media space. Contribution: The study made contributions to the social knowledge management literature in two ways. First, the study developed a research model that links social media use to the two distinct dimensions of knowledge sharing. Second, the study provides a quantitative approach, where statistical techniques were applied to validate the social media use and knowledge sharing link. Findings: Statistically, the public organisations utilise social media partly for knowledge sharing, with its effect being significant on outward knowledge sharing and insignificant on inward knowledge sharing. This indicates that social media were deployed mainly for information dissemination “outward knowledge sharing” and not for stakeholders’ feedback and interaction “inward knowledge sharing”. Recommendations for Practitioners: Public organisations should develop a policy framework and guidelines for social media use to encourage the full use of this technology to inform and interact with stakeholders. It is important for this policy document to adopt best practices regarding interactive spaces so that both knowledge sharing dimensions manifest themselves in social media communications. Second, it is necessary to carry out staff training for the professional use of this technology for knowledge sharing. Recommendation for Researchers: Future studies should extend to more populations in different contexts to validate findings Impact on Society: This paper intends to influence practices adopted by organisations in the public sector to improve the knowledge sharing dimensions via the social media space. Future Research: Future studies may extend to public organisations in other geographical locations around Nigeria. It will be useful for studies to provide an international perspective by sampling public organisations from different countries or by comparing and contrasting the findings of other studies, specifically those from other countries. A longitudinal study should be encouraged to detect advancement or development with regards to the subject matter over a period of time. http://www.informingscience.org/Publications/4503 social media knowledge sharing outward knowledge sharing inward knowledge sharing public organisation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-02-29 15 039 064 4505 article Rogerio Ferreira da Silva rogerio.ferreira@ufpr.br Itana Maria de Souza Gimenes imsgimenes@uem.br José Carlos Maldonado jcmaldon@icmc.usp.br Aim/Purpose: This paper presents a study of Virtual Communities of Practice (VCoP) evaluation methods that aims to identify their current status and impact on knowledge sharing. The purposes of the study are as follows: (i) to identify trends and research gaps in VCoP evaluation methods; and, (ii) to assist researchers to position new research activities in this domain. Background: VCoP have become a popular knowledge sharing mechanism for both individuals and organizations. Their evaluation process is complex; however, it is recognized as an essential means to provide evidences of community effectiveness. Moreover, VCoP have introduced additional features to face to face Communities of Practice (CoP) that need to be taken into account in evaluation processes, such as geographical dispersion. The fact that VCoP rely on Information and Communication Technologies (ICT) to execute their practices as well as storing artifacts virtually makes more consistent data analysis possible; thus, the evaluation process can apply automatic data gathering and analysis. Methodology: A systematic mapping study, based on five research questions, was carried out in order to analyze existing studies about VCoP evaluation methods and frameworks. The mapping included searching five research databases resulting in the selection of 1,417 papers over which a formal analysis process was applied. This process led to the preliminary selection of 39 primary studies for complete reading. After reading them, we select 28 relevant primary studies from which data was extracted and synthesized to answer the proposed research questions. Contribution: The authors of the primary studies analyzed along this systematic mapping propose a set of methods and strategies for evaluating VCoP, such as frameworks, processes and maturity models. Our main contribution is the identification of some research gaps present in the body of studies, in order to stimulate projects that can improve VCoP evaluation methods and support its important role in social learning. Findings: The systematic mapping led to the conclusion that most of the approaches for VCoP evaluation do not consider the combination of data structured and unstructured metrics. In addition, there is a lack of guidelines to support community operators’ actions based on evaluation metrics. http://www.informingscience.org/Publications/4505 systematic mapping virtual community of practice evaluation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-04-21 15 065 090 4536 article Haili Pan phlwy126@126.com Aim/Purpose: This study examines the kind of community value companies should provide when strengthening the relationship between customers and brands through the establishment of an online brand community, and how this kind of community value promotes customers’ sense of community engagement and willingness to spread brand reputation. The paper also discusses how an enterprise’s brand symbolism affects the relationship between community value and customers’ engagement in online brand community. This study explored the important role of brand symbolism in the establishment of an online brand community. Background: Many companies want to create online brand communities to strengthen their relationships with consumers as well as to provide better service and value to consumers, for example, Huawei’s Huafen community (club.huawei.com), Apple’s support community (support.apple.com/zh-cn), and Samsung’s Galaxy community (samsungmembers.cn). However, these brand communities may have different interests and consumer engagement about the kind of community value to offer to their customers. Methodology: This study uses data collection from questionnaire surveys to design a quantitative research method. An online questionnaire survey of mobile phone users in China was conducted to collect data on social value, cognitive value, brand symbolism, customer community engagement, and brand recommendation. The brands of mobile phone include Apple, Huawei, Samsung, OPPO, VIVO, MI, and Meizu. The researcher purchased a sample service of WJX, an online survey company (www.wjx.cn), and WJX company distributed the questionnaire to research participants. The WJX company randomly selected 240 subjects from their sample database and then sent the questionnaire link to research participants’ mobile phones. Among the 240 research participants, the researcher excluded participants who lacked online brand community experience or had invalid data to qualify for data collection. After the researcher excluded participants who did not qualify for data collection, only 203 qualified questionnaire surveys advanced to the data collection and analysis phase, which was the questionnaire recovery rate of 84.58%. For the model analysis and hypotheses testing, the researcher used statistical software IBM SPSS Statistics and AMOS 21 and Smartpls3. Contribution: This study deepens the body of literature knowledge by combining online brand community value and brand symbolic value to explore issues that companies should consider when establishing an online brand community for their products and services. This study confirms that brands with high symbolic value establish communities and strengthen social values in the online brand community rather than reducing brand symbolism. Online brand community involves a horizontal interaction (peer interaction) among peers, which can have an effect on the symbolic value of brand (social distance). Findings: First, online brand community value (both cognitive and social value) has a positive impact on customer community engagement. Second, customer community engagement has a positive impact on customers’ brand recommend intention. Third, the customer community engagement is a mediator between the online brand community value and the customer brand recommend intention. Most importantly, fourth, the symbolic value of the brand controls the relationship between community value and customer community engagement. For brands with high symbolic value, the community value should emphasize cognitive value rather than social value. For brands with a low symbolic value, the community provides cognitive or social value, which is not affected by the symbolism of the brand. Recommendations for Practitioners: Practitioners can share best practices with the corporate sectors. Brand owners can work with researchers to explore the characteristics of their online brand communities. On this basis, brand owners and researchers can jointly build and manage online brand communities. Recommendation for Researchers: Researchers can explore different perspectives and factors of brand symbolism that involve brand owners when establishing an online brand community to advance consumer engagement, community value, and brand symbolism. Impact on Society: Online brand community is relevant for brand owners to establish brand symbolism, community value, and customer engagement. Readers of this paper can gain an understanding that cognitive and social values are two important drivers of individual participation in online brand communities. The discussion of these two factors can give readers and brand owners the perception to gain more understanding on social and behavior activities in online brand communities. Future Research: Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different perspectives of research samples and hypotheses on online brand community. http://www.informingscience.org/Publications/4536 WOM online brand community brand symbolism customer engagement eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-05-04 15 091 108 4541 article Saud Altaf saltaf@aut.ac.nz Muhammad Waseem Waseem mwaseem@manukau.ac.nz Laila Kazmi lailakazmi95@gmail.com Aim/Purpose: The clustering techniques are normally considered to determine the significant and meaningful subclasses purposed in datasets. It is an unsupervised type of Machine Learning (ML) where the objective is to form groups from objects based on their similarity and used to determine the implicit relationships between the different features of the data. Cluster Analysis is considered a significant problem area in data exploration when dealing with arbitrary shape problems in different datasets. Clustering on large data sets has the following challenges: (1) clusters with arbitrary shapes; (2) less knowledge discovery process to decide the possible input features; (3) scalability for large data sizes. Density-based clustering has been known as a dominant method for determining the arbitrary-shape clusters. Background: Existing density-based clustering methods commonly cited in the literature have been examined in terms of their behavior with data sets that contain nested clusters of varying density. The existing methods are not enough or ideal for such data sets, because they typically partition the data into clusters that cannot be nested. Methodology: A density-based approach on traditional center-based clustering is introduced that assigns a weight to each cluster. The weights are then utilized in calculating the distances from data vectors to centroids by multiplying the distance by the centroid weight. Contribution: In this paper, we have examined different density-based clustering methods for data sets with nested clusters of varying density. Two such data sets were used to evaluate some of the commonly cited algorithms found in the literature. Nested clusters were found to be challenging for the existing algorithms. In utmost cases, the targeted algorithms either did not detect the largest clusters or simply divided large clusters into non-overlapping regions. But, it may be possible to detect all clusters by doing multiple runs of the algorithm with different inputs and then combining the results. This work considered three challenges of clustering methods. Findings: As a result, a center with a low weight will attract objects from further away than a centroid with higher weight. This allows dense clusters inside larger clusters to be recognized. The methods are tested experimentally using the K-means, DBSCAN, TURN*, and IDCUP algorithms. The experimental results with different data sets showed that IDCUP is more robust and produces better clusters than DBSCAN, TURN*, and K-means. Finally, we compare K-means, DBSCAN, TURN*, and to deal with arbitrary shapes problems at different datasets. IDCUP shows better scalability compared to TURN*. Future Research: As future recommendations of this research, we are concerned with the exploration of further available challenges of the knowledge discovery process in clustering along with complex data sets with more time. A hybrid approach based on density-based and model-based clustering algorithms needs to compare to achieve maximum performance accuracy and avoid the arbitrary shapes related problems including optimization. It is anticipated that the comparable kind of the future suggested process will attain improved performance with analogous precision in identification of clustering shapes. http://www.informingscience.org/Publications/4541 clustering density-based large data sets parameter IDCUP arbitrary shapes eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-07-02 15 109 125 4596 article Dan Bouhnik Dan.Bouhnik@biu.ac.il Golan Carmi carmi@jct.ac.il Aim/Purpose: This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is explored. Background: The study focuses on employees’ attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology: A self-reported questionnaire was distributed among 202 employees of a large financial Corporation Contribution: As far as we know, this is the first paper to thoroughly explore employees’ awareness of information system procedures, among financial organizations in Israel, and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. The main contribution of this study is that it investigates compliance with information security practices among employees of a defined financial corporation operating under rigid regulatory governance, confidentiality and privacy of data, and stringent requirements for compliance with information security procedures. Findings: Our results indicate that employees’ attitudes, normative beliefs and personal capabilities to comply with firm’s ISP, have positive effects on the firm’s ISP compliance. Also, employees’ general awareness of IS, as well as awareness to ISP within the firm, positively affect employees’ ISP compliance. Recommendations for Practitioners: This study can help information security managers identify the motivating factors for employee behavior to maintain information security procedures, properly channel information security resources, and manage appropriate information security behavior. Recommendation for Researchers: Researchers can see that corporate rewards and sanctions have significant effects on employee security behavior, but other motivational factors also reinforce the ISP’s compliance behavior. Distinguishing between types of corporations and organizations is essential to understanding employee compliance with information security procedures. Impact on Society: This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research: Future work should sample employees from another type of corporation from other fields and should apply qualitative analysis to explore other aspects of behavioral patterns related to the subject matter. http://www.informingscience.org/Publications/4596 information security behavior information security awareness information security management information security policy employee compliance finan-cial corporation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-07-06 15 127 154 4595 article Michael Hart michael.hart-2@mnsu.edu John Burke john.burke@mnsu.edu Aim/Purpose: Based on business-IT alignment, this study addresses the understudied practice of DevOps. Background: Although organizations continue to implement DevOps practices, few studies explore connections with prior theory. This study contributes to this need by developing the DevOps strategic IT alignment model. Methodology: The sample included 57 firms from the current Forbes Global 2000 and the Fortune 500 lists. The authors employed partial least squares structural equation modeling (PLS-SEM) to evaluate the DevOps IT alignment model. Contribution: The proposed model builds a foundation for further investigation into the influence of theory on DevOps using quantitative research methods. It also contributes to a reliable and valid DevOps instrument for future exploration. Findings: Continuous integration of software and knowledge sharing increases the level of IT subunit alignment in large organizations that foster DevOps. Furthermore, practicing DevOps positively influences the level of business-IT alignment. Recommendations for Practitioners: Organizations that cultivate DevOps experience greater levels of business-IT alignment through stronger knowledge sharing and continuous integration of applications. Thus, managers should identify how to develop closer bonds between subunits with dissimilar skillsets in their organizations. Recommendation for Researchers: Researchers should explore how theories interact, help, and/or do not support blossoming practices like DevOps. Impact on Society: Stronger bonds increase knowledge sharing between interdepartmental colleagues. Lower hierarchical levels of an organization as well as higher managerial levels benefit from cross-domain IT knowledge. Future Research: It is important to explore how different types of knowledge in diverse disciplines requires unique cross-discipline bonds to form and whether these relationships have connections with the contingency theory and quality management. http://www.informingscience.org/Publications/4595 DevOps strategic IT alignment contingency theory continuous integration knowledge sharing continuous deployment software theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-08-18 15 155 174 4616 article Caiyun Zhuang zhuangcaiyun19900@163.com Guohong Chen 54505663@qq.com Xiaoyu Du 18760190330@163.com Aim/Purpose: Drawing on theories of organizational learning, this study analyzes the mechanism of Internet integration capability affecting knowledge generation by 399 Chinese enterprises. This paper will further explore whether there is a moderating role of learning orientation in the mechanism of Internet integration capability affecting enterprise knowledge generation. Background: The Internet has gradually integrated into the enterprise innovation system and penetrated into all aspects of technological innovation, which has promoted the integration and optimization of resources inside and outside the organization. However, there is limited understanding of how the combination of the Internet and integration capability can drive enterprise knowledge generation. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet integration capability, organizational learning, knowledge generation, and uses PROCESS macro program to test the mediated moderation effect of learning orientation. Contribution: First, this study provides empirical evidence for managers to better build Internet integration capability and ambidextrous learning to promote enterprise knowledge generation. Second, this study highlights the important moderating role of learning orientation in the mediating role of ambidextrous learning. Findings: First, the study confirms the mediating role of exploratory learning and exploitative learning in knowledge generation driven by Internet integration capability. Second, the results show that when organizations have a strong learning orientation, the indirect path of Internet integration capability influencing knowledge generation through exploratory learning will be enhanced. Recommendations for Practitioners: Enterprises should pay full attention to the improvement of internet integration capability and ambidextrous learning to promote knowledge generation. In addition, enterprises should establish a good learning atmosphere within the organization to strengthen the bridge role of exploratory learning between Internet integration capability and knowledge generation. Recommendation for Researchers: Researchers could collect data from countries with different levels of economic development to verify the universal applicability of the proposed theoretical model. Impact on Society: This study provides references for enterprises using Internet integration capability to promote their knowledge generation capability under the internet background. Future Research: Future research can compare the impact of Internet integration capability on knowledge generation in different industries. http://www.informingscience.org/Publications/4616 internet integration capability organizational learning knowledge genera-tion learning orientation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-08-27 15 175 202 4607 article Mina Ranjbarfard m.ranjbarfard@alzahra.ac.ir Zeynab Hatami hzeynab50@gmail.com Aim/Purpose: The purpose of this paper is to identify Critical Success Factors (CSFs) for Business Intelligence (BI) implementation projects by studying the existing BI project implementation methodologies and to compare these methodologies based on the identified CSFs. Background: The implementation of BI project has become one of the most important technological and organizational innovations in modern organizations. The BI project implementation methodology provides a framework for demonstrating knowledge, ideas and structural techniques. It is defined as a set of instructions and rules for implementing BI projects. Identifying CSFs of BI implementation project can help the project team to concentrate on solving prior issues and needed resources. Methodology: Firstly, the literature review was conducted to find the existing BI project implementation methodologies. Secondly, the content of the 13 BI project implementation methodologies was analyzed by using thematic analysis method. Thirdly, for examining the validation of the 20 identified CSFs, two questionnaires were distributed among BI experts. The gathered data of the first questionnaire was analyzed by content validity ratio (CVR) and 11 of 20 CSFs were accepted as a result. The gathered data of the second questionnaire was analyzed by fuzzy Delphi method and the results were the same as CVR. Finally, 13 raised BI project implementation methodologies were compared based on the 11 validated CSFs. Contribution: This paper contributes to the current theory and practice by identifying a complete list of CSFs for BI projects implementation; comparison of existing BI project implementation methodologies; determining the completeness degree of existing BI project implementation methodologies and introducing more complete ones; and finding the new CSF “Expert assessment of business readiness for successful implementation of BI project” that was not expressed in previous studies. Findings: The CSFs that should be considered in a BI project implementation include: “Obvious BI strategy and vision”, “Business requirements definition”, “Business readiness assessment”, “BI performance assessment”, “Establishing BI alignment with business goals”, “Management support”, “IT support for BI”, “Creating data resources and source data quality”, “Installation and integration BI programs”, “BI system testing”, and “BI system support and maintenance”. Also, all the 13 BI project implementation methodologies can be divided into four groups based on their completeness degree. Recommendations for Practitioners: The results can be used to plan BI project implementation and help improve the way of BI project implementation in the organizations. It can be used to reduce the failure rate of BI implementation projects. Furthermore, the 11 identified CSFs can give a better understanding of the BI project implementation methodologies. Recommendation for Researchers: The results of this research helped researchers and practitioners in the field of business intelligence to better understand the methodology and approaches available for the implementation and deployment of BI systems and thus use them. Some methodologies are more complete than other studied methodologies. Therefore, organizations that intend to implement BI in their organization can select these methodologies according to their goals. Thus, Findings of the study can lead to reduce the failure rate of implementation projects. Future Research: Future researchers may add other BI project implementation methodologies and repeat this research. Also, they can divide CSFs into three categories including required before BI project implementation, required during BI project implementation and required after BI project implementation. Moreover, researchers can rank the BI project implementation CSFs. As well, Critical Failure Factors (CFFs) need to be explored by studying the failed implementations of BI projects. The identified CSFs probably affect each other. So, studying the relationship between them can be a topic for future research. http://www.informingscience.org/Publications/4607 business intelligence business intelligence project implementation business intelligence implementation methodologies Fuzzy Delphi method critical success factors (CSF) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-09-15 15 203 225 4619 article Hani H Al-Dmour dmourh@ju.edu.jo Futon Asfour Nafissa97r@gmail.com Rand Al-Dmour Rand.aldmour@ju.edu.jo Ahmed Al-Dmour Ahmadmourh@gmail.com Aim/Purpose: This study aimed to examine the effect of marketing knowledge management (MKM) on bank performance via the mediating role of the Fintech innovation in Jordanian commercial banks. Background: An extensive number of studies found a significant relationship between Marketing knowledge management and bank performance (e.g., Akroush & Al-Mohammad, 2010; Hou & Chien 2010; Rezaee & Jafari, 2015; Veismoradi et al., 2013). However, there remains a lack of clarity regarding the relationship between marketing knowledge management (MKM) and bank performance (BP). Furthermore, the linkage between MKM and BP is not straightforward but, instead, includes a more complicated relationship. Therefore, it is argued that managing marketing knowledge management assets and capabilities can enhance performance via the role of financial innovation as a mediating factor on commercial banks; to date, however, there is no empirical evidence. Methodology: Based on a literature review, knowledge-based theory, and financial innovation theory, an integrated conceptual framework has been developed to guide the study. A quantitative approach was used, and the data was collected from 336 managers and employees in all 13 Jordanian commercial banks using online and in hand instruments. Structural equation modeling (SEM) was used to analyze and verify the study variables. Contribution: This article contributes to theory by filling a gap in the literature regarding the role of marketing knowledge management assets and capabilities in commercial banks operating in a developing country like Jordan. It empirically examined and validated the role of Fintech innovation as mediators between marketing knowledge management and bank performance Findings: The main findings revealed that marketing knowledge management had a significant favorable influence on bank performance. Fintech innovation acted as partial mediators in this relationship. Recommendations for Practitioners: Commercial banks should be fully aware of the importance of knowledge management practices to enhance their financial innovation and bank performance. They should also consider promoting a culture of practicing knowledge management processes among their managers and employees by motivating and training to promote innovations. Recommendation for Researchers: The result endorsed Fintech innovation’s mediating effect on the relationship between the independent variable, marketing knowledge management (assets and capabilities), and the dependent variable bank performance, which was not addressed before; thus, it needs further validation. Future Research: The current designed research model can be applied and assessed further in other sectors, including banking and industrial sectors across developed and developing countries. It would also be of interest to introduce other variables in the study model that can act as consequences of MKM capabilities, such as financial and non-financial performance measures http://www.informingscience.org/Publications/4619 marketing knowledge management Fintech innovation bank performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-10-04 15 227 246 4643 article Carlos Santos-Mangudo casant01@ucm.es Antonio J. Heras aheras@ccee.ucm.es Aim/Purpose: This article proposes a methodology for selecting the initial sets for clustering categorical data. The main idea is to combine all the different values of every single criterion or attribute, to form the first proposal of the so-called multiclusters, obtaining in this way the maximum number of clusters for the whole dataset. The multiclusters thus obtained, are themselves clustered in a second step, according to the desired final number of clusters. Background: Popular cluster methods for categorical data, such as the well-known K-Modes, usually select the initial sets by means of some random process. This fact introduces some randomness in the final results of the algorithms. We explore a different application of the clustering methodology for categorical data that overcomes the instability problems and ultimately provides a greater clustering efficiency. Methodology: For assessing the performance of the proposed algorithm and its comparison with K-Modes, we apply both of them to categorical databases where the response variable is known but not used in the analysis. In our examples, that response variable can be identified to the real clusters or classes to which the observations belong. With every data set, we perform a two-step analysis. In the first step we perform the clustering analysis on data where the response variable (the real clusters) has been omitted, and in the second step we use that omitted information to check the efficiency of the clustering algorithm (by comparing the real clusters to those given by the algorithm). Contribution: Simplicity, efficiency and stability are the main advantages of the multicluster method. Findings: The experimental results attained with real databases show that the multicluster algorithm has greater precision and a better grouping effect than the classical K-modes algorithm. Recommendations for Practitioners: The method can be useful for those researchers working with small and medium size datasets, allowing them to detect the underlying structure of the data in an intuitive and reasonable way. Recommendation for Researchers: The proposed algorithm is slower than K-Modes, since it devotes a lot of time to the calculation of the initial combinations of attributes. The reduction of the computing time is therefore an important research topic. Future Research: We are concerned with the scalability of the algorithm to large and complex data sets, as well as the application to mixed data sets with both quantitative and qualitative attributes. http://www.informingscience.org/Publications/4643 clustering categorical data K-Modes eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2020-10-08 15 247 263 4633 article Salah Alsharhan alsharhans@iuk.edu.kw Ahmed A. Al-Hunaiyyan hunaiyyan@hotmail.com Andrew Thomas Bimba andrewbimba@gmail.com Aim/Purpose: This study describes a conceptual model, based on the principles of concept algebra that can provide intelligent academic advice using adaptive, knowledge-based feedback. The proposed model advises students based on their traits and academic history. The system aims to deliver adaptive advice to students using historical data from previous and current students. This data-driven approach utilizes a cognitive knowledge-based (CKB) model to update the weights (values that indicate the strength of relationships between concepts) that exist between student’s performances and recommended courses. Background: A research study conducted at the Public Authority for Applied Education and Training (PAAET), a higher education institution in Kuwait, indicates that students’ have positive perceptions of the e-Advising system. Most students believe that PAAET’s e-Advising system is effective because it allows them to check their academic status, provides a clear vision of their academic timeline, and is a convenient, user-friendly, and attractive online service. Student advising can be a tedious element of academic life but is necessary to fill the gap between student performance and degree requirements. Higher education institutions have prioritized assisting undecided students with career decisions for decades. An important feature of e-Advising systems is personalized feedback, where tailored advice is provided based on students' characteristics and other external parameters. Previous e-Advising systems provide students with advice without taking into consideration their different attributes and goals. Methodology: This research describes a model for an e-Advising system that enables students to select courses recommended based on their personalities and academic performance. Three algorithms are used to provide students with adaptive course selection advice: the knowledge elicitation algorithm that represents students' personalities and academic information, the knowledge bonding algorithm that combines related concepts or ideas within the knowledge base, and the adaptive e-Advising model that recommends relevant courses. The knowledge elicitation algorithm acquires student and academic characteristics from data provided, while the knowledge bonding algorithm fuses the newly acquired features with existing information in the database. The adaptive e-Advising algorithm provides recommended courses to students based on existing cognitive knowledge to overcome the issues associated with traditional knowledge representation methods. Contribution: The design and implementation of an adaptive e-Advising system are challenging because it relies on both academic and student traits. A model that incorporates the conceptual interaction between the various academic and student-specific components is needed to manage these challenges. While other e-Advising systems provide students with general advice, these earlier models are too rudimentary to take student characteristics (e.g., knowledge level, learning style, performance, demographics) into consideration. For the online systems that have replaced face-to-face academic advising to be effective, they need to take into consideration the dynamic nature of contemporary students and academic settings. Findings: The proposed algorithms can accommodate a highly diverse student body by providing information tailored to each student. The academic and student elements are represented as an Object-Attribute-Relationship (OAR) model. Recommendations for Practitioners: The model proposed here provides insight into the potential relationships between students’ characteristics and their academic standing. Furthermore, this novel e-Advising system provides large quantities of data and a platform through which to query students, which should enable developing more effective, knowledge-based approaches to academic advising. Recommendation for Researchers: The proposed model provides researches with a framework to incorporate various academic and student characteristics to determine the optimal advisory factors that affect a student’s performance. Impact on Society: The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advice to students. The proposed approach can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to learning. Future Research: In future studies, the proposed algorithms will be implemented, and the adaptive e-Advising model will be tested on real-world data and then further improved to cater to specific academic settings. The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advisory to students. The approach proposed can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to course recommendation. http://www.informingscience.org/Publications/4633 e-advising academic advising academic model student model cognitive knowledge-based model course selection adaptive algorithm eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-01-09 14 000 000 4172 article Geoffrey Z. Liu Geoffrey.Liu@sjsu.edu June Lu luj@uhv.edu http://www.informingscience.org/Publications/4172 IJIKM contents eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-01-09 14 001 025 4169 article Ra'ed Masa'deh r.masadeh@ju.edu.jo Dmaithan Abdelkarim Almajali almjalidmaithan@yahoo.com Ala'aldin Alrowwad a.alrowwad@ju.edu.jo Bader Obeidat b.obeidat@ju.edu.jo Aim/Purpose: This research aims to examine the role of Knowledge Management (KM) infrastructure (technological, structural, and cultural) in enhancing job satisfaction in the context of developing countries, as exemplified by Jordan. Background: Despite the presence of job satisfaction studies conducted in educational institutions across the world, knowledge management issues have not been taken into consideration as influencing factors. Methodology: A total of 168 responses to a questionnaire survey were collected from the academic staff at Zarqa University in Jordan. Multiple regression analysis was conducted to test the research hypotheses. Contribution: This study offers deeper understanding about the role that knowledge management infrastructure plays in enhancing job satisfaction from a developing country perspective. The proposed model is tested the first time in Jordan. Findings: Results of the current study revealed that there are significant positive impacts of technological and cultural KM infrastructures on job satisfaction, whereas structural KM infrastructure does not have a significant impact on job satisfaction. Also, the results revealed significant gender difference in perception of the impact of knowledge management infrastructure on job satisfaction. On the other hand, an ANOVA test found no significant difference in the impact of knowledge management infrastructure on job satisfaction among groups by age, experience, and academic rank. Recommendation for Researchers: Our findings can be used as a base of knowledge for further studies about knowledge management infrastructure and job satisfaction following different criteria and research procedures. Future Research: The current model can be applied and assessed further in other sectors, including public universities and other services sectors in developed and developing countries. http://www.informingscience.org/Publications/4169 knowledge management infrastructure knowledge management job perfor-mance Jordan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-01-20 14 027 044 4176 article Da Thon Nguyen dant@uel.edu.vn Hanh T Tan tanhanh@ptithcm.edu.vn Duy Hoang Pham Phamhduy@gmail.com Aim/Purpose: In this article, we provide a better solution to Webpage access prediction. In particularly, our core proposed approach is to increase accuracy and efficiency by reducing the sequence space with integration of PageRank into CPT+. Background: The problem of predicting the next page on a web site has become significant because of the non-stop growth of Internet in terms of the volume of contents and the mass of users. The webpage prediction is complex because we should consider multiple kinds of information such as the webpage name, the contents of the webpage, the user profile, the time between webpage visits, differences among users, and the time spent on a page or on each part of the page. Therefore, webpage access prediction draws substantial effort of the web mining research community in order to obtain valuable information and improve user experience as well. Methodology: CPT+ is a complex prediction algorithm that dramatically offers more accurate predictions than other state-of-the-art models. The integration of the importance of every particular page on a website (i.e., the PageRank) regarding to its associations with other pages into CPT+ model can improve the performance of the existing model. Contribution: In this paper, we propose an approach to reduce prediction space while improving accuracy through combining CPT+ and PageRank algorithms. Experimental results on several real datasets indicate the space reduced by up to between 15% and 30%. As a result, the run-time is quicker. Furthermore, the prediction accuracy is improved. It is convenient that researchers go on using CPT+ to predict Webpage access. Findings: Our experimental results indicate that PageRank algorithm is a good solution to improve CPT+ prediction. An amount of though approximately 15 % to 30% of redundant data is removed from datasets while improving the accuracy. Recommendations for Practitioners: The result of the article could be used in developing relevant applications such as Webpage and product recommendation systems. Recommendation for Researchers: The paper provides a prediction model that integrates CPT+ and PageRank algorithms to tackle the problem of complexity and accuracy. The model has been experimented against several real datasets in order to show its performance. Impact on Society: Given an improving model to predict Webpage access using in several fields such as e-learning, product recommendation, link prediction, and user behavior prediction, the society can enjoy a better experience and more efficient environment while surfing the Web. Future Research: We intend to further improve the accuracy of webpage access prediction by using the combination of CPT+ and other algorithms. http://www.informingscience.org/Publications/4176 Webpage access prediction sequence prediction compact prediction tree PageRank algorithm eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-01-24 14 045 076 4184 article Alexei Botchkarev alexei.botchkarev@ontario.ca Aim/Purpose: The aim of this study was to analyze various performance metrics and approaches to their classification. The main goal of the study was to develop a new typology that will help to advance knowledge of metrics and facilitate their use in machine learning regression algorithms Background: Performance metrics (error measures) are vital components of the evaluation frameworks in various fields. A performance metric can be defined as a logical and mathematical construct designed to measure how close are the actual results from what has been expected or predicted. A vast variety of performance metrics have been described in academic literature. The most commonly mentioned metrics in research studies are Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), etc. Knowledge about metrics properties needs to be systematized to simplify the design and use of the metrics. Methodology: A qualitative study was conducted to achieve the objectives of identifying related peer-reviewed research studies, literature reviews, critical thinking and inductive reasoning. Contribution: The main contribution of this paper is in ordering knowledge of performance metrics and enhancing understanding of their structure and properties by proposing a new typology, generic primary metrics mathematical formula and a visualization chart Findings: Based on the analysis of the structure of numerous performance metrics, we proposed a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics. The paper identified three (3) key components (dimensions) that determine the structure and properties of primary metrics: method of determining point distance, method of normalization, method of aggregation of point distances over a data set. For each component, implementation options have been identified. The suggested new typology has been shown to cover a total of over 40 commonly used primary metrics Recommendations for Practitioners: Presented findings can be used to facilitate teaching performance metrics to university students and expedite metrics selection and implementation processes for practitioners Recommendation for Researchers: By using the proposed typology, researchers can streamline development of new metrics with predetermined properties Impact on Society: The outcomes of this study could be used for improving evaluation results in machine learning regression, forecasting and prognostics with direct or indirect positive impacts on innovation and productivity in a societal sense Future Research: Future research is needed to examine the properties of the extended metrics, composite metrics, and hybrid sets of metrics. Empirical study of the metrics is needed using R Studio or Azure Machine Learning Studio, to find associations between the properties of primary metrics and their “numerical” behavior in a wide spectrum of data characteristics and business or research requirements http://www.informingscience.org/Publications/4184 performance metrics error measures accuracy measures distance similarity dissimilarity properties typology classification machine learning regression forecasting prognostics prediction evaluation estimation modeling eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-04-01 14 077 097 4267 article Brenda M Scholtz brenda.scholtz@nmmu.ac.za Jean-Paul Van Belle jean-paul.vanbelle@uct.ac.za Kennedy Njenga knjenga@uj.ac.za Alexander Serenko aserenko@lakeheadu.ca Prashant Palvia pcpalvia@uncg.edu Aim/Purpose: This study forms part of the World IT Project, which aims to gain a deeper understanding of individual, personal and organisational factors influencing IT staff in a modern, work environment. The project also aims to provide a global view that complements the traditional American/Western view. The purpose of this study is to investigate and report on some of these factors, in particular, the role that job satisfaction has in turnover intention (i.e., changing jobs within the IT industry) and turn-away intention (i.e., moving to another industry other than IT) in South Africa. Background: Several studies have reported on the importance of an employee’s job satisfaction to organisation success, and the various factors that influence it. Most studies on job satisfaction adopted a Westernised and not a global view. Very few empirical studies have been conducted on job satisfaction of IT workers in South Africa. This paper reports on the individual, personal and organisational factors that influence the job satisfaction of IT staff in South Africa. Methodology: The study uses statistical analysis of survey data acquired through the World IT Project. Both online and paper based questionnaires were used. A sample size of 301 respondents was obtained from the survey, which was conducted over a period of 6 months during 2017. The factors that influence IT job satisfaction were analysed using correlation analysis, multiple regression analysis and discriminant analysis. The factors investigated were employee and organisational demographics, aspects of occupational culture, and various job-related individual issues. Contribution: This paper presents the only study focused specifically on turnover and turn-away intention amongst IT staff in South Africa. The final proposed model, grounded in the empirical dataset, clearly shows job satisfaction as a strong mediating construct explaining most of the variance in the IT professional’s intention to leave the organisation (i.e. their turnover intention) and the industry (i.e. their turn-away intention). Findings: The findings revealed that there was a significant correlation between job satisfaction and turnover intention as well as between job satisfaction and turn-away intention of IT staff. Perceived professional self-efficacy, strain and experience were also highly correlated with turnover intention. Professional self-efficacy was also significantly correlated with turn-away intention. Based on the analyses that were conducted, a research model is presented that shows the relationships between the various antecedents of turnover and turn-away intention. Recommendations for Practitioners: Managers in organisations dealing with the shortage of IT skills can use the model to plan interventions to reduce IT staff turnover rates by focussing on addressing the identified individual issues such as strain, job (in)security and work load as well as the personal value and IT occupational culture issues. Recommendation for Researchers: Researchers in the field of IT staff recruitment and management can find value for their research in the proposed refined model of IT job satisfaction and turnover intention. Future research could possibly replicate the study in other countries or could focus on different factors. Impact on Society: IT skills play a crucial role in society today and are therefore in high demand. However, this demand is not being satisfied by the current rate of supply. Research into what factors influence IT staff to leave the organisation or the industry can assist managers with improving their employee relations and job conditions so as to reduce this turnover and increase organisations’ and society’s competitiveness and economic growth. Future Research: It would be interesting to determine if the findings are similar for a sample of smaller organisations and/or younger IT employees since this study focussed on larger organisations and more experienced staff. Future research could also compare the findings of South African organisations with those in other countries. http://www.informingscience.org/Publications/4267 turnover intention job satisfaction in IT staff IS personnel workforce burn-out exhaustion eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-04-16 14 099 117 4280 article Mawarny M Rejab mawarny@uum.edu.my James Noble kjx@ecs.vuw.ac.nz Stuart Marshall stuart.marshall@vuw.ac.nz Aim/Purpose: This paper aims to discuss the activities involved in facilitating self-selecting teams for Agile software development projects. This paper also discussed how these activities can influence the successful expertise coordination in Agile teams. Background: Self-selecting teams enable Agile team members to choose teams based on whom they prefer to work with. Good team bonding allows Agile team members to rely on each other in coordinating their expertise resources effectively. This is the focal point where expertise coordination is needed in Agile teams. Methodology: This study employed Grounded Theory by interviewing 48 Agile practitioners from different software organizations mainly based in New Zealand. This study also carried out several sessions of observations and document analysis in conjunction with interviews. Contribution: This study contributes to the body of knowledge by identifying the way self-selecting teams support expertise coordination. Findings: Our findings indicated that the activities involved tend to influence the successful expertise coordination in Agile teams. Self-selecting teams are essential to supporting expertise coordination by increasing inter-dependencies between Agile team members, ensuring a diverse range of knowledge and skills in teams. Recommendations for Practitioners: The self-selecting team activities can be used as a guideline for Agile software organizations in forming self-selecting teams in the fastest and most efficient way. It is vital for management to facilitate the process of self-selecting teams in order to optimize successful expertise coordination. Recommendation for Researchers: There is potential for further Grounded Theory research to explore more activities and strategies involved in self-selecting teams. Impact on Society: Self-selecting teams in Agile software developments projects tend to boost the productivity of software development. Future Research: Several hypotheses can be tested through a deductive approach in future studies. http://www.informingscience.org/Publications/4280 agile software development self-selecting teams expertise coordination grounded theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-04-26 14 119 143 4320 article Ewa Wanda Ziemba ewa.ziemba@ue.katowice.pl Monika Eisenbardt monika.eisenbardt@ue.katowice.pl Roisin Mullins r.mullins@uwtsd.ac.uk Sandra Dettmer sandra.dettmer@uwtsd.ac.uk Aim/Purpose: The main purpose of this paper is to identify prosumers’ engagement in business process innovation through knowledge sharing. Background: In the increasingly competitive knowledge-based economy, companies must seek innovative methods of doing business, quickly react to consumer demand, and provide superior value to consumers. Simultaneously, contemporary consumers, named “prosumers”, want to be active co-creators of value and satisfy their consumption needs through collaboration with companies for co-creation, co-design, co-production, co-promotion, co-pricing, co-distribution, co-consumption, and co-maintenance. Consequently, consumer involvement in development and improvement of products and business process must be widely analyzed in various contexts. Methodology: The research is a questionnaire survey study of 388 prosumers in Poland and 76 in the UK. Contribution The contribution of this research is twofold. First, it identifies how prosumers can be engaged in business processes through knowledge sharing. Second, it investigates the differences between Poland- and UK-based prosumers in engagement in business process. Findings: The study found that prosumers are engaged in knowledge sharing at each stage of the business process innovation framework. However, there are differences in the types of processes that draw on prosumers’ engagement. Prosumers in Poland are found to engage mostly in the business process of developing and managing products, whereas prosumers in the UK engage mostly in the business process of managing customer services. Recommendations for Practitioners: This study provides practitioners with guidelines for engaging prosumers and their knowledge sharing to improve process innovation. Companies gain new insight from these findings about prosumers’ knowledge sharing for process innovation, which may help them make better decisions about which projects and activities they can engage with prosumers for future knowledge sharing and creating prospective innovations. Recommendations for Researchers: Researchers may use this methodology and do similar analysis with different samples in Poland, the UK, and other countries, for many additional comparisons between different groups and countries. Moreover, a different methodology may be used for identifying prosumers’ engagement and knowledge sharing for processes improvement. Future Research: This study examined prosumers’ engagement from the prosumers’ standpoint. Therefore prosumers’ engagement from the company perspective should be explored in future research. http://www.informingscience.org/Publications/4320 consumer engagement consumer knowledge prosumer knowledge sharing business processes consumer innovations eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-04-28 14 145 163 4299 article Ying Han ying_han_@hotmail.com Aim/Purpose: This study examines the influence of ambidextrous knowledge sharing in industrial clusters on innovation performance from the perspective of knowledge-based dynamic capabilities. Background: The key factor to improving innovation performance in an enterprise is to share knowledge with other enterprises in the same cluster and use dynamic capabilities to absorb, integrate, and create knowledge. However, the relationships among these concepts remain unclear. Based on the dynamic capability theory, this study empirically reveals how enterprises drive innovation performance through knowledge sharing. Methodology: Survey data from 238 cluster enterprises were used in this study. The sample was collected from industrial clusters in China’s Fujian province that belong to the automobile, optoelectronic, and microwave communications industries. Through structural equation modeling, this study assessed the relationships among ambidextrous knowledge sharing, dynamic capabilities, and innovation performance. Contribution: This study contributes to the burgeoning literature on knowledge management in China, an important emerging economy. It also enriches the exploration of innovation performance in the cluster context and expands research on the dynamic mechanism from a knowledge perspective. Findings: Significant relationships are found between ambidextrous knowledge sharing and innovation performance. First, ambidextrous knowledge sharing positively influences the innovation performance of cluster enterprises. Further, knowledge absorption and knowledge generation capabilities play a mediating role in this relationship, which confirms that dynamic capabilities are a partial mediator in the relationship between ambidextrous knowledge sharing and innovation performance. Recommendations for Practitioners: The results highlight the crucial role of knowledge management in contributing to cluster innovation and management practices. They indicate that cluster enterprises should consider the importance of knowledge sharing and dynamic capabilities for improving innovation performance and establish a multi-agent knowledge sharing platform. Recommendation for Researchers: Researchers could further explore the role of other mediating variables (e.g., organizational agility, industry growth) as well as moderating variables (e.g., environmental uncertainty, learning orientation). Impact on Society: This study provides a reference for enterprises in industrial clusters to use knowledge-based capabilities to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct a comparative analysis of industrial clusters. http://www.informingscience.org/Publications/4299 industrial cluster ambidextrous knowledge sharing innovation dynamic capabilities China eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-05-02 14 165 181 4310 article Hsiaoping Yeh hpyeh2000@nkust.edu.tw Fenghung Kuo 0428902@nkust.edu.tw Aim/Purpose: This study empirically analyzed and examined the effectiveness of the online advocacy banners on customers’ reactions to make replacements with the similar products in their shopping carts. Background: When a product in a shopping cart is removed, it might be put back into the cart again during the same purchase or it may be bought in the future. Otherwise, it might be abandoned and replaced with a similar item based on the customer’s enquiry list or on the recommendation of banners. There is a lack of understanding of this phenomenon in the existing literature, pointing to the need for this study. Methodology: With a database from a Taiwanese e-retailer, data were the tracks of empirical webpage clickstreams. The used data for analyses were particularly that the products were purchased again or replaced with the similar ones upon the advocacy banners being shown when they were removed from customers’ shopping carts. Few pre-defined Apriori rules as well as similarity algorithm, Jaccard index, were applied to derive the effectiveness. Contribution: This study addressed a measurement challenge by leveraging the information from clickstream data – particularly clickstream data behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior, but not click-through rates, for web banners. The study develops a new methodology to aid advertisers in evaluating the effectiveness of their banner campaign. Findings: The recommending/advocating titles of “you probably are interested” and “the most viewed” are not significantly effective on saving back customers’ removed products or repurchasing similar items. For the banners entitled “most buy”, “the most viewed” might only show popularity of the items, but is not enough to convince them to buy. At the current stage on the host website, customers may either not trust in the host e-retailer or in such mechanism. Additionally, the advocating/recommending banners only are effective on the same customer visits and their effects fade over time. As time passes, customers’ impressions of these banners may become vague. Recommendations for Practitioners: One managerial implication is more effective adoption of advocacy/recommendation banners on e-retailing websites. Another managerial implication is the evaluation of the advocacy/recommendation banners. By using a data mining technique to find the association between removed products and restored ones in e-shoppers’ shopping carts, the approach and findings of this study, which are important for e-retailing marketers, reflect the connection between the usage of banners and the personalized purchase changes in an individual customer’s shopping cart. Recommendation for Researchers: This study addressed a new measurement which challenges to leverage the information from clickstream data instead of click-through rates – particularly retailing webpages browsing behavior. These data are most useful to observe the real-time behavior of consumers on websites and also are applied to studying click-through behavior. Impact on Society: Personalization has become an important technique that allows businesses to improve both sales and service relationships with their online customers. This personalization gives e-marketers the ability to deliver real effectiveness in the use of banners. Future Research: The effectiveness is time- and case-sensible. Business practitioners and academic researchers are encouraged to apply the mining methodology to longevity studies, specific marketing campaigns of advertising and personal recommendations, and any further recommendation algorithms. http://www.informingscience.org/Publications/4310 recommendation banner product similarity association rule eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-06-07 14 183 198 4358 article Uzoma Heman Ononye ononye.uz@gmail.com Anthony Igwe igweunec@yahoo.com Aim/Purpose: This study investigates the relationship between knowledge sharing process and innovation success with specific emphasis on tacit knowledge. Based on the literature review, we hypothesised that knowledge donating and collecting have a positive relationship with innovation success. Methodology: The hypotheses were empirically tested using the partial least square path modelling with data collected from twelve state-owned public organisations operating in Southern Nigeria. Contribution: The research made distinct empirical contributions to the burgeoning literature on knowledge sharing and innovation from the public sector and developing country context. Findings: Knowledge donating and collecting contribute to innovation success positively and significantly. Knowledge donating effect on innovation success was found to be more significantly positive than the effect of knowledge collecting on innovation success. Recommendations for Practitioners: Public organisations should promote a supportive culture to spur innovation through the frequent share of experiences, information and skills among the various knowledge actors. Public managers should convey the importance of knowledge sharing and its value to knowledge users in clear terms and attend to creating conditions or contexts that encourage people to share knowledge freely and willingly with others. It is apt to improve organisational commitment and support for knowledge sharing activities such as mentorship programs, workshops, conferences, seminars and other related training and development programs in order to provide opportunities for employees to develop innovation competencies from the transfer of tacit knowledge developed over time from experience. To optimise innovation outcomes from knowledge sharing practices, knowledge sharing should be in tandem with the industry or global best practices. Future Research: Future studies should add interviews to provide depth in terms of insights and substance to the questionnaire, and may extend to public organisation with different ownership structure. http://www.informingscience.org/Publications/4358 tacit knowledge knowledge sharing knowledge donating knowledge collecting innovation success eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-06-10 14 199 234 4340 article Kenneth Chukwujioke Agbim kennethagbim2012@gmail.com Anthony Igwe igweunec@yahoo.com Aim/Purpose: This study seeks to investigate if participation in business association’s programs through the traditional and new media platforms influences family businesses in South Eastern Nigeria to diversify into similar or different businesses. Background: Before the advances in information and communication technology, businesses were carried on via the traditional media. The application of these advances has changed the way business communications and transactions are conducted globally in both family and non-family businesses. Businesses are adapting to today’s turbulent environment by opening similar or different businesses in the same or different locations that are hinged on the traditional and new media platforms. Nigerians are largely involved in social network through the traditional (face-to-face contact) and new media (e.g., Facebook, WhatsApp, Twitter, YouTube and Instagram). Moreover, in spite of the commonplaceness of family businesses in Nigeria, these businesses still experience weak diversification, bankruptcy and loss of socio-emotional wealth. Consequent upon the foregoing, this paper specifically investigates if involvement in social network via the traditional media (i.e., participation in business association’s meetings, workshops, seminars) and the new media (i.e., participation in the business association’s interactive sessions on trending business issues through the association’s online social platform like WhatsApp, Twitter), influence family businesses in South Eastern Nigeria to diversify into similar or different businesses. Methodology: The study adopted a qualitative methodology. The qualitative data were generated via interview involving 30 purposively selected businesses from South Eastern Nigeria. This comprises 15 family businesses each that have respectively adopted related and unrelated diversification strategies. Two respondents (i.e., the business owner and a top level manager) each were drawn from the selected businesses. In all, 60 respondents were interviewed. Since the unit of analysis is the family business, the interview transcriptions from all the respondents were subjected to thematic content analysis on the basis of the family businesses. Contribution: Active involvement and participation in all the meetings, discussions, workshops and seminars of the social network via the traditional and new media platforms facilitates the adoption of related or unrelated diversification in family businesses. Moreover, the adoption of similar social network platforms like WhatsApp and Twitter in all the relationships among and between employees and managers, and the transactions of the businesses is one of the key factors for achieving successful related or unrelated diversification in family businesses. Findings: In spite of the risky nature of the business environment, the adoption of related diversification strategies is significantly influenced by resources such as business consultancy services garnered through the traditional and new media platforms of the social network. Also, family businesses that are actively involved in a social network where the actors interact through the traditional and new media are influenced by the resources acquired to consider adopting unrelated diversification. These resources include: better understanding of the nature of business challenges, environments and experiences; and different lines of businesses. Thus, the traditional and new media platforms are complementary in their roles. Recommendations for Practitioners: Family business owner-managers could use the findings to develop related or unrelated strategies for diversifying into existing or new markets. This can be through the localization of manufacturing plant, improvement of product packaging, sitting of sales outlet closer to the consumers, introduction of lower prices for products/services, introduction of new and better ways of service delivery, or development of more compelling promotion strategies. Recommendation for Researchers: As a veritable guide, this study could guide future researchers in the formulation of their objectives, selection of instrument for data collection and respondents, and adoption of method of data analysis. Impact on Society: Successful diversification suggests the establishment of new or more businesses. Consequently, these new or more family businesses are expected to translate to more employment opportunities and by extension reduction in unemployment and poverty rates in the society. Future Research: Further studies should be carried out to enhance the development of family businesses, contribute to the existing literature and ensure the generalization of the findings. http://www.informingscience.org/Publications/4340 family business social network unrelated diversification strategy related diversification strategy eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-09-06 14 235 252 4427 article Abed Al-Fatah A. Karasneh akarasneh@yu.edu.jo Aim/Purpose: The purpose of this study is to investigate the relationship between knowledge management (KM) and organizational innovation (OI). It also enriches our understanding of the mediating effect of organizational learning (OL) in this relationship. Background: KM’s relationship with OL and OI has been tackled extensively in developed countries’ literature. Nowadays, the challenges of developing countries lie in the process of knowledge application. This study attempts to develop a new managerial knowledgeable tool and present a theoretical model and empirical analysis of the relationship between KM and innovation in Jordan, a developing country. To the knowledge of the author, no attempt has been taken to investigate this relationship in any Jordanian sector. Methodology: The sample of this study consists of 457 managers representing strategic, tactical, and operational levels randomly selected from 56 manufacturing companies in Jordan. A questionnaire-based survey has been developed based on KM, OL and OI literature to collect data. A structural equation modeling (SEM) approach was applied to investigate the proposed research model. Contribution: This study contributes to the literature in different ways. First, it asserts that OL assists in improving OI in manufacturing organization of developing countries. Second, it highlights the substantial benefits of applying KM, OL and OI in manufacturing companies in Jordan. Furthermore, it enhances the relationship between KM and innovativeness’ literature by providing empirical evidence, suggesting that OL is as important as KM to advance organizational innovation. Most importantly, it identifies the problem of a developing economy which is not promoting OL or taking care of it as much as they attended to KM in their organizational practices. Findings: Study findings indicate that the relationship between KM and OI is significantly positive. Results also reveal that the relationship between KM and organizational learning is significantly positive. Empirical results emerging from this study indicate that there is partial mediation to support the relationship between OL and OI. Recommendations for Practitioners: This study suggests that managers ought to recognize that organizational learning is equally important to KM. This entails that OL should be utilized within organizations to achieve organizational innovation. Moreover, managers ought to comprehend their importance and encourage their employees to adopt knowledge from various sources; which, if implemented correctly, will enhance the OL environment. Recommendation for Researchers: The research model can be used or applied in different manufacturing and service sectors across the globe. The findings of the current study can serve as a foundation to perform different studies to understand KM processes and recognize its antecedence. Impact on Society: This study presents insights on how to apply KM, OL and OI methodologies in Jordanian manufacturing companies to achieve a competitive advantage; hence, positively influencing society. Future Research: Future research may include conducting a similar study in the context of developed countries and developing countries which allows for comparison. Also, future research may examine the impact of KM on organizational performance applying both OL and OI as mediating variables. http://www.informingscience.org/Publications/4427 knowledge management organizational learning organizational innovation Jordanian manufacturing companies eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-09-09 14 253 276 4429 article Rana Nabeel-Rehman nabeel_um@hotmail.com Mohammad Nazri Akzy333@gmail.com Aim/Purpose: Despite the fact that the plethora of studies demonstrate the positive impact of information technology (IT) capabilities on SMEs performance, the understanding of underlying mechanisms through which IT capabilities affect the firm performance is not yet clear. This study fills these gaps by explaining the roles of absorptive capacity and corporate entrepreneurship. The study also elaborates the effect of IT capability dimensions (IT integration and IT alignment) upon the SMEs performance outcomes through the mediating sequential process of absorptive capacity and corporate entrepreneurship. Methodology: This study empirically tests a theoretical model based on the Dynamic Capability View (DCV), by using the partial least square (PLS) technique with a sample of 489 manufacturing SMEs in Pakistan. A survey is employed for the data collection by following the cluster sampling approach. Contribution: This research contributes to the literature of IT by bifurcating the IT capability into two dimensions, IT integration and IT alignment, which allows us to distinguish between different sources of IT capabilities. Additionally, our findings shed the light on the dynamic capability view by theoretically and empirically demonstrating how absorptive capacity and corporate entrepreneurship sequentially affect the firms' performance outcomes. At last, this study contributes to the literature of SMEs by measuring the two levels of performance: innovation performance and firm performance. Findings: The results of the analysis show that the absorptive capacity and the corporate entrepreneurship significantly mediate the relationship between both dimensions of IT capability and performance outcomes. http://www.informingscience.org/Publications/4429 information technology capabilities IT integration IT alignment absorptive capacity corporate entrepreneurship innovation performance firm perfor-mance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-09-19 14 277 294 4386 article Dwi Suhartanto dwi.suhartanto@polban.ac.id David Dean david.dean@lincoln.ac.nz Gundur Leo gundur.leo@polban.ac.id Ni Nyoman Triyuni triyuni_gora@yahoo.com Aim/Purpose: To examine millennial satisfaction towards online food delivery services, including e-service quality, food quality, and perceived value as the determinants and behavioral intention as the consequence. Background: Among the generational cohorts, millennials are a demanding target group for many retailers, including restaurants. Despite many studies examining millennial behavior in the restaurant context, almost no research on millennial attitudes and behavior in the context of online food home delivery service can be found. Methodology: For this research, 332 millennials completed a self-administered survey in Indonesia. To assess the associations between satisfaction and its determinants and consequences, this study employs Partial Least Square modeling. Contribution: This research extends existing knowledge of millennial satisfaction toward online food delivery service by highlighting that food quality, e-service quality and perceived value are the main determinants of satisfaction for online food purchasing among millennials. Further, this study offers support for the spillover theory in the online food home delivery service from millennial perspective. Findings: This study uncovers the important direct dual influences of e-service quality and food quality on millennial satisfaction with online food delivery services. Further, this study notes that e-service and food quality also have an indirect influence on satisfaction via perceived value. Moreover, satisfied millennial customers are more likely to re-purchase, recommend to others, and re-purchase at an increased price. Recommendations for Practitioners: For small and medium restaurants, it is suggested that they need to focus solely on their core business of providing food. If they want to offer an e-service, they should develop strategic cooperation with one or more online service providers. Recommendation for Researchers: Millennials tend to repurchase, recommend, and be willing to pay more in the future extends the existing models that look at the associations among quality, satisfaction and behavioral intention. Thus, in online restaurant purchasing services, both e-service quality and food quality should be included in the future research models. Impact on Society: This study could help restaurant industries to increase their business performance and, indirectly, impact on society as a whole by providing high quality food, employment opportunities, and tax revenues. Future Research: Future researchers can reassess the model in different countries and/or with other generation cohorts as well as including other variables such as trust, image, involvement, as well as socio-demographic factors. http://www.informingscience.org/Publications/4386 millennial satisfaction online food home delivery service eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-09-26 14 295 324 4438 article Ahmad Samed Al-Adwan a.adwan@ammanu.edu.jo Aim/Purpose: This study aims to identify the main factors influencing consumers’ adoption of social commerce (s-commerce). Based on the socio-technical theory, the study suggests a research model that investigates the key social and technical factors driving consumers’ decision to purchase from social commerce websites. In addition, the research model explores the interactive relationship among these factors. Background: The phenomenon of social commerce (s-commerce) has emerged due to the increased penetration of social media and the rapid development of Web 2.0 technologies. Electronic commerce (e-commerce) companies have made significant efforts to shift their operations to s-commerce. Therefore, to facilitate their efforts to transform, various research has been conducted to investigate the main factor influencing the adoption of s-commerce. Most of these studies have emphasised the social aspects related to s-commerce design features to understand how the use of advanced web technologies influence how customers interact with each other in s-commerce environments. However, s-commerce is viewed as a socio-technical system that requires the investigation of both social and technical factors to help in the design of effective s-commerce platforms. Methodology: To validate the proposed research model, 418 paper-based and online questionnaires were collected from online shoppers in Jordan. The Structure Equation Modelling (SEM) approach was used to test the proposed hypotheses. Contribution: This study offers a research model that serves as a theoretical framework for investigating customers’ behaviour in s-commerce environment. It represents a strong context-specific model that includes both the technical and social facilitators of s-commerce. The research model participates in gaining an improved understanding of how customers’ intention, actual purchase and post-purchase experience are formed in the s-commerce environment. Findings: The results of Structure Equation Modelling (SEM) reveal that s-commerce constructs, familiarity and user experience have a positive influence on the perceived usefulness and perceived ease of use of s-commerce. In addition, perceptions of its usefulness and ease of use have a positive influence on trust, which in turn influences the purchase intention and the actual purchase. Finally, the post-purchase experience significantly influences both trust and purchase intention. Recommendations for Practitioners: This study shows that social commerce constructs strengthen customers’ perceptions of usefulness. S-commerce service providers are required to provide their customers with various channels to seek social support. Both familiarity and user experience are key enablers of customers’ perceived ease of use. S-commerce service providers consider the variation in customers’ familiarity and experience with s-commerce websites because this has a significant influence on purchase intentions and behaviour. Consequently, system designers should offer useful and sufficient information and tutorials that effectively guide customers in their searching, decision-making and purchasing activities throughout the shopping process. S-commerce service providers should understand the importance of providing secure payment systems and make their privacy policies clear to customers. Post-purchase experience has an influential role in reinforcing customers’ trust and purchase intention. The findings confirm the important role of post-purchase experience in retaining customers by improving their trust and repurchase intention. Therefore, making a customer’s post-purchase experience pleasant should be a key priority for s-commerce service providers because it has a significant influence on customers’ trust and repurchase intentions. Recommendation for Researchers: This study offers a unidimensional conceptualisation of the design features of s-commerce. These features include three main forms: recommendations and referrals, communities and forums, and reviews and ratings. Such conceptualisation provides additional insights and an understanding of the activities of information sharing in s-commerce. The significance of the technical side of s-commerce is highlighted and empirical proof is provided that social interactions guided by social technologies enhance customers’ perceived usefulness of an s-commerce website, thus increasing their trust and intention to purchase which leads to an actual purchase. This offers insights into the various types of s-commerce characteristics that contribute to facilitating customers’ purchase behaviour on s-commerce websites. Impact on Society: The findings offer insights which have important implications for research and practice to help facilitate the adoption of s-commerce. Future Research: This study considered the s-commerce websites as a homogenous online environment. Additional research could collect data from diverse online communities, such as professional groups, to provide a comprehensive understanding of how a wider variety of user behaviour is affected. Second, this was a quantitative study based on data collected in a questionnaire. Further studies may consider using qualitative or mixed methodologies (i.e. focus groups and interviews) to explore other technical and social factors that influence the use of s-commerce. http://www.informingscience.org/Publications/4438 social commerce trust e-commerce post purchase experience familiarity perceived usefulness perceived ease of use TAM eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-10-18 14 325 341 4445 article Salah Kabanda salah.kabanda@uct.ac.za Fernanda Matsinhe nandamatsinhe@gmail.com Aim/Purpose: This study explores how women-led SMMEs in developing countries, specifically in the Mozambican context, institutionalise e-commerce by focusing on the ongoing interaction between the SMME, its context, and process of e-commerce institutionalization. Background: It is believed that institutionalization of e-commerce provides significant benefits of unlimited access to new markets, and access to new, improved, inexpensive and convenient operational methods of transacting. Although prior studies have examined the adoption of e-commerce and the enabling and constraining factors, few have examined e-commerce (i) institutionalization (that is, post-adoption), and (ii) from a gender perspective. This study aims to respond to this paucity in the literature by exploring how women-led SMMEs in developing countries, specifically in the Mozambican context, institutionalise e-commerce. Methodology: The study follows a qualitative inquiry approach for both data collection and analysis. Semi-structured interviews were adopted for data collection and thematic analysis implemented on the data. SMMEs were purposively sampled to allow for the selection of information-rich SMMEs for study and specifically those that have gone through the experience of adoption and in some cases have institutionalized e-commerce. Contribution: The empirical findings explain how the institutionalization process from interactive e-commerce to transactive e-commerce unfolds in the Mozambican context. Findings: Transition from interactive to transactive e-commerce is firstly influenced by (i) the type of business the SMME is engaged in; and (ii) customer and trading partner’s readiness for e-commerce. Secondly, the transition process is influenced by the internal factors of (i) manager’s demographic factors; (ii) mimetic behaviour arising from exposure to (foreign) organizations in the same industry that have mature forms of e-commerce; (iii) the business networks developed with some of these organizations that have mature forms of e-commerce; (iv) access to financial resources; and (v) social media technologies. Thirdly, the process is influenced by external contextual factors of (i) limited government intervention towards e-commerce endeavors; (ii) limited to lack of financial institutions readiness for e-commerce; (iii) lack of local available IT expertise; (iv) consumer’s low purchasing power due to economic recessions; (vi) international competitive pressure; and (vii) sociocultural practices. Recommendations for Practitioners: The study provides SMME managers, practitioners, and other stakeholders concerned with women’s development with a better understanding of the process in order to develop appropriate policies and interventions that are suitable for the reality of women-led SMMEs in Mozambique and other developing countries with similar contextual characteristics. Recommendation for Researchers: The study contributes to the existing debate of e-commerce and the use of ICT for development in developing countries by providing a distinct contribution of the institutionalization process and how the contextual structures influence this process. Impact on Society: Women-led SMME managers can learn from the different experiences, and compare their e-commerce efforts with SMMEs that were able to institutionalize and make strategies for improvements within their organizations. Future Research: The manner in which women-led SMMEs employ e-commerce requires further investigation to understand how issues related to gender, the cultural context, and different regions or countries impact this process. http://www.informingscience.org/Publications/4445 small micro and medium enterprises (SMMEs) contextualist inquiry e-commerce developing countries eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-10-20 14 343 366 4420 article Dinakaran Muruganantham dinakaran.m@vit.ac.in Atilla Elçi atilla.elci@gmail.com SenthilKumar Narayanasamy senthilkumar.n@vit.ac.in Aim/Purpose: Vis-à-vis management of crisis and disaster situations, this paper focuses on important use cases of social media functions, such as information collection & dissemination, disaster event identification & monitoring, collaborative problem-solving mechanism, and decision-making process. With the prolific utilization of disaster-based ontological framework, a strong disambiguation system is realized, which further enhances the searching capabilities of the user request and provides a solution of unambiguous in nature. Background: Even though social media is information-rich, it has created a challenge for deriving a decision in critical crisis-related cases. In order to make the whole process effective and avail quality decision making, sufficiently clear semantics of such information is necessary, which can be supplemented through employing semantic web technologies. Methodology: This paper evolves a disaster ontology-based system availing a framework model for monitoring uses of social media during risk and crisis-related events. The proposed system monitors a discussion thread discovering whether it has reached its peak or decline after its root in the social forum like Twitter. The content in social media can be accessed through two typical ways: Search Application Program Interfaces (APIs) and Streaming APIs. These two kinds of API processes can be used interchangeably. News content may be filtered by time, geographical region, keyword occurrence and availability ratio. With the support of disaster ontology, domain knowledge extraction and comparison against all possible concepts are availed. Besides, the proposed method makes use of SPARQL to disambiguate the query and yield the results which produce high precision. Contribution: The model provides for the collection of crisis-related temporal data and decision making through semantic mapping of entities over concepts in a disaster ontology we developed, thereby disambiguating potential named entities. Results of empirical testing and analysis indicate that the proposed model outperforms similar other models. Findings: Crucial findings of this research lie in three aspects: (1) Twitter streams and conventional news media tend to offer almost similar types of news coverage for a specified event, but the rate of distribution among topics/categories differs. (2) On specific events such as disaster, crisis or any emergency situations, the volume of information that has been accumulated between the two news media stands divergent and filtering the most potential information poses a challenging task. (3) Relational mapping/co-occurrence of terms has been well designed for conventional news media, but due to shortness and sparseness of tweets, there remains a bottleneck for researchers. Recommendations for Practitioners: Though metadata avails collaborative details of news content and it has been conventionally used in many areas like information retrieval, natural language processing, and pattern recognition, there is still a lack of fulfillment in semantic aspects of data. Hence, the pervasive use of ontology is highly suggested that build semantic-oriented metadata for concept-based modeling, information flow searching and knowledge exchange. Recommendation for Researchers: The strong recommendation for researchers is that instead of heavily relying on conventional Information Retrieval (IR) systems, one can focus more on ontology for improving the accuracy rate and thereby reducing ambiguous terms persisting in the result sets. In order to harness the potential information to derive the hidden facts, this research recommends clustering the information from diverse sources rather than pruning a single news source. It is advisable to use a domain ontology to segregate the entities which pose ambiguity over other candidate sets thus strengthening the outcome. Impact on Society: The objective of this research is to provide informative summarization of happenings such as crisis, disaster, emergency and havoc-based situations in the real world. A system is proposed which provides the summarized views of such happenings and corroborates the news by interrelating with one another. Its major task is to monitor the events which are very booming and deemed important from a crowd’s perspective. Future Research: In the future, one shall strive to help to summarize and to visualize the potential information which is ranked high by the model. http://www.informingscience.org/Publications/4420 disaster management social media ontological support semantic search SPARQL RDF eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2019-11-03 14 367 403 4447 article Omar Hasan Salah omar_salah79@hotmail.com Prof.Dr. Zawiyah Mohammad Yusof zawiy@ukm.edu.my Dr.Hazura Mohamed hazura.mohamed@ukm.edu.my Aim/Purpose: This study aimed to examine the relationships among compatibility, relative advantage, complexity, IT Infrastructure, security, top Management Support, financial Support, information Policies, employee engagement, customer pressure, competitive pressure, information integrity, information sharing, attitude toward adopting technology factors, and CRM adoption Background: Customer relationship management (CRM) refers to the use of the process, information, technology, and people for the management of the interactions between the organization and its customers. Therefore, there is a need for SMEs to implement CRM practices in their businesses for competitive advantage. However, in developing nations, the adoption rate of such practices remains low. This low rate may be attributed to the lack of important factors that guide CRM adoption, and as such, the present study attempts to investigate the factors affecting CRM adoption in Palestinian SMEs. This paper used the Diffusion of Innovation Theory (DOI), Resource-Based View (RBV), and Technology, Organization, and Environment Framework (TOE) framework to identify the determinant factors from the technological, organizational, environmental, and information culture perspectives. Methodology: This study uses a quantitative approach to investigate the relationships between the variables. A questionnaire was designed to collect data from 420 SMEs in Palestine. 331respondents completed and returned the survey. The Partial Least Square-Structural Equation Model (PLS-SEM) approach was used to assess both the measurement and structural models. Contribution: This study contributes to both theory and practitioners by providing insights into factors that affect CRM adoption in Palestinian SMEs, which did not explore before. Future research suggestions are also provided. Findings: The results of the study prove that the adoption of CRM depends on compatibility (CMP), security (SEC), top management support (TMS), information policies (INP), financial resources (FR), employee engagement (EEN), competitive pressure (COP), customers pressure (CUP), attitude toward adopting technology (ATA), information integrity (INI), and information sharing (INS). Surprisingly, complexity (CMX), IT infrastructure (ITI), and relative advantage (RLA) do not play any role in CRM adoption in Palestine. Recommendations for Practitioners: This study provides practitioners with the important factors for CRM adoption upon its successful implementation in the context of Palestinian SMEs. Recommendation for Researchers: Our findings may be used to conduct further studies about compatibility, security, top management support, information policies, financial resources, employee engagement, competitive pressure, customers pressure, attitude toward adopting technology, information integrity, information sharing factors, and CRM adoption by using different countries, procedure, and context. Impact on Society: The proposed framework provides insights for SMEs which have significant effects for research and practice to help facilitate the adoption of CRM Future Research: The findings may also be compared to other studies conducted in different contexts and provide deeper insights into the influence of the examined contexts on the employees’ intention toward CRM adoption in banking and universities. It would be fruitful to test whether the results hold true in developed and developing countries. http://www.informingscience.org/Publications/4447 customer relationship management system small and medium enterprise CRM adoption Palestine eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-01-28 13 . i iii 3945 article Geoffrey Z. Liu Geoffrey.Liu@sjsu.edu June Lu luj@uhv.edu http://www.informingscience.org/Publications/3945 IJIKM contents eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-01-28 13 001 020 3940 article Abdoulaye Kaba kaba_abdoulaye@yahoo.com Chennupati K. Ramaiah chennupati_kramaiah@yahoo.com Aim/Purpose: This study investigates the issue of knowledge acquisition among faculty members. Background: The paper reports the use of knowledge acquisition tools and reading knowledge sources by faculty members. It also identifies demographic differ-ences among participants in using knowledge acquisition tools and reading knowledge sources. Methodology: The study used an online survey-based questionnaire tool for data collection. The participants consisted of 300 faculty members from 26 academic institu-tions in UAE. Statistical tests are used to verify and validate the hypotheses. Contribution: The paper represents one of the few empirical studies conducted on knowledge acquisition among faculty members in the GCC countries. Find-ings of the study may contribute to the theoretical and practical understanding of knowledge acquisition among faculty members. Findings: Findings of the study revealed that medical faculty members read knowledge acquisition sources more than other faculty members. Likewise, IT faculty members use knowledge acquisition tools more than other faculty members. Results of the study supported stage three of knowledge acquisition proposed in the “Stage Theory of Knowledge Consumption Growth” (Mathew, 1985). The study found that journals are the most sources read by the participants while web-based training (WBT) tools are the most used knowledge acquisition tools among faculty members. Results of the study indicated significant differ-ences among faculty members of different age groups, academic ranks, aca-demic specializations, and institutional affiliation in reading knowledge sources. Likewise, findings of the study revealed significant difference among partici-pants of different academic specializations in using knowledge acquisition tools. Recommendations for Practitioners: Results of the study could be extrapolated to other faculty members in the GCC countries. Recommendation for Researchers: More researches could be done to address different issues of knowledge acquisition among faculty members. Impact on Society: Faculty reading of knowledge sources and use of knowledge acquisition tools may have direct or indirect positive impacts on innovation, creativity, and re-search productivity in any society. Future Research: It will be interesting to apply more than one data collection method in the future research. http://www.informingscience.org/Publications/3940 knowledge knowledge sources knowledge acquisition tools faculty members universities colleges UAE eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-02-10 13 021 044 3942 article Ashraf Ahmed Fadelelmoula asahfaab@gmail.com Aim/Purpose: The aim of this study is to examine empirically the effects of certain key Critical Success Factors (CSFs) for the implementation of Enterprise Resource Planning (ERP) Systems on the comprehensive achievement of the crucial roles of Computer-Based Information Systems (CBISs) Background: The effects of the CSFSs were examined in the higher education sector in the Kingdom of Saudi Arabia (KSA) using a case study of the ERP adoption in Prince Sattam Bin Abdulaziz University. Methodology: A theoretical model was proposed based on the literature written on the CSFs and the roles of CBISs in business. The model encompasses six key CSFs and their associations with the realization of the crucial roles of CBISs. To test the proposed model, a questionnaire was developed by considering the most frequently used measurements items in the ERP’s literature. The data were collect-ed from 219 key stakeholders. Contribution: This study acts as one of the few empirical studies in assessing the effects of the important CSFs for ERP implementation upon its successful implementation. Its outcomes provide more insights and clarifications about the effects of six key CSFs on the comprehensive achievement of the crucial CBIS’s roles. Particularly, the uniqueness of this study lies in addressing the effects of these CSFs on the achievement of the vital CBIS’s roles collectively rather than the achievement of each role individually. Moreover, the study examined these effects in the higher education environment, which is characterized by its own special business processes and services. Findings: The results reveal that the six key CSFs have a positive relationship with the comprehensive achievement of the crucial roles of CBISs. These findings are consistent with many previous studies on the effects of the CSFs on the realization of the expected benefits of the enterprise systems. Recommendations for Practitioners: The managers and other key stakeholders should carefully manage the vital aspects of the CSFs in order to realize the promised ERP’s benefits, including the CBIS’s roles. Future Research: Additional empirical examinations are needed to investigate the effects of the rest of the CSFs on realizing the roles of information systems. http://www.informingscience.org/Publications/3942 enterprise resource planning critical success factors ERP implementation comprehensive achievement of the CBIS’s roles eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-03-04 13 045 060 3964 article Abdul Waheed abdulwaheed168@yahoo.com Jianhua Yang yangjh@ustb.edu.cn Jon K. Webber drjonwebber@gmail.com Aim/Purpose: The current study investigates the relationship between mobile and email marketing and consumer impulse buying tendencies in Pakistan. Background: Technology has become a primary driver for all business operations, which has dramatically transformed the wireless communications marketing paradigm. However, researchers have claimed that further inquiry is still needed to explore the role that distinct and emerging global technologies have on marketing communication strategies. This study explores the linkage of mobile and email marketing on consumers’ impulse buying behavior in Pakistan. Methodology: Primary data were collected through the distribution of 1000 questionnaires among students of different universities within two provinces of Pakistan: Punjab and Khyber Pakhton Khan (KPK). The study was conducted between November 2016 and March 2017. The authors received back 950 surveys, which is a very significant rate of return (95%). Of those submitted, 900 surveys were deemed eligible for analysis after improper documents were eliminated. Structure equation modeling (SEM) was utilized to test the study’s hypotheses. Contribution: This study assists organizations in improving marketing campaigns by focusing more on mobile devices (m-devices) and email medium to better comprehend consumers’ assessment processes at a lower budgetary cost. Such digital considerations could provide innovative possibilities for marketers in approaching their target market by adopting novel methods for information sharing. Findings: The findings revealed a positive association between mobile and email marketing on consumers’ impulse buying tendencies. The comprehensive analysis affirmed; however, there is a higher positive relationship of mobile marketing results compared to email marketing outcomes. There are favorable benefits in considering such emerging methods in marketing communications as promotional strategies are considered by organizations. Recommendations for Practitioners: Marketers are encouraged to evaluate the potential of using both emerging mediums to take advantage of consumer impulse buying habits where m-devices and emails approaches are utilized. Future Research: Future inquiries might examine the global influence of m-devices and email technology toward other buying tendencies of consumers: exploratory, online, variety seeking, habitual, and other emerging complex on-demand buying behavior. http://www.informingscience.org/Publications/3964 marketing communications mobile marketing email marketing impulse buy-ing tendencies Islamic Republic of Pakistan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-03-15 13 061 077 3975 article Lanto Ningrayati Amali ningrayati_amali@ung.ac.id Muhammad Rifai Katili mrifaikatili@ung.ac.id Aim/Purpose: This study is carried out to determine the factors influencing the implementation of IT governance in public sector. Background: IT governance in organizations plays strategic roles in deciding whether IT strategies and investments of both private and public organizations could be efficient, consistent, and transparent. IT governance has the potential to be the best practice that could improve organizational performance and competency. Methodology: The study involves qualitative and quantitative approaches, where data were collected through questionnaire, observation, interview, and document study through a sample of 367 respondents. The collected data were analyzed using Structured Equation Modeling (SEM) for validating the model and testing the hypotheses. Besides, semi-structured interview, observation, and document study were also carried out to obtain the management’s feedback on the implementation of IT governance and its activities. Contribution: The results of this study contribute to knowledge regarding good IT governance. Practically, this study can be used as a guideline for the future development and good IT governance. Findings: The findings reveal that policy has a significant direct influence on system planning, the management of IT investment, system realization, operation and maintenance, and organizational culture. The existence of IT governance policies, the success of the IT process can work well. Monitoring and evaluation processes also significantly affect system plan-ning, management of IT investment, system realization, operation and maintenance, and organizational culture. It indicates the process of monitoring and evaluation required for indications of financial efficiency, infrastructure, resources, risk and organizational success. Recommendations for Practitioners: It is important for organizational management to pay more attention to the organization’s internal controls in order to create good IT governance. Recommendation for Researchers: A comparative study between Indonesia and developing countries on the implementation of IT governance is needed to capture the differences be-tween those countries. Impact on Society: Knowledge of the factors influencing the implementation of IT governance as an effort to implement and improve the quality of IT governance. Future Research: Future studies should look further at the policy and IT governance models, specifically in public organizations, besides other influencing factors. Moreover, the outcome of this study could be generated as a guideline for the advanced development of IT governance and as a point of improvement as a way to generate a better good IT governance. It is essential because such evidence is lacking in current literature. http://www.informingscience.org/Publications/3975 IT governance process public organizations eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-05-28 13 079 094 4063 article Boniface K Alese bkalese@futa.edu.ng Olufunso Dayo Alowolodu odalowolodu@futa.edu.ng Aderonke Favour-Bethy Thompson afthompson@futa.edu.ng Blessing Emmanuel Oladele blessemol@gmail.com Aim/Purpose: The wide use of online banking and technological advancement has attracted the interest of malicious and criminal users with a more sophisticated form of attacks. Background: Therefore, banks need to adapt their security systems to effectively stem threats posed by imposters and hackers and to also provide higher security standards that assure customers of a secured environment to perform their financial transactions. Methodology : The use of authentication techniques that include the mutual secure socket layer authentication embedded with some specific features. Contribution: An approach was made through this paper towards providing a more reliable and complete solution for implementing multi-level user authentication in a banking environment. Findings: The use of soft token as the final stage of authentication provides ease of management with no additional hardware requirement. Recommendations for Practitioners : This work is an approach made towards providing a more reliable and complete solution for implementing multi-level user authentication in a banking environment to stem cybercrime. Recommendation for Researchers: With this approach, a reliable system of authentication is being suggested to stem the growing rate of hacking activities in the information technology sector. Impact on Society :This work if adopted will give the entire populace confidence in carrying out online banking without fear of any compromise. Future Research: This work can be adopted to model a real-life scenario. http://www.informingscience.org/Publications/4063 multilevel-security authentication soft-token cybercrime eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-05-30 13 095 115 4067 article Ewa Wanda Ziemba ewa.ziemba@ue.katowice.pl Monika Eisenbardt monika.eisenbardt@ue.katowice.pl Aim/Purpose: The main purpose of this paper is to answer the research question whether the ways in which prosumers share their knowledge with enterprises and public organizations are in line with the ways in which enterprises and public organizations expect them to get engaged in knowledge sharing. Background: Contemporary consumers do not wish to be passive consumers anymore. They want to satisfy their consumption needs by products’ evaluation, co-designing, co-creation and co-reconfiguration. They can do that by sharing their knowledge with enterprises and public organizations. Such consumers are referred as ‘prosumers’. Methodology: The research process consisted of a survey among prosumers and online observations of enterprises and public organizations. A final research sample includes 388 prosumers and 90 organizations. Contribution: This work contributes to existing research on utilizing consumers’ knowledge in business and public organizations by identifying and examining ways of consumers’ knowledge sharing with such organizations. Findings: It was found that there are differences between the ways in which prosumers share knowledge with organizations in comparison with the ways in which enterprises and public organizations expect them to get engaged in knowledge sharing. Prosumers mainly share their knowledge by evaluating products, whereas organizations mainly expect prosumers to get engaged in knowledge sharing by creating and designing products. In addition, it was found that enterprises have bigger expectations as to prosumers’ engagement in knowledge sharing than public organizations. Recommendations for Practitioners: This study provides practitioners with guidelines for prosumers’ knowledge utilization, especially helping them understand which ways prosumers use to share knowledge. Recommendation for Researchers: Researchers may consider the findings of the current study useful to conduct further research on customer knowledge sharing with organizations using our approach and developing own research contexts. Future Research: This study examines Polish prosumers and organizations operating in the Polish market. It is advisable to extend the research to other countries and compare the results. http://www.informingscience.org/Publications/4067 knowledge knowledge sharing prosumer prosumption consumer product evaluation product co-creation eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-06-05 13 117 135 4066 article M. Thangaraj thangarajmku@yahoo.com M Sivakami sivakamimk@gmail.com Aim/Purpose: The aim of this paper is to analyze various text classification techniques employed in practice, their strengths and weaknesses, to provide an improved awareness regarding various knowledge extraction possibilities in the field of data mining. Background: Artificial Intelligence is reshaping text classification techniques to better acquire knowledge. However, in spite of the growth and spread of AI in all fields of research, its role with respect to text mining is not well understood yet. Methodology: For this study, various articles written between 2010 and 2017 on “text classification techniques in AI”, selected from leading journals of computer science, were analyzed. Each article was completely read. The research problems related to text classification techniques in the field of AI were identified and techniques were grouped according to the algorithms involved. These algorithms were divided based on the learning procedure used. Finally, the findings were plotted as a tree structure for visualizing the relationship between learning procedures and algorithms. Contribution: This paper identifies the strengths, limitations, and current research trends in text classification in an advanced field like AI. This knowledge is crucial for data scientists. They could utilize the findings of this study to devise customized data models. It also helps the industry to understand the operational efficiency of text mining techniques. It further contributes to reducing the cost of the projects and supports effective decision making. Findings: It has been found more important to study and understand the nature of data before proceeding into mining. The automation of text classification process is required, with the increasing amount of data and need for accuracy. Another interesting research opportunity lies in building intricate text data models with deep learning systems. It has the ability to execute complex Natural Language Processing (NLP) tasks with semantic requirements. Recommendations for Practitioners: Frame analysis, deception detection, narrative science where data expresses a story, healthcare applications to diagnose illnesses and conversation analysis are some of the recommendations suggested for practitioners. Recommendation for Researchers: Developing simpler algorithms in terms of coding and implementation, better approaches for knowledge distillation, multilingual text refining, domain knowledge integration, subjectivity detection, and contrastive viewpoint summarization are some of the areas that could be explored by researchers. Impact on Society: Text classification forms the base of data analytics and acts as the engine behind knowledge discovery. It supports state-of-the-art decision making, for example, predicting an event before it actually occurs, classifying a transaction as ‘Fraudulent’ etc. The results of this study could be used for developing applications dedicated to assisting decision making processes. These informed decisions will help to optimize resources and maximize benefits to the mankind. Future Research: In the future, better methods for parameter optimization will be identified by selecting better parameters that reflects effective knowledge discovery. The role of streaming data processing is still rarely explored when it comes to text classification. http://www.informingscience.org/Publications/4066 classification machine learning statistical methods analysis eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-07-02 13 137 163 4083 article Ruben Pereira ruben.filipe.pereira@iscte.pt João Aguiar joaofaguiar@gmail.com José Braga Vasconcelos jose.vasconcelos@universidadeeuropeia.pt Isaias Bianchi isaias.bianchi@dsi.uminho.pt Aim/Purpose: This research aims to develop an information technology (IT) maturity model for incident management (IM) process that merges the most known IT frameworks’ practices. Our proposal intends to help organizations overcome the current limitations of multiframework implementation by informing organizations about frameworks’ overlap before their implementation. Background: By previously identifying frameworks’ overlaps it will assist organizations during the multi-framework implementation in order to save resources (human and/or financial). Methodology: The research methodology used is design science research (DSR). Plus, the authors applied semi-structured interviews in seven different organizations to demonstrate and evaluate the proposal. Contribution: This research adds a new and innovative artefact to the body of knowledge. Findings: The proposed maturity model is seen by the practitioners as complete and useful. Plus, this research also reinforces the frameworks’ overlap issue and concludes that some organizations are unaware of their actual IM maturity level; some organizations are unaware that they have implemented practices of other frameworks besides the one that was officially adopted. Recommendations for Practitioners: Practitioners may use this maturity model to assess their IM maturity level before multi-framework implementation. Moreover, practitioners are also incentivized to communicate further requirements to academics regarding multi-framework assessment maturity models. Recommendation for Researchers: Researchers may explore and develop multi-frameworks maturity models for the remaining processes of the main IT frameworks. Impact on Society: This research findings and outcomes are a step forward in the development of a unique overlapless maturity model covering the most known IT frameworks in the market thus helping organizations dealing with the increasing frameworks’ complexity and overlap. Future Research: Overlapless maturity models for the remaining IT framework processes should be explored. http://www.informingscience.org/Publications/4083 IT framework maturity model DSR incident management overlap ITIL COBIT CMMI eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-07-03 13 165 182 4080 article Kevin A. Johnston kevin.johnston@uct.ac.za Aiden J Walton WLTAID001@myuct.ac.za Aim/Purpose: This paper explored the factors (enablers and barriers) that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption. Background: In recent years, Bitcoin has seen a rapid growth as a virtual cryptocurrency throughout the world. Bitcoin is a protocol which allows value to be exchanged over the internet without a central bank or intermediary. Cryptocurrencies such as Bitcoin are technological tools that arguably can contribute to reducing transactions costs. This paper explored the factors that affect Bitcoin adoption in South Africa, a Sub-Saharan country with the high potential for Bitcoin adoption, as little is known about the factors that affect Bitcoin adoption and the barriers to adoption. Methodology: A quantitative questionnaire was distributed to South African virtual communities where Bitcoin is a topic of interest, and 237 quantitative responses were received, along with 212 open-ended comments. Contribution: This research contributes to the body of knowledge in information systems by providing insights into factors that affect Bitcoin adoption in South Africa. It raises awareness of incentives and barriers to Bitcoin adoption at a time when financial literacy is a crucial issue both in South Africa and worldwide. Findings: The results indicate that perceived benefit, attitude towards Bitcoin, subjective norm, and perceived behavioral control directly affected the participants’ intentions to use Bitcoin. Perceived benefit, usefulness, ease of use, and trust-related risk were found to indirectly affect intention to use Bitcoin. Further, it emerges that the barriers to Bitcoin adoption in South Africa consist of the complex nature of Bitcoin and its high degree of volatility. Recommendations for Practitioners: Bitcoin can contribute to reducing transactions costs, but factors that affect adoption and the barriers to adoption should be taken into consideration. These findings can inform systems and software developers to develop applications that make managing Bitcoin keys and transacting using Bitcoin less complex and more intuitive for end users. Recommendation for Researchers: Bitcoin adoption in South Africa is a topic that has not been previously researched. Researchers could research similarities or differences in the various constructs that were used in this research model. Impact on Society: South African Bitcoin users consider it as a universal currency that makes cross-border payments cheaper. A large number of refugees and workers in South Africa make regular payments across borders. Bitcoin could reduce the costs of these transfers. Future Research: Future research could explore Bitcoin (and other cryptocurrencies) adoption in other developing countries. Researchers could look at factors that influence cryptocurrency adoption in general. The factors affecting adoption of other cryptocurrencies can be compared to the results of this study, and similarities and differences can thus be identified. http://www.informingscience.org/Publications/4080 Bitcoin cryptocurrency virtual community virtual investment community South Africa eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-07-16 13 183 199 4089 article Ananda Sabil Hussein sabil@ub.ac.id Nadiyah Hirfiyana Rosita nadiyah_hr@ub.ac.id Mintarti Rahayu mintarti.rahayu@gmail.com Risca Fitri Ayuni risca.fa@gmail.com Aim/Purpose: Two research objectives were addressed in this study. The first objective was to determine the effect of knowledge management orientation behaviour on business performance, and the second objective was to investigate the mediating effect of market orientation in the relationship between knowledge management orientation behaviour and business performance. Background: In business strategic perspective, the idea of knowledge management has been discussed widely. However, there is a lack of study exploring the notion of knowledge management orientation especially in the perspective of Indonesia’s creative economy sector. Methodology: One hundred and thirty one participants were involved in this study. They were economy creative practitioners in Indonesia. Data were analysed by using Partial Least Squares. Contribution: Upon the completion of the research objectives, this study contributes to both theoretical and practical perspectives. From a theoretical standpoint, this study proposes a conceptual model explaining the relationship among knowledge management orientation behaviour, market orientation, and business performance in Indonesia’s creative economy sector. As this study found a significant effect of knowledge sharing in market orientation and market orientation in business performance, the study showed the mediation role of market orientation in the relationship between knowledge sharing and business performance. From a practical perspective, this study implies a guideline for business practitioners in enhancing business through the application of knowledge management orientation behaviour. Findings: The results show that organizing memory, knowledge absorption, and knowledge receptivity has a direct significant effect on business performance. However, in affecting business performance, knowledge sharing must be mediated by market orientation. Recommendations for Practitioners: Based on the results of the study, practitioners should enhance their behaviour in implementing knowledge management in terms of increasing business performance. In addition, it is suggested that business practitioners must be market driven, as market orientation was found to have an important role in affecting business performance. Recommendation for Researchers: Future researchers might integrate other constructs such as innovation, marketing capabilities, or organizational learning with this current conceptual model to have more comprehensive insight about the relationship between knowledge management orientation and business performance. Impact on Society: This study suggests that business practitioners must have knowledge management driven behaviour as well as market orientation to enhance the performance of their business. Future Research: Future research might add other variables to make the conceptual model more comprehensive and also replicate this study into different industrial settings. http://www.informingscience.org/Publications/4089 knowledge management orientation market orientation business performance economy creative small and medium enterprises eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-08-02 13 201 231 4095 article Shouhong Wang swang@umassd.edu Hai Wang hwang@smu.ca Nadia Khalil nkhalil2@umassd.edu Aim/Purpose: This study investigates the research profile of the papers published in Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) to provide silhouette information of the journal for the editorial team, researchers, and the audience of the journal. Background: Information and knowledge management is an interdisciplinary subject. IJIKM defines intersections of multiple disciplinary research communities for the interdisciplinary subject. Methodology: A quantitative study of categorical content analysis was used for a thematic analysis of IJIKM. One hundred fifty nine (159) papers published since the inauguration of the journal in 2006 were coded and analyzed. Contribution: The study provides synopsized information about the interdisciplinary research profile of IJIKM, and adds value to the literature of information and knowledge management. Findings: The analysis reveals that IJIKM disseminates research papers with a wide range of research themes. Among the research themes, Organizational issues of knowledge/information management, Knowledge management systems/tools, Information/knowledge sharing, Technology for knowledge/information management, Information/knowledge application represent the five main research streams of IJIKM. The total number of papers on organizational issues of knowledge/information management increased from 16% to 28% during the past 6 years. Statistical method was the most common research methodology, and summarization was the most common research design applied in the papers of IJIKM. The paper also presents other patterns of participant countries, keywords frequencies, and reference citations. Recommendations for Practitioners: Innovation is the key to information and knowledge management. Practitioners of information and knowledge management can share best practices with external sectors. Recommendation for Researchers: Researchers can identify opportunities of cross-disciplinary research projects that involve experts in business, education, government, healthcare, technology, and psychology to advance knowledge in information and knowledge management. Impact on Society: Information and knowledge management is still a developing field, and readers of this paper can gain more understanding of the dissemination of the literature of information and knowledge management involved in all relevant disciplines. Future Research: A longitudinal study could follow up in the future to provide updated and comparative information of the research profile of the journal. http://www.informingscience.org/Publications/4095 Interdisciplinary Journal of Information Knowledge and Management IJIKM research profile content analysis thematic analysis eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-08-23 13 233 258 4106 article Ahmed Al-Azawei ahmedhabeeb@itnet.uobabylon.edu.iq Aim/Purpose: This study aims at (1) extending an existing theoretical framework to gain a deeper understanding of the technology acceptance process, notably of the Facebook social network in an unexplored Middle East context, (2) investigating the influence of social support theory on Facebook adoption outside the work context, (3) validating the effectiveness of the proposed research model for enhancing Facebook adoption, and (4) determining the effect of individual differences (gender, age, experience, and educational level) amongst Facebook users on the associated path between the proposed model constructs. Background: Social networking sites (SNSs) are widely adopted to facilitate social interaction in the Web-based medium. As such, this present work contends that there is a gap in the existing literature, particularly in the Middle East context, as regards an empirical investigation of the relationship between the social, psychological, individual, and cognitive constructs potentially affecting users’ intention to accept SNSs. The present research, therefore, attempts to address this deficit. The relevance of this work is also considered in light of the scarcity of empirical evidence and lack of detailed research on the effect of social support theory with regard to SNS adoption in a non-work context. Methodology: A quantitative research approach was adopted for this study. The corresponding analysis was carried out based on structural equation modelling (SEM), more specifically, partial least squares (PLS), using SmartPLS software. Earlier research recommended the PLS approach for exploratory studies when extending an existing model or developing a new theory. PLS is also a superior method of complex causal modelling. Moreover, a multi-group analysis technique was adopted to investigate the moderating influence of individual differences. This method divides the dataset into two groups and then computes the cause and effect relationships between the research model variables for each set. The analysis of an in-person survey with a sample of Facebook users (N=369) subsequently suggested four significant predictors of continuous Facebook use. Contribution: This study contributes to the body of knowledge relating to SNSs by providing empirical evidence of constructs that influence Facebook acceptance in the case of a developing country. It raises awareness of antecedents of Facebook acceptance at a time when SNSs are widely used in Arab nations and worldwide. It also contributes to previous literature on the effectiveness of the unified theory of acceptance and use of technology (UTAUT) in different cultural contexts. Another significant contribution of this study is that it has reported on the relevance of social support theory to Facebook adoption, with this theory demonstrating a significant and direct ability to predict Facebook acceptance. Finally, the present research identified the significant moderating effect of individual differences on the associated path between the proposed model constructs. This means that regardless of technological development, individual gaps still appeared to exist among users. Findings: The findings suggested four significant predictors of continuous Facebook use, namely, (a) performance expectancy, (b) peer support, (c) family support, and (d) perceived playfulness. Furthermore, behavioral intention and facilitating conditions were found to be significant determinants of actual Facebook use, while individual differences were shown to moderate the path strength between several variables in the proposed research model. Recommendations for Practitioners: The results of the present study make practical contributions to SNS organizations. For example, this research revealed that users do not adopt Facebook because of its usefulness alone; instead, users’ acceptance is developed through a sequence of variables such as individual differences, psychological factors, and social and organizational beliefs. Accordingly, social media organizations should not consider only strategies that apply to just one context, but also to other contexts characterized by different beliefs, perceptions, and cultures. Moreover, the evidence provided here is that social support theory has a significant influence on SNSs acceptance. This suggests that social media organizations should provide services to support this concept. Furthermore, the significant positive effect of perceived playfulness on the intention to use SNSs implied that designers and organizations should pay further attention to the entertainment services provided by social networks. Recommendation for Researchers: To validate the proposed conceptual framework, researchers from different countries and cultures are invited to apply the model. Moreover, a longitudinal research design could be implemented to gather data over a longer period, in order to investigate whether users have changed their attitudes, beliefs, perceptions, and intention by the end of the study period. Other constructs, such as individual experience, compatibility, and quality of working life could be included to improve the power of the proposed model. Impact on Society: Middle Eastern Facebook users regard the network as an important tool for interacting with others. The increasing number of Facebook users renders it a tool of universal communication and enjoyment, as well as a marketing network. However, knowledge of the constructs affecting the application of SNSs is valuable for ensuring that such sites have the various functions required to suit different types of user. Future Research: It is hoped that our future research will build on the results of this work and attempt to provide further explanation of why users accept SNSs. In this future research, the proposed research model could be adopted to explore SNSs acceptance in other developing countries. Researchers might also include other factors of potential influence on SNSs acceptance. The constructs influencing acceptance of other social networks could then be compared to the present research findings and thus, the differences and similarities would be highlighted. http://www.informingscience.org/Publications/4106 social media networks Facebook acceptance unified theory of acceptance and use of technology (UTAUT) social support theory perceived playfulness individual differences Middle East eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-09-01 13 259 278 4108 article Caiyun Zhuang zhuangcaiyun19900@163.com Jian Hou nushj1991@163.com Juan Liang 271604167@qq.com Guohong Chen 54505663@qq.com Aim/Purpose: This study analyzes the mechanism of Internet capability (IC) driving knowledge creation performance (KCP). We consider the mediating role of strategic flexibility and the moderating role of informatization density. Background: The key to achieving KCP for firms is to transform knowledge created into new products or services and to realize the economic benefits. However, the research has not paid enough attention to firms’ KCP. Based on dynamic capability theory, this study empirically reveals how firms drive KCP through Internet capability. Methodology: The study uses survey data from 399 organizations in China. Through structural equation modeling, this study assesses the relationship between Internet capability, strategic flexibility, and KCP and uses hierarchical regression to test the moderating role of informatization density. Contribution: First, this study expands research on knowledge creation and focuses on the further achievement of knowledge creation performance. The study also enriches the exploration of KCP in the Internet context and deepens the research on the internal mechanism by which Internet capability influences KCP. Second, this study highlights the important role of informatization density in the Internet context and expands the research on the impact of external factors on the internal mechanism. Findings: First, Internet capability has a significantly positive effect on both strategic flexibility and KCP. Furthermore, Internet capability directly impacts strategic flexibility, yet it affects KCP both directly and indirectly through strategic flexibility, which confirms that strategic flexibility is a partial mediator in the relationship between Internet capability and KCP. Second, strategic flexibility positively influences KCP. Third, informatization density has a significant moderating effect on the relationship between Internet capability and KCP. Recommendations for Practitioners: The results indicate that firms should consider the importance of Internet capability and strategic flexibility for KCP in the Internet context. This study also provides a theoretical basis that could guide the Chinese government’s informatization construction of the industrial chain. Recommendation for Researchers: Researchers could further explore the role of other mediator variables (e.g., business process management, organizational agility) and consider the role of other moderator variables (e.g., resource commitment, learning orientation). Impact on Society: This study provides a reference for enterprises with similar cultural backgrounds in using Internet capability to enhance their competitive advantage. Future Research: Future research could collect data from various countries and regions to test the research model and conduct longitudinal studies to increase the robustness of the conclusions. http://www.informingscience.org/Publications/4108 Internet capability knowledge creation performance strategic flexibility informatization density eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-09-24 13 279 309 4088 article Ra'ed Masa'deh r.masadeh@ju.edu.jo Shadi Abualoush shadi_habes@inu.edu.jo Khaled Bataineh dr.khaled.adnan@inu.edu.jo Ala'aldin Alrowwad a.alrowwad@ju.edu.jo Aim/Purpose: The objective of this study was to assess the interrelationships among knowledge management infrastructure, knowledge management process, intellectual capital, and organization performance. Background: Although knowledge management capability is extensively used by organizations, reaching their maximum financial and non-financial performances has not been fully researched. Therefore, organizations need to optimize their performance by exploiting knowledge management capability through the accumulation of intellectual capital, where the new competitiveness is shifting from tangible to intangible resources. Methodology: This study adopted a positivist philosophy and deductive approach to accomplish the main goal of this research. Moreover, this research employed a quantitative approach since this study is concerned with causal relationship between variables. A questionnaire-based survey was designed to evaluate the research model using a convenience sample of 134 employees from the food industry sector in Jordan. Surveyed data was examined following the structural equation modeling procedures. Contribution: This study highlighted the potential benefits of applying the knowledge management capabilities, intellectual capital, and organizational performance to the food industrial sector in Jordan. Future research suggestions are also provided. Findings: Results indicated that knowledge management infrastructure had a positive effect on knowledge management process. In addition, knowledge management process impacted positively intellectual capital and organization performance and mediated the relationship between knowledge management infrastructure and intellectual capital. However, knowledge management infrastructure did not positively associate to organization performance. Recommendations for Practitioners: The current model is designed to help managers and decision makers to improve their management capabilities as well as their organization financial and non-financial performance through exploiting the organizational knowledge management infrastructure and intellectual capital approaches. Recommendation for Researchers: Our findings can be used as a base of knowledge to conduct further studies about knowledge management capabilities, intellectual capital, and organization performance following different criteria and research procedures. Impact on Society: The designed model highlights a significant organizational performance approach that can influence Jordanian food industrial sector positively. Future Research: The current designed research model can be applied and assessed further in other sectors including banking and industrial sectors across developed and developing countries. Also, we suggest that in addition to focusing on knowledge management process and intellectual capital as mediating variables, future research could test our findings in a longitudinal study and examine how to affect financial and non-financial performance. http://www.informingscience.org/Publications/4088 knowledge management infrastructure knowledge management process intellectual capital organization performance Jordan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-10-01 13 311 335 4107 article Mohammad Sharaf Qdah mohd_sharaf@yahoo.com Amer Nizar Fayez AbuAli drabuali@yahoo.com Juhana Salim js@ukm.edu.my Tarek Issa Khalil tarek.khalil7@gmail.com Aim/Purpose: A vital business activity within organizations is tacit knowledge (TK) transfer. This work aims to propose a novel framework for TK transferability in multinational corporations (MNCs) from the information and communication technology (ICT) perspective. Background: In the past two decades, researchers have developed several frameworks for TK transfer based on humanistic, business, and educational perspectives. However, a review of the existing work revealed that TK transfer has seldom been examined from an ICT perspective. Methodology: A qualitative method was adopted because it was considered the most appropriate for the research requirements. A grounded theory approach was employed to generate the items that potentially affect the transferability of TK. Face-to-face semi-structured interviews were conducted to collect data, along with observations when possible. The study sample consisted of 20 expert interviewees in Malaysia. An inductive ongoing data analysis process based on grounded theory via open, axial, and selective coding was used as the primary analysis method. In addition, comparative and frequency count analyses were used to examine the collected data. Contribution: The main contribution of this study is its use of the grounded theory approach, which resulted in the generation of items that affect the transferability of TK, not all of which had been identified by previous researchers. This paper reports one of the few inductive studies conducted on TK transferability among MNCs and, therefore, makes distinct contributions to the literature on TK management, specifically bringing to the fore the intricacies involved in TK transferability. Findings: Information and communication technology plays a crucial role in and has a positive impact on TK transfer in MNCs. This study evaluated the potential of various ICT channels to facilitate TK transfer. The findings show that ICT tools cannot completely substitute for face-to-face contact. Tacit knowledge that has a high degree of complexity requires sophisticated channel features for its transfer. From this standpoint, virtual face-to-face communication is the richest communication medium in the ICT hierarchy. On the other hand, email and voicemail are less effective channels for TK transfer, while synchronous groupware is an intermediate communication medium. The findings highlight the importance of utilizing an appropriate mix of channels to improve TK transferability. Recommendations for Practitioners: It is recommended that practitioners consider the diverse aspects of TK and the potential of a range of ICT channels for the TK transfer process in order to increase the efficiency of TK transfer. The analytic categories developed in this study may give managers new insights into and a better understanding of how TK can be supported in a modern organization and how to overcome the barriers to TK transfer. http://www.informingscience.org/Publications/4107 tacit knowledge transferability information and communication technology multinational corporations eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-10-09 13 337 359 4118 article Imran Mahmud imranmahmud@daffodilvarsity.edu.bd T. Ramayah ramayah@usm.my Pravina Jayapal pravina6600@gmail.com Nusrat Jahan nusrat.swe@diu.edu.bd Mohamed Emran Hossain emran@daffodilvarsity.edu.bd Tapushe Rabaya Toma toma.swe@diu.edu.bd Aim/Purpose: In this research, we examined the influence of the information system (IS) quality dimensions proposed by Wixom and Todd on reading satisfaction of online newspaper readers in Bangladesh, especially the readers’ intention to revisit and recommendations through electronic word-of-mouth (eWOM). Background: We identified the top 50 most visited websites, of which 13 were online newspapers, although their ranking among Bangladesh online newspapers varies from month to month. The literature illustrates that, despite the wide availability of online news portals and the fluctuations in frequency of visits, little is known about the factors that affect the satisfaction, word-of-mouth, and frequency of visits of readers. An understanding of reader satisfaction will help to gain richer insights into the phenomenon of readers’ intention to revisit and recommendation by eWOM. Stakeholders of online newspapers can then focus on those factors to increase visits to their websites, which will help them attract online advertisements from different organisations. Methodology: Data were collected using a structured questionnaire, from 217 people who responded to the survey. We used SmartPLS 3 to analyze the data collected, as it is based on second-generation analysis, which in turn is based on structural equation modeling (SEM). Contribution: This research explores the impacts of technological dimensions on readers’ satisfaction, as most of the previous research has focused on cultural or social dimensions. Findings: The results supported all of the hypothesized relationships between technological dimensions and reader satisfaction with online newspapers, except for one. The first, information, was predicted with accuracy and completeness, while the second object-based belief, system quality, was predicted by its accessibility, flexibility, reliability, and timeliness. Overall, quality factors influencing readers’ satisfaction were shown to lead to word-of-mouth revisit intentions. Our proposed model was empirically tested and has contributed to a nascent body of knowledge about readers’ revisit intentions and eWOM recommendations regarding online newspapers. It was also shown that strong satisfaction leads to higher revisit intention and eWOM. Recommendations for Practitioners: To keep the users satisfied, online newspapers need to focus on improving information quality (IQ) and system quality (SQ). If they do this well, they will be rewarded with higher revisit intention and recommendations by eWOM. Recommendation for Researchers: This study extends Oh’s customer loyalty model by integrating the Wixom-Todd model. This study reinforces an alternative rationale of the construct satisfaction. Future Research: We ignored negative stimulus like technostress, which can have an impact on satisfaction. In future, we will test the relationship between technostress and its impact on online newspaper reading. http://www.informingscience.org/Publications/4118 information quality system quality IS success model online newspapers PLS eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-10-18 13 361 381 4132 article Ibrahim Magboul ibrahimmagboul@gmail.com Muneer Abbad muneerabbad@gmail.com Aim/Purpose: This paper identifies the antecedents that affect E-Banking (EB) adoption and investigates the relationship between the level of EB adoption and the performance of private banks. Background: Rapid technological advancement has transformed the business environment dramatically. These advancements particularly the Internet has reshaped the way businesses operate. Over the last decade, the banking industry has become highly complex and competitive and operates in a highly volatile and unpredictable global economy. With the increasing demand for electronic services, banks are harnessing EB technology to improve their products and services. Methodology: Quantitative research using Structural Equation Modelling (SEM) was carried out with a sample size of 211 by sending questionnaires to employees of six banks in Khartoum, Sudan. The study is based on different technology theories and models. Contribution: The study provides insights into the employees’ perception of EB adoption in their banking transactions. Findings: The results showed that four factors are significant in the adoption of EB in Sudan. However, training and user trust were insignificant in determining its adoption. Moreover, the level of adoption of EB significantly affected private bank performance. Recommendations for Practitioners: Private banks in Sudan that are interested in EB might find these findings helpful in guiding their technology adoption and application initiatives. Recommendation for Researchers: To validate the research model, cross data from different countries are encouraged to apply the model to capture the differences and similarities among them. In addition, a longitudinal research could be conducted to gather data for adoption process over a longer period rather than one point of time, to investigate antecedents and bank performance outcomes by the end of the study period. Other antecedents and outcomes could possibly be included to improve the power of the study model. Impact on Society: This study provides a reference for banks with similar developing country backgrounds in adopting EB to enhance their performance. Moreover, knowledge of antecedents and outcomes of EB adoption could be positively reflected in service quality performance. Future Research: This research is limited to the employees’ perspective, and future research could consider the perception of customers from a developing country towards EB adoption. http://www.informingscience.org/Publications/4132 technology acceptance e-banking adoption performance Sudan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-10-20 13 383 396 4134 article Basem Y. Alkazemi bykazemi@uqu.edu.sa Aim/Purpose: This paper reports our implementation of a prototype system, namely PRATO (Proposals Reviewers Automated Taxonomy-based Organization), for automatic assignment of proposals to reviewers based on categorized tracks and partial matching of reviewers’ profiles of research interests against proposal keywords. Background: The process of assigning reviewers to proposals tends to be a complicated task as it involves inspecting the matching between a given proposal and a reviewer based on different criteria. The situation becomes worse if one tries to automate this process, especially if a reviewer partially matches the domain of the paper at hand. Hence, a new controlled approach is required to facilitate the matching process. Methodology: Proposals and reviewers are organized into categorized tracks as defined by a tree of hierarchical research domains which correspond to the university’s colleges and departments. In addition, reviewers create their profiles of research interests (keywords) at the time of registration. Initial assignment is based on the matching of categorized sub-tracks of proposal and reviewer. Where the proposal and a reviewer fall under different categories (sub-tracks), assignment is done based on partial matching of proposal content against re-viewers’ research interests. Jaccard similarity coefficient scores are calculated of proposal keywords and reviewers’ profiles of research interest, and the reviewer with highest score is chosen. The system was used to automate the process of proposal-reviewer assignment at the Umm Al-Qura University during the 2017-2018 funding cycle. The list of proposal-reviewer assignments generated by the system was sent to human experts for voting and subsequently to make final assignments accordingly. With expert votes and final decisions as evaluation criteria, data system-expert agreements (in terms of “accept” or “reject”) were collected and analyzed by tallying frequencies and calculating rejection/acceptance ratios to assess the system’s performance. Contribution: This work helped the Deanship of Scientific Research (DSR), a funding agency at Umm Al-Qura University, in managing the process of reviewing proposals submitted for funding. We believe the work can also benefit any organizations or conferences to automate the assignment of papers to the most appropriate reviewers. Findings: Our developed prototype, PRATO, showed a considerable impact on the entire process of reviewing proposals at DSR. It automated the assignment of proposals to reviewers and resulted in 56.7% correct assignments overall. This indicates that PRATO performed considerably well at this early stage of its development. Recommendations for Practitioners: It is important for funding agencies and publishers to automate reviewing process to obtain better reviewing quality in a timely manner. Recommendation for Researchers: This work highlighted a new methodology to tackle the proposal-reviewer assignment task in an automated manner. More evaluation might be needed with consideration of different categories, especially for partially matched candidates. Impact on Society: The new methodology and knowledge about factors influencing the implementation of automated proposal-reviewing systems will help funding agencies and publishers to improve the quality of their internal processes. Future Research: In the future, we plan to examine PRATO’s performance on different classification schemes where specialty areas can be represented in graphs rather than trees. With graph representation, the scope for reviewer selection can be widened to include more general fields of specialty. Moreover, we will try to record the reasons for rejection to identify accurately whether the rejection was due to improper assignment or other reasons. http://www.informingscience.org/Publications/4134 reviewers matching taxonomy-based Jaccard index proposals auto assignment eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-12-03 13 397 415 4149 article Hadi AL-Abrrow hauni_2000@yahoo.com Alhamzah Alnoor alhamzah.malik@stu.edu.iq Hasan Oudah Abdullah hasan_oudah@yahoo.com Aim/Purpose: This explanatory study aimed to determine the mediating role of ERP in the relation between the effect of a socio-technical approach and decision-making environment, and firms’ sustainable performance. Background: Although earlier studies have discussed the critical success factors of the failure or success of an ERP system and the extent to which it achieves its desired objectives, the current study focused on the significant impact of socio-technical elements and decision-making environment on the success of the ERP system (i.e., sustainable performance). In addition, the lack of research on ERP as a mediator in the above relationship motivated this study to bridge the literature gap. Methodology: The data was collected using questionnaires distributed to 233 randomly selected employees of three multinational companies (BP, LUKOIL, and Eni) operating in Iraq. The structural equation modeling was employed to test the hypothesized relationships. Contribution: The study contributes to the literature by examining the mediating role of the ERP system in the relationship between socio-technical elements and the decision-making environment, as well as, the moderating role of organizational culture in the relationship between socio-technical elements and ERP systems. Findings: The results showed that ERP is a significant mediator between the linkage of socio-technical elements and the decision-making environment while organizational culture has an insignificant moderating role in the relationship between socio-technical elements and ERP systems. Recommendations for Practitioners: In a developing country like Iraq, there is a need to implement ERP to achieve better sustainable performance through change management and organizational development that ultimately work towards enhancing individual capabilities, knowledge, and training. Recommendation for Researchers: The researchers are recommended to conduct an in-depth study of the phenomenon based on theoretical and empirical grounds, particularly in light of the relationship of socio-technical elements and decision-making environments. Impact on Society: This study provides a reference for organizations with similar cultural backgrounds in using ERP systems to minimize pollution in Iraqi context. Future Research: A more in-depth study can be performed using a bigger sample, which not only includes the oil industry but also the other industries. http://www.informingscience.org/Publications/4149 organizational culture; socio-technical approach; decision-making environment; ERP system; sustainable performance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2018-12-29 13 417 435 4166 article Mochamad Agung Wibowo agungwibowo360@gmail.com Rudi Waluyo rudiwaluyo30@gmail.com Zhabrinna Zhabrinna zhabrinnas@gmail.com Aim/Purpose: This study aims to investigate the relationship between the knowledge management (KM) process and the performance of construction companies. The ultimate goal is to promote better efficiency and competitive advantage in the construction industry by making the best use of knowledge. Background: While attention to KM is currently on the rise, as shown by the number of studies conducted, research on KM in the construction industry of Indonesia is still very rare. However, organizational learning as the implementation of KM provides an opportunity to improve the construction industry, and thus there is an urgency to conduct research on this topic. Methodology: This study lasted for three months and used the survey method, with 100 questionnaires distributed to contractors of grade 6 and 7 on the islands of Java and Borneo in Indonesia. A total of 54 returned questionnaires were deemed complete and eligible for further analysis. Data analysis was performed using the structural equation modeling method with partial least squares (SEM PLS). Contribution: This study helps to measure the relationship value of the KM process and company performance. Findings: The results of this study indicate that the process of KM has a significant and positive influence on company performance, and there is a positive interaction in the process of KM and company performance as well. Recommendations for Practitioners: Construction companies need to perceive that activities undertaken in a construction project should always be assumed to be a KM process in order to make strategic and effective decisions that can result in improvements to customers, finance, internal business, learning, and growth. Recommendation for Researchers: Research on the KM process and information technology needs to be developed more, so that construction companies can apply this knowledge to explore problems and create solutions, resulting in methods to facilitate efficiency and effectiveness. Impact on Society: This paper helps to understand that KM activities provide initial benefits and guidance for companies that want to apply KM. Future Research: Innovative and new ideas to cultivate the KM process in the construction industry need to be explored and developed to improve the implementation. http://www.informingscience.org/Publications/4166 knowledge knowledge management corporate performance construction eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-01-17 12 i iii 3642 article Table of Contents for the Interdisciplinary Journal of Information, Knowledge, and Management, Volume 12, 2017 http://www.informingscience.org/Publications/3642 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-01-17 12 001 015 3639 article Kennedy Njenga knjenga@uj.ac.za Aim/Purpose: Violations of Information Systems (IS) security policies continue to generate great anxiety amongst many organizations that use information systems, partly because these violations are carried out by internal employees. This article addresses IS security policy violations in organizational settings, and conceptualizes and problematizes IS security violations by employees of organizations from a paradox perspective. Background: The paradox is that internal employees are increasingly being perceived as more of a threat to the security of organizational systems than outsiders. The notion of paradox is exemplified in four organizational contexts of belonging paradox, learning paradox, organizing paradox and performing paradox. Methodology : A qualitative conceptual framework exemplifying how IS security violations occur as paradoxes in context to these four areas is presented at the end of this article. Contribution: The article contributes to IS security management practice and suggests how IS security managers should be positioned to understand violations in light of this paradox perspective. Findings: The employee generally in the process of carrying out ordinary activities using computing technology exemplifies unique tensions (or paradoxes in belonging, learning, organizing and performing) and these tensions would generally tend to lead to policy violations when an imbalance occurs. Recommendations for Practitioners: IS security managers must be sensitive to employees tensions. Future Research: A quantitative study, where statistical analysis could be applied to generalize findings, could be useful. http://www.informingscience.org/Publications/3639 information security violations paradox systematic literature review (SLR) security policies eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-01-22 12 017 036 3644 article Jhong-Min Yang a845461@gmail.com Chien-Ta Ho bruceho@nchu.edu.tw Wei-Ting Chen marionette522@gmail.com Aim/Purpose: This study uses a cosmetic virtual community (VC) as the research context and the UTAUT model as the theoretical structure aim to explore factors affecting the re-usage intentions of VC members. Background: The Internet use rate of VC was up to 50%, thereby implying that VC gained the attention of Internet users. Therefore, operating a VC will be an effective way to communicate with customers. However, to maintain an existing member is more efficient than creating a new one. As such, understanding determinants of VC members’ re-use intentions becomes important for firms. Methodology: Through an online survey, 276 valid responses were gathered. The collected data were examined by performing confirmatory factor analysis, structural equation modelling procedures, as well as the moderator analysis. Contribution: This study shows the importance in the context of online cosmetics-related VC, which was rarely explored before. We provide issues for future research, despite the accumulated academic literature related to UTAUT and VC. Findings: Results show that only performance expectancy and social influence significantly affecting re-usage intentions and only gender has moderating effects on the path from performance expectancy to VC re-use intention and from trust to VC re-use intention. Recommendations for Practitioners : This study found that users emphasized performance expectancy most of all. A cosmetic product-related VC should introduce products abundantly, offer useful information, and help people accomplish tasks quickly and productively. Recommendation for Researchers: Future researchers may use our findings to conduct further positivist research in the area of social influence using different subjects and research contexts. http://www.informingscience.org/Publications/3644 virtual community cosmetic products UTAUT model structural equation modelling approach effort expectancy performance expectancy social influ-ence trust re-usage intentions eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-02-05 12 037 051 3652 article Benjamin Wagner vom Berg benjamin.wagnervomberg@uni-oldenburg.de Jorge Marx Gómez jorge.marx.gomez@uni-oldenburg.de Alexander Sandau alexander.sandau@uni-oldenburg.de Aim/Purpose: The topic of this study is the ICT-enabled transformation of car dealerships to regional providers of sustainable mobility (e.g., car sharing). Background: Car dealerships offer specific conditions that enable a sustainable mobility offer, based on individual motorized transport like car sharing. This is especially useful in small towns or rural areas where people’s mobility is strongly dominated by private cars, and public transport coverage is limited. However, these new mobility services are combined services with the need of a deep integration of information systems, and these services are not yet related to car dealerships and customer acquisition has to be supported. Methodology: An empirical study with an inductive approach was chosen. The study consists of interviews with three focus groups of different stakeholders of car dealerships. Within the frame of the research project, “ReCaB – Regional Car-Balancing” a qualitative research approach was chosen. Within a design science approach the existing SusCRM architecture was adapted based on the elaborated requirements. Contribution: A software architecture is proposed, where Customer Relationship Management (CRM) components to market new sustainable mobility offers are vital parts and existing information systems of car dealerships are integrated. Findings: The basic feasibility of the establishment and customer acceptance has been demonstrated, at least in the area of car sharing within ReCaB. The execution in the car sharing field has already started and a number of car dealerships are already bringing their own offers to market. Major findings for the SusCRM architecture have been elaborated in a design science approach in the national German research project “Showcase for electro mobility”. Recommendations for Practitioners: There is still no fully functional prototype developed for this specific use case and evaluated in the car dealership environment. An implementation only, based on own efforts, is difficult for car dealerships because of the dealership’s lack of know-how as well as tight IT budgets. However, this approach appears particularly successful in rural areas where public transport services are heavily declining. For full implementation, the presented ICT support is imperative. Recommendation for Researchers: The research on the retailer level, especially in combination with a digital trans-formation by the use of ICT systems, is still fragmentary. Research in this area that both addresses sustainability goals on a general level and supports economical goals on the company level of automotive retailers would be useful. Impact on Society: Creation of sustainable offers as a substitute or supplement for mobility based on their own car is a promising way to reduce negative effects of mobility. Enhancement of the mobility of the people in rural areas is leading to a more active lifestyle by reaching the leisure facilities, workplaces and educational institutions in a sustainable manner. Future Research: In terms of the fast changing mobility landscape, especially on a technical level with the development of autonomous vehicles and digitalization of entire businesses new solutions are becoming accessible, that have to be integrated in further research. http://www.informingscience.org/Publications/3652 car dealership automotive retailer car sharing SusCRM sustainability CRM sustainable mobility rural regions eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-02-28 12 053 073 3666 article Vaughan Henriques vaughanhenriques@gmail.com Maureen Tanner mc.tanner@uct.ac.za Background/Aim/Purpose: A commonly implemented software process improvement framework is the capability maturity model integrated (CMMI). Existing literature indicates higher levels of CMMI maturity could result in a loss of agility due to its organizational focus. To maintain agility, research has focussed attention on agile maturity models. The objective of this paper is to find the common research themes and conclusions in agile maturity model research. Methodology: This research adopts a systematic approach to agile maturity model research, using Google Scholar, Science Direct, and IEEE Xplore as sources. In total 531 articles were initially found matching the search criteria, which was filtered to 39 articles by applying specific exclusion criteria. Contribution:: The article highlights the trends in agile maturity model research, specifically bringing to light the lack of research providing validation of such models. Findings: Two major themes emerge, being the coexistence of agile and CMMI and the development of agile principle based maturity models. The research trend indicates an increase in agile maturity model articles, particularly in the latter half of the last decade, with concentrations of research coinciding with version updates of CMMI. While there is general consensus around higher CMMI maturity levels being incompatible with true agility, there is evidence of the two coexisting when agile is introduced into already highly matured environments. Future Research: Future research direction for this topic should include how to attain higher levels of CMMI maturity using only agile methods, how governance is addressed in agile environments, and whether existing agile maturity models relate to improved project success. http://www.informingscience.org/Publications/3666 Agile Scrum XP Maturity Model Agile Maturity Model Agile Process Improve-ment eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-03-16 12 075 098 3670 article Andrew T Bimba bimba@siswa.um.edu.my Ahmed A. Al-Hunaiyyan hunaiyyan@hotmail.com Norisma Idris norisma@um.edu.my Salah Al-Sharhan alsharhans@gust.edu.kw Aim/Purpose: This work aims to present a knowledge modeling technique that supports the representation of the student learning process and that is capable of providing a means for self-assessment and evaluating newly acquired knowledge. The objective is to propose a means to address the pedagogical challenges in m-learning by aiding students’ metacognition through a model of a student with the target domain and pedagogy. Background: This research proposes a framework for social and meta-cognitive support to tackle the challenges raised. Two algorithms are introduced: the meta-cognition algorithm for representing the student’s learning process, which is capable of providing a means for self-assessment, and the social group mapping algorithm for classifying students according to social groups. Methodology : Based on the characteristics of knowledge in an m-learning system, the cognitive knowledge base is proposed for knowledge elicitation and representation. The proposed technique allows a proper categorization of students to support collaborative learning in a social platform by utilizing the strength of m-learning in a social context. The social group mapping and metacognition algorithms are presented. Contribution: The proposed model is envisaged to serve as a guide for developers in implementing suitable m-learning applications. Furthermore, educationists and instructors can devise new pedagogical practices based on the possibilities provided by the proposed m-learning framework. Findings: The effectiveness of any knowledge management system is grounded in the technique used in representing the knowledge. The CKB proposed manipulates knowledge as a dynamic concept network, similar to human knowledge processing, thus, providing a rich semantic capability, which provides various relationships between concepts. Recommendations for Practitioners: Educationist and instructors need to develop new pedagogical practices in line with m-learning. Recommendation for Researchers: The design and implementation of an effective m-learning application are challenging due to the reliance on both pedagogical and technological elements. To tackle this challenge, frameworks which describe the conceptual interaction between the various components of pedagogy and technology need to be proposed. Impact on Society: The creation of an educational platform that provides instant access to relevant knowledge. Future Research: In the future, the proposed framework will be evaluated against some set of criteria for its effectiveness in acquiring and presenting knowledge in a real-life scenario. By analyzing real student interaction in m-learning, the algorithms will be tested to show their applicability in eliciting student metacognition and support for social interactivity. http://www.informingscience.org/Publications/3670 m-learning pedagogy mobile device knowledge modeling eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-03-21 12 099 124 3680 article Shreyas Suresh Rao shreyassureshrao@gmail.com Ashalatha Nayak asha.nayak@manipal.edu Aim/Purpose: A vital business activity within socio-technical enterprises is tacit knowledge externalization, which elicits and explicates tacit knowledge of enterprise employees as external knowledge. The aim of this paper is to integrate diverse aspects of externalization through the Enterprise Ontology model. Background: Across two decades, researchers have explored various aspects of tacit knowledge externalization. However, from the existing works, it is revealed that there is no uniform representation of the externalization process, which has resulted in divergent and contradictory interpretations across the literature. Methodology : The Enterprise Ontology model is constructed step-wise through the conceptual and measurement views. While the conceptual view encompasses three patterns that model the externalization process, the measurement view employs certainty-factor model to empirically measure the outcome of the externalization process. Contribution: The paper contributes towards knowledge management literature in two ways. The first contribution is the Enterprise Ontology model that integrates diverse aspects of externalization. The second contribution is a Web application that validates the model through a case study in banking. Findings: The findings show that the Enterprise Ontology model and the patterns are pragmatic in externalizing the tacit knowledge of experts in a problem-solving scenario within a banking enterprise. Recommendations for Practitioners : Consider the diverse aspects (what, where, when, why, and how) during the tacit knowledge externalization process. Future Research: To extend the Enterprise Ontology model to include externalization from partially automated enterprise systems. http://www.informingscience.org/Publications/3680 tacit knowledge enterprise ontology socio-technical enterprise externalization certainty-factor eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-04-02 12 125 138 3687 article Jeanne Moore moorej107@gmail.com Aim/Purpose: This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the information to circumvent big data challenges for executive strategic decision making. Background: This journal paper seeks to understand what executives value in data visualization, based on the literature published from prior data studies. Methodology: The qualitative methodology was used to understand the sentiments of executives and data analysts using semi-structured interview techniques. Contribution: The preliminary findings can provide practical knowledge for data visualization designers, but can also provide academics with knowledge to reflect on and use, specifically in relation to information systems (IS) that integrate human experience with technology in more valuable and productive ways. Findings: Preliminary results from interviews with executives and data analysts point to the relevance of understanding and effectively presenting the data source and the data journey, using the right data visualization technology to fit the nature of the data, creating an intuitive platform which enables collaboration and newness, the data presenter’s ability to convey the data message and the alignment of the visualization to core the objectives as key criteria to be applied for successful data visualizations Recommendations for Practitioners: Practitioners, specifically data analysts, should consider the results highlighted in the findings and adopt such recommendations when presenting data visualizations. These include data and premise understanding, ensuring alignment to the executive’s objective, possessing the ability to convey messages succinctly and clearly to the audience, having knowledge of the domain to answer questions effectively, and using the right technology to convey the message. Recommendation for Researchers: The importance of human cognitive and sensory processes and its impact in IS development is paramount. More focus can be placed on the psychological factors of technology acceptance. The current TAM model, used to describe use, identifies perceived usefulness and perceived ease-of-use as the primary considerations in technology adoption. However, factors that have been identified that impact on use do not express the importance of cognitive processes in technology adoption. Future Research: Future research requires further focus on intangible and psychological factors that could affect technology adoption and use, as well as understanding data visualization effectiveness in corporate environments, not only predominantly within the Health sector. Lessons from Health sector studies in data visualization should be used as a platform. http://www.informingscience.org/Publications/3687 big data data analytics data visualization cognitive fit theory Cynefin Frame-work executive strategic decision making eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-04-16 12 139 157 3710 article Abdul Waheed abdulwaheed168@yahoo.com Jianhua Yang yangjh@ustb.edu.cn Jon K. Webber drjonwebber@gmail.com Aim/Purpose: The present study investigates the relationship between the five-factor model (FFM) of personality traits and sales performance in Pakistan. Background: Personality is a well-researched area in which numerous studies have examined the correlation between personality traits and job performance. In this study, a positive effect between the various dimensions of the five-factor model (extraversion, agreeableness, conscientiousness, emotional stability, and open to experience) and sales performance in Pakistan is investigated. Methodology: Pearson’s correlation values as well as analysis methodologies were employed to gather descriptive statistics, reliability analysis, correlation analysis, and use the analytical hierarchy process (AHP). Cronbach’s alpha value helped determine the internal consistency of the group items. Questionnaires were distributed among 600 salespersons in various cities of Pakistan from April 2015 to January 2016. Subsequently, 510 questionnaires were acquired for the sample. Contribution: The current study contributes to the literature on personality traits and sales performance by applying empirical evidence from sales managers in three industries of Pakistan: pharmaceutical, insurance, and electronics. Findings: The results affirmed a positive effect of the five-factor model on sales performance among various industries in Pakistan. The effect of each sub-factor from the five-factor model was examined autonomously. There is a favorable benefit to sales managers in considering FFM when making hiring decisions. Impact on Society: FFM offers important insights into personality traits that work well within Pakistani sales industry structure. Future Research: A broader rendering of the effects of FFM on sales organizations in other geographical locations around Pakistan should be considered. Additionally, an extended study should be conducted to investigate the effects of FFM on female sales employees involving religious and cultural forces within that country. http://www.informingscience.org/Publications/3710 personality traits five-factor model (FFM) sales performance sales force of Pakistan females religious and cultural forces eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-05-03 12 159 174 3735 article Alrence S Halibas alrence@gulfcollege.edu.om Rowena Ocier Sibayan dr.wheng@yahoo.com.ph Rolou Lyn Maata roloumaata@gmail.com Aim/Purpose: Countries today strategically pursue regional development and economic diversification to compete in the world market. Higher Education Institutions (HEIs) are at the crux of this political strategy. The paper reviews how HEIs can propel regional socio-economic growth and development by way of research innovation and entrepreneurship. Background: Offering an academic perspective about the role of HEIs using the Penta Helix innovation network for business and social innovation, the paper discusses opportunities and challenges in gestating an innovation culture. It likewise seeks, identifies and details strategies and workable programs. Methodology: Best-practice innovation campaigns initiated by Omani HEIs in collaboration with capstone programs organized by the government were parsed from selected local and international literature. The study includes a causal analysis of innovation information contained in 40 out of 44 published OAAA Quality Audit reports about HEIs from 2009 to 2016. The best-practice programs serve as success indicators and will be used as a field metric effect a Penta Helix blueprint for innovation. Contribution: The paper discusses how HEIs can engender, nurture, drive, and sustain innovation and entrepreneurial activity by using an innovation strategic blueprint like the Penta Helix model. It gathers together the recent historical attempts at promoting innovation by HEIs. It likewise suggests the creation of a network channel to allow key players in the innovation network to share innovation information and to collaborate with each other. Furthermore, it contributes to the development of innovation culture in HEIs. Findings: Expectations run high in academia. For one, universities believe that all innovations embryonically begin within their halls. Universities–too–believe it is naturally incumbent on them to stimulate and advance innovation despite that most innovation programs are initiated by the government in Oman. HEI engagement is perceivably still weak. HEIs have yet to come out as a strong leading force in promoting systems of innovation. There is clear awareness of the need to adopt leading-edge practices in innovation strategy and management, curriculum and assessment, staff support and reward systems, funding and ICT infrastructure, research commercialization and IP management, and community engagement. Recommendations for Practitioners: There is need to conduct more in-depth analyses about the synergy and partnerships between key players of the Penta Helix model. A large-scale survey will help completely reveal the status and impact of innovation practices in the region and among HEIs. Recommendation for Researchers: There is need to conduct more in-depth analyses about the synergy and partnerships between key players of the Penta Helix model. A large-scale survey will help completely reveal the status and impact of innovation practices in the region and among HEIs. Impact on Society: The paper hopes to influence policy. It fully intends to convince policymakers increase the adoption of strategic interventions. The paper is not a theoretical description of the problem. It suggests several concrete courses of action. Future Research: The paper has seen the need to measure the effectiveness of the current innovation practices among key players in the innovation network and how these practices advance Oman’s knowledge economy. We propose a Likert-based bottom-up engagement metric. http://www.informingscience.org/Publications/3735 entrepreneurship HEI innovation knowledge economy Penta Helix eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-05-10 12 175 187 3740 article Meg Coffin Murray isdoctor@gmail.com Joy Fluker joy.fluker@yahoo.com Aim/Purpose: Unified Communications (UC) is touted as a technology that will transform business communication. While positive claims abound, the factors of UC attributable to its success have yet to be identified. By examining how users perceive UC impacts productivity, this study aids organizations in making better decisions regarding investments in and usage of communications technologies. Background: Unified Communications integrates disparate communications and information sharing applications into a single platform. The promise of UC is that it will revolutionize the workplace by providing a more synchronized fit between the way people communicate and the technology they use. Methodology: Through case study research conducted within a large multinational corporation (the Hewlett Packard Company), this study investigated the impact of UC on productivity. Interview narratives were examined using an open coding technique to capture individual perceptions of productivity. Further, to assess the role UC plays in facilitating relationship building and its connection to productivity, participant responses were mapped to the key factors of technology that influence relationships within an organization as identified by Dillon and Montano (2005). Contribution: This research contributes to studies on the impact of UC on productivity in the workplace. Findings UC was found to increase personal productivity, remove communication barriers, and create a more positive work environment. Recommendations for Practitioners : The findings of this study will aid organizations in making investment decisions as they evolve their business communications strategy. Impact on Society: Unified Communications will play an increasingly important role as people adapt to the evolving digital world through which they communicate and collaborate. Future Research: Little research exists that examines the impact of UC within an organization. Additional research investigating the use of UC in a variety of business sectors is needed. http://www.informingscience.org/Publications/3740 Unified Communications (UC) business communications communications channels perceived productivity eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-05-20 12 189 208 3742 article Albert Akanlisikum Akanferi albert.akanferi@upsamail.edu.gh Isaac Asampana isaac.asampana@upsamail.edu.gh James Ami-Narh j.ami-narh@upsamail.edu.gh Aim/Purpose: This study investigates the factors that affect the post implementation success of a web-based learning management system at the University of Professional Studies, Accra (UPSA). Background: UPSA implemented an LMS to blend Web-based learning environment with the traditional methods of education to enable working students to acquire education. Methodology: An explanatory sequential mixed method was adopted, under the pragmatic paradigm, to investigate the level of acceptance of web-based learning by students. The effects of perceived usefulness, perceived ease of use, and other social factors were investigated. In all, 4500 final and third-year undergraduate students of UPSA made up the population. A sample size of 870 was used for this study. Contribution: This paper contributes to the body of knowledge by identifying the factors that hinder post-implementation of LMS at the tertiary level in Ghana and adds to the general literature available. Findings: The level of acceptance of LMS seems very low due to poor IT infrastructure, inadequate training, and the relevance of the system to quality lecture delivery. However, students’ intention to use LMS and the usefulness of LMS were perceived to be high, especially among students in higher levels. Recommendations for Practitioners: The authors recommend that IT infrastructure, especially reliable and fast internet connectivity, and adequate training should be provided. Recommendation for Researchers: Further research should be done to confirm if the provision of a more reliable internet system will boost students’ internet proficiency, which in turn will improve their utilisation of the LMS. Impact on Society: Help create awareness of schooling while pursuing a career and also improve interactions between students and lecturers. It will also improve enrolment and possibly reduce the cost of education in the long-run. Future Research: Researchers can look at the possibility of implementing total virtual learning systems at the tertiary level in Ghana. http://www.informingscience.org/Publications/3742 web-based learning information system information technology IT infrastructure web-based learning management system Moodle eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-07-23 12 209 243 3786 article Iris A Humala Humala.Iris.A@student.uta.fi Aim/Purpose: This study aims to develop a descriptive typology to better identify leadership toward creativity in virtual work in different types of companies. Background: The study empirically explores how leadership toward creativity occurs in virtual work and uses the theoretical lenses of creativity-conducive leadership and heterarchy to generate a typology. Methodology : A multiple qualitative case study design, interpretivist approach, and abductive analysis are applied. Data is collected by interviewing 21 leaders and employees face-to-face in four companies in the ICT sector and one business advisor company. Contribution: The empirical evidence of this study enriches the understanding of leadership toward creativity in virtual work and contributes to the limited empirical knowledge on leadership that stimulates a virtual workforce to achieve creativity. Findings: The four different types of companies in the typology utilize various transitions toward leadership creativity in virtual work. The trend in leadership in the existing virtually networked business environment is toward the “collective mind” company, which is characterized by shared values, meaningful work, collective intelligence, conscious reflection, transparency, coaching, empowering leadership by example, effective multichannel interaction, and assertiveness. The findings empirically support applying a heterarchy perspective to lead a virtual workforce toward creativity and promote leaders who are genuinely interested in people, their development, collaboration, and technology. Recommendations for Practitioners: The typology helps professionals realize the need to develop leadership, communication, interaction, learning, and growth to foster creative interaction and improve productivity and competitiveness. Recommendation for Researchers: This study enables researchers to more rigorously and creatively conceptualize the conditions and relationships in leadership that facilitate creativity in virtual work. Impact on Society : The findings highlight humanistic values for developing leadership. The study strengthens the view that collective creativity in virtual work cannot emerge without virtual and physical interaction in appropriate spaces and caring for each other. Future Research: Future studies may focus on other fields, industries, networks, roles of materialities, and employees in fostering creativity and on theory development. Longitudinal studies are advisable. http://www.informingscience.org/Publications/3786 virtual work creativity leadership typology heterarchy eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-09-06 12 245 268 3853 article Millicent Agangiba agnmil001@myuct.ac.za salah Kabanda salah.kabanda@uct.ac.za Aim/Purpose: The purpose of this paper is to examine the key research foci, methodologies, and theoretical perspectives adopted by researchers when studying E-government accessibility for persons with disabilities (PWDs), particularly in developing countries. The study aims to develop a conceptual framework for designing accessible E-government for PWDs in developing countries. Background: Studies on E-government accessibility for persons with disabilities in developing countries have been minimal. The few studies conducted until now have failed to integrate PWDs, a population already marginalized, into the digital society. Accessibility has been identified by researchers as a major hindrance to PWDs participating in E-government. It is imperative therefore to examine the manner in which researchers investigate and acquire knowledge about this phenomenon. Methodology : The study synthesizes literature from top IS journals following a systematic literature review approach. The data synthesis focuses on identifying key concepts relating to E-government accessibility for PWDs. Contribution: The study contributes to the field of E-government, with a focus on how E-government services can be made accessible to PWDs. The study calls on researchers to reflect on their epistemological and ontological paradigms when examining accessibility of E-government services in developing countries. Findings: The findings show that most researchers focus on the evaluation of E-government websites and predominantly adopt quantitative methods. The study also reveals that the use of technological determinism as a theoretical lens is high among researchers. Recommendations for Practitioners : The study recommends that E-government web developers and policy makers involve PWDs from design to evaluation in the development of E-government applications. Recommendation for Researchers: The study advocates the need to conduct studies on E-government accessibility by employing more qualitative and mixed approaches to gain in-depth and better understanding of the phenomenon. Impact on Society : This study creates greater awareness and points out inadequacies that society needs to address to make E-government more inclusive of and participatory for PWDs. Future Research: Further empirical work is required in order to refine the relevance and applicability of various constructs in EADM so as to arrive at a framework for addressing E-government accessibility for PWDs in developing countries. http://www.informingscience.org/Publications/3853 e-government accessibility persons with disabilities developing countries eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-09-07 12 269 282 3854 article Uzoma Heman Ononye ononye.uz@gmail.com Anthony Igwe igweunec@yahoo.com Aim/Purpose: Facebook has made it possible for organisation to embrace social and network centric knowledge processes by creating opportunities to connect, interact, and collaborate with stakeholders. We have witnessed a significant increase in the popularity and use of this tool in many organisations, especially in the private sector. But the utilisation of Facebook in public organisations is at its infancy, with many also believing that the use of Facebook is not a common practice in many public organisations in Nigeria. In spite of this fact, our discernment on the implications of Facebook usage in public organisations in Nigeria, especially organisations at the local level, seem to be remarkably limited. This paper specifically sought to ascertain if Facebook usage influenced inward and outward knowledge sharing in the selected local government councils in Delta State, Nigeria Methodology: The qualitative method was adopted. The study used interview as the primary means of data gathering. The study purposively sampled thirty-six employees as interviewees, twenty from Oshimili South and sixteen from Oshimili North local government councils respectively. The thematic content analysis method was used to analyse interview transcripts. Contribution: This research made distinct contributions to the available literature in social knowledge management, specifically bringing to the fore the intricacies surrounding the use of Facebook for knowledge sharing purposes in the public sector. Findings: The local government councils were yet to appreciate and utilise the interactive and collaborative nature of Facebook in improving stakeholders’ engagement, feedback, and cooperation. Facebook was used for outward knowledge sharing but not for inward knowledge sharing. Recommendations for Practitioners: Local government councils should encourage interaction via Facebook, show willingness to capture knowledge from identifiable sources, and effectively manage critical knowledge assets in order to build trust, cooperation, and confidence in the system. To gain strategic benefits from the use of Facebook for synchronous communication of knowledge, local government councils should ensure that the use of such technology is aligned with strategic plans and that directional change is in line with the new knowledge economy, where interaction and collaboration through technology are seen as strategic imperatives for continued success and sustainability. In addition, local government councils need to train stakeholders on effective use of Facebook for knowledge sharing, with special emphasis on how, why, who, when, and where to use such tool for knowledge sharing activities. http://www.informingscience.org/Publications/3854 social media Facebook knowledge sharing eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-11-29 12 283 308 3887 article Ayman N. Alkhaldi ayman_alkhaldi@hotmail.com Aim/Purpose: This work aims to understand why a disparity between the popularity of smart phones and the limited adoption of m-banking exists. Accordingly, this study investigates factors that affect a person’s decision to adopt m-banking services. Such an investigation seeks to determine if and to what extent customers’ mobile phone experience as well as their awareness of m-banking services influence their intention to use such services? Background: This study developed a conceptual model to determine the influence that users’ mobile phone experience as well as users’ awareness of m-banking services had on users’ behavioral intention to use m-banking in Saudi Arabia. Methodology: The quantitative method used to collect data was a survey questionnaire tech-nique. A questionnaire with non-structured (close-ended) questions was formulated. A random sample, targeting banking customers in Saudi Arabia, was selected. This study collected data using a cross-sectional survey. Of those surveyed, 389 provided valid responses eligible for data analysis. SPSS v.22 was used to analyze the data. Contribution: This study produced helpful results and a new m-banking conceptual model. The developed conceptual model focused integrally on users’ awareness and experience as antecedents of m-banking adoption and highlighted the im-portance of differentiating between measuring the users’ characteristics in adopting e-banking in general and m-banking services in particular. In addition, this type of model has the ability to synthesize new control variables as well as to study technology acceptance in developing countries. This study, based on an extended UTAUT model, set out to discover what factors might affect customers’ intentions to use m-banking in Saudi Arabia. Findings: The results show that service awareness has a direct effect on performance and effort expectancy, but not on perceived risk. Moreover, mobile phone experience fails to impact the relationships in the same hypothesized direction. As anticipated, performance expectancy, effort expectancy, and perceived risk have direct and significant effects on behavioral intentions to use m-banking. However, customer awareness fails to impact the relationships of performance expectancy, effort expectancy, and perceived risk on behavioral intentions to use m-banking. Recommendations for Practitioners: Banks should target customers by distributing useful information and applying measures to increase acceptance. Banks need to introduce something imaginative to convince bank customers to abandon existing service channels and adopt m-banking services. Banks should make m-banking services the easiest service for conducting bank transactions and/or help customers conduct transactions that they cannot do any other way. Recommendation for Researchers: Other factors, such as trust, culture, and/or credibility should be investigated along with user’s awareness and experience factors in m-banking services. There is a need to focus on a specific type of m-banking. Thus, it may be fruitful to study the adoption of different systems of m-banking services. Impact on Society: This study suggests that m-banking services should be designed and built based on a deep understanding of customers’ needs using extensive testing to assure that applications and sites function well in a mobile setting. Future Research: Future researchers should apply the conceptual model developed in this study in different settings, different countries, and to different technologies. http://www.informingscience.org/Publications/3887 mobile banking mobile commerce mobile phone experience awareness of services behavioral intention to use eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-12-04 12 309 335 3891 article Shamsudeen Ladan Shagari shagareez@gmail.com Akilah Abdullah akilah@uum.edu.my Rafeah Mat Saat rafeah@uum.edu.my Aim/Purpose: The purpose of this study is to investigate the interrelationship among the quality measures of information system success, including system quality, information, quality, and service quality, that eventually influence accounting information systems effectiveness. Background: It is generally believed that investment in an information system offers opportunities to organizations for business process efficiency and effectiveness. Despite huge investments in accounting information systems, banks in Nigeria have not realized the full potential benefits of using these systems because of persistent failures. Few studies have been conducted to address the problem. Methodology: A survey research design was used to collect data, and a total of 287 questionnaires were retrieved from respondents in the Nigerian banking sector. Contribution: This study contributes to the understanding of the most important antecedent factors of the quality measures, the interrelationship among the quality measures, and the influence of these measures on the accounting information systems effectiveness. Findings: The result of the study revealed that security, ease of use, and efficiency are key features of system quality, while the information quality dimension includes accuracy, timeliness, and completeness. The result of the study further revealed that information quality and system quality have significant influences on accounting information systems effectiveness. Recommendations for Practitioners: This study provides practitioners with important measures for evaluation of AIS effectiveness in the context of Nigerian banks. Recommendation for Researchers: Future researchers may build on the findings of current study to conduct fur-ther research in the area of AIS effectiveness in different contexts. Future Research: This study examines only three quality measures of Delone and Mclean model and antecedents of information and system quality measures, neglecting contingency factor. Therefore, future study should include other factors to the AIS effectiveness model to help in developing more specific theory in AIS domain. http://www.informingscience.org/Publications/3891 accounting information systems effectiveness system quality information quality service quality Nigeria eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2017-12-15 12 337 365 3897 article Andre Calitz andre.calitz@nmmu.ac.za Margaret Cullen margaret.cullen@nmmu.ac.za Aim/Purpose: This paper aims to present an example of the application of a Knowledge Man-agement (KM) framework to automotive original component manufacturers (OEMs). The objective is to explore KM according to the four pillars of a selected KM framework. Background: This research demonstrates how a framework, namely the George Washington University’s Four Pillar Framework, can be used to determine the KM status of the automotive OEM industry, where knowledge is complex and can influence the complexity of the KM system (KMS) used. Methodology: An empirical study was undertaken using a questionnaire to gather quantitative data. There were 38 respondents from the National Association of Automotive Component and Allied Manufacturers (NAACAM) and suppliers from three major automotive OEMs. The respondents were required to be familiar with the company’s KMS. Contribution: Currently there is a limited body of research available on the KM implementation frameworks for the automotive industry. This study presents a novel approach to the use of a KM framework to reveal the status of KM in automotive OEMs. At the time of writing, the relationship between the four pillars and the complexity of KMS had not yet been determined. Findings: The results indicate that there is a need to improve KM in the automotive OEM industry. According to the relationships investigated, the four pillars, namely leadership, organization, technology and learning, are considered important for KM, regardless of the level of KMS complexity, Recommendations for Practitioners: Automotive OEMs need to ensure that the KM aspects are established and should be periodically evaluated by using a KM framework such as the George Washington University’s Four Pillar Framework to identify KM weaknesses. Recommendation for Researchers: The establishment and upkeep of a successful KM environment is challenging due to the complexity involved with various influencing aspects. To ensure that all aspects are considered in KM environments, comprehensive KM frameworks, such as the George Washington University’s Four Pillar Framework, need to be applied. Impact on Society: The status of KM management and accessibility of knowledge in organizations needs to be periodically examined, in order to improve supplier and OEM knowledge sharing. Future Research: Although the framework used provides a process for KM status determination, this study could be extended by investigating a methodology that includes KMS best practice and tools. This study could be repeated at a national and international level to provide an indication of KM practice within the entire automotive industry. http://www.informingscience.org/Publications/3897 knowledge management knowledge management system framework automotive industry eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-12-31 11 i iii 2345 article http://www.informingscience.org/Publications/2345 table of contents IJIKM Information Knowledge Management eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-12-31 11 001 016 2340 article Babak Teimourpour va.eslami@gmail.com Vahid Eslami ve_eslami@yahoo.com Milad Padidarfard milad_padidar@yahoo.com Maghsoud Mohammadi sa.afshar81@yahoo.com Helping a company organize and capture the knowledge used by its employees and business processes is a daunting task. In this work we examine several proposed methodologies and synthesize them into a new methodology that we demonstrate through a case study of an electric power distribution company. This is a practical research study. First, the research approach for creating the knowledge map is process-oriented and the processes are considered as the main elements of the model. This research was done in four stages: literature review, model editing, model validation and case study. The Delphi method was used for the research model validation. Some of the important outputs of this research were mapping knowledge flows, determining the level of knowledge assets, expert-area knowledge map, preparing knowledge meta-model, and updating the knowledge map according to the company’s processes. Besides identifying, auditing and visualizing tacit and explicit knowledge, this knowledge mapping enables us to analyze the knowledge areas’ situation and subsequently help us to improve the processes and overall performance. So, a process map does knowledge mapping in a clear and accurate frame. Once the knowledge is used in processes, it creates value. http://www.informingscience.org/Publications/2340 Knowledge mapping knowledge breakdown structure knowledge levelling business-process oriented knowledge management knowledge meta-model eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-02-09 11 017 030 3402 article Sasmita Mishra drsasmitamishra74@gmail.com Prokreeti Mitra prokreetim@gmail.com Recently ERP implementation has seen increasing significance in different sectors. The research related to the implementation issues of ERP has also increased during the past decade. Particularly the behavioral aspects of ERP implementations have been researched in terms of identifying appropriate frameworks, critical success factors, perception and attitude of users and managers, the role of change agents, leadership, etc. This conceptual review summarizes some of the studies done on the above aspects and suggests further research areas. It is suggested that leadership competencies, learning attitude of the users, and organizational power dynamics can be potential areas of research in the context of ERP implementation. http://www.informingscience.org/Publications/3402 ERP Implementation critical success factors perception of users leadership eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-04-12 11 031 053 3434 article Karoly Bozan bozakaro@isu.edu Pratim Datta datta.pratim@gmail.com A central premise for the creation of Electronic Health Records (EHR) is ensuring the portability of patient health records across various clinical, insurance, and regulatory entities. From portability standards such as International Classification of Diseases (ICD) to data sharing across institutions, a lack of portability of health data can jeopardize optimal care and reduce meaningful use. This research empirically investigates the relationship between health records availability and portability. Using data collected from 168 medical providers and patients, we confirm the positive relationship between user perceptions of expected satisfaction with EHR availability and the expected satisfaction with portability. Our findings contribute to more informed practice by understanding how ensuring the availability of patient data by virtue of enhanced data sharing standards, device independence, and better EHR data integration can subsequently drive perceptions of portability across a multitude of stakeholders. http://www.informingscience.org/Publications/3434 Design Theory Data Availability Data Portability Satisfaction Stakeholders Patient Care Processes eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-04-12 11 055 072 3439 article Irena Malgorzata Ali Irena.ali@dsto.defence.gov.au This paper reports on research with a broad objective to examine the relationship between two organizational entities, the formally structured organization and informal organizational structures, in a changing operational environment, more specifically during military deployments. The paper draws on organizational and complexity paradigms; based on empirical evidence obtained through qualitative techniques, it describes mechanisms that enable a symbiotic relationship between these two organizational structures in a complex operational landscape. Substantive findings provide insights into the dynamics of the interactions between these structures and illuminate the relationship between three enabling factors – accountability, responsible autonomy, and command and control arrangements – that need to be considered to fully exploit the strengths inherent in both formal and informal structures. Based on these findings, a model for enhancement of organizational agility in response to changes in a complex operational environment is described. The model is predicated on feedback and mutual adjustment of the organization, institution and individual through sensemaking; it illustrates the dynamic nature of interactions that are required for such a response. http://www.informingscience.org/Publications/3439 organizational studies formal and informal organizational structures – symbiotic re-lationship organizational adaptation organizational agility organizations and institutions complexity frameworks case studies eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-05-04 11 073 087 3450 article Olusola I. Akinbobola solaakinbobola@yahoo.co.uk Akinniyi A. Adeleke erinfaith10@yahoo.com Several studies extended the Technology Acceptance Model (TAM) by examining the antecedents of perceived usefulness and perceived ease of use; the present study looks at demographic aspect of external variables in virtual library use among undergraduate students. The purpose of this study is to identify the demographic factors sex, level of study, cumulative grade point average, and computer knowledge that act as external factors that are antecedents of perceived usefulness and perceived ease of use. The university management makes a large investment in the provision of a virtual library; investigation of the virtual library acceptance by students is important. TAM and theory of reasoned action (TRA) are utilised to theoretically test a model for the extension and to predict virtual library acceptance and usage. In a survey study, data was collected by using a structured questionnaire given to 394 randomly selected participants in a private university. Data were analysed by Pearson product moment correlation, multiple and hierarchical regression. The result of the study is consistent with TAM factors examined for explaining virtual library usage. The extension model accounts for 2.5% variance in perceived usefulness, 2.1% in perceived ease of use, 11.7% - 15.2% on intention to use and 7.2% on actual use of virtual library. Implications of the findings of the study on user’s virtual library training are discussed. http://www.informingscience.org/Publications/3450 Technology acceptance model Theory of reasoned action demographic variables users’ perception virtual library usage eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-05-23 11 089 113 3507 article Ewa Ziemba ewa.ziemba@ue.katowice.pl Information and communication technologies (ICTs) encompassing computer and network hardware and software, and so on, as well as various services and applications associated with them, are assuming a growing presence within the modern homestead and have an indelible impact on the professional and everyday life of people. This research aims to explore factors influencing the successful adoption and usage of ICTs within Polish households. Based on prior literature and practical experiences, a framework of success factors is provided. The required data was collected from a survey questionnaire administered to a sample of Polish households to examine this framework and identifies which factors are of greatest importance for the adoption and usage of ICTs within households in Poland. Based on 751 questionnaires the paper indicates that the adoption of ICTs within households is mainly influenced by the economic status of households and cost of ICTs, perceived economic benefits from the usage of ICTs, technological availability and security of ICTs, ICT competences and awareness, as well as satisfaction with the adoption of ICTs. Furthermore, gender, education, and place of residence do not reflect significant differences on the factors. Yet, there are significant differences among the factors that could be attributed to age. Both, policy makers and ICT providers can benefit from the findings with regard to bridging the gap of ICT adoption and use in the Polish households. http://www.informingscience.org/Publications/3507 ICTs households ICT adoption ICT usage success factors Poland eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-05-29 11 115 139 3456 article Titus Chukwuemezie Okeke tc.okeke@gmail.com Christian Nedu Osakwe osakwe@fame.utb.cz A general belief is that Mobile Money (mMoney) has the catalytic effect of spurring mCommerce growth and driving financial inclusion in developing nations like Nigeria. In Nigeria, mMoney service is certainly a new financial service innovation in the country, and as a result critical issues surrounding its early critical mass adoption, including its perceived usefulness, remain largely opaque. In this paper, our aim was to explore factors influencing perceived usefulness of mMoney by using the extended technology acceptance model (TAM) as the theoretical underpinning of our work. This work is based on a usable sample of 127 respondents from two major cities in Nigeria. Overall, the study’s results indicate that perceived regulator assurance, service affordability, convenience, proximity to the nearest bank branch, and worry over ease of use are significant predictors of mMoney perceived usefulness. The work helps shed new insights about the significant factors that are closely related to the consumer’s perception of the relevance of mMoney services (to his/her financial needs). In sum, the study is an initial step to addressing the issue of perceived usefulness of mMoney service, including its pivotal importance to laying a solid foundation for mCommerce growth in Nigeria and similar sub-Saharan African (SSA) coun-tries. http://www.informingscience.org/Publications/3456 BoP consumer behaviour financial inclusion mMoney mCommerce Nigeria SSA sub-Saharan Africa eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-06-07 11 141 176 3455 article Luis E Valdez juarez38@hotmail.com Domingo García-Pérez de Lema domingo.garcia@upct.es Gonzalo Maldonado-Guzmán gmaldona@correo.uaa.mx For more than two decades, knowledge management (KM) has been examined in the literature and considered a basic factor in business management. The purpose of this article is to explore the ability of knowledge management to achieve small and medium-sized enterprise (SME) innovation and business performance. Data analysis procedures of PLS-SEM was used to analyze the data based on responses from the owners of 903 companies in industry, construction, services, and trade in the Region of Murcia (Spain) through a self-directed survey. The results show that KM has a significant influence on innovation but the influence on the level of performance of SMEs is insignificant. However, training employees as part of KM showed no significant influence on innovation in SMEs. It is important for leaders and managers to have greater openness to changes in the implementation and proper execution of KM. This work contributes primarily to the development of the literature on knowledge management and its relationship with innovation and business performance. http://www.informingscience.org/Publications/3455 Knowledge management (KM) innovation performance small and medium-sized enterprises (SMEs) information and communication technology (ICT) eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-06-27 11 177 199 3528 article Chris W Callaghan chris.callaghan@wits.ac.za Knowledge management research applied to the development of real-time research capability, or capability to solve societal problems in hours and days instead of years and decades, is perhaps increasingly important, given persistent global problems such as the Zika virus and rapidly developing antibiotic resistance. Drawing on swarm intelligence theory, this paper presents an approach to real-time research problem-solving in the form of a framework for understanding the complexity of real-time research and the challenges associated with maximizing collaboration. The objective of this research is to make explicit certain theoretical, methodological, and practical implications deriving from new literature on emerging technologies and new forms of problem solving and to offer a model of real-time problem solving based on a synthesis of the literature. Drawing from ant colony, bee colony, and particle swarm optimization, as well as other population-based metaheuristics, swarm intelligence principles are derived in support of improved effectiveness and efficiency for multidisciplinary human swarm problem-solving. This synthesis seeks to offer useful insights into the research process, by offering a perspective of what maximized collaboration, as a system, implies for real-time problem solving. http://www.informingscience.org/Publications/3528 Knowledge management crowdsourcing swarm solving theory development complex problem solving eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-07-25 11 201 214 3539 article Eunyoung Kim ekim@ischool.t.u-tokyo.ac.jp Hideyuki Horii horii@civil.t.u-tokyo.ac.jp Analogical thinking is one of the most effective tools to generate innovative ideas. It enables us to develop new ideas by transferring information from well-known domains and utilizing them in a novel domain. However, using analogical thinking does not always yield appropriate ideas, and there is a lack of consensus among researchers regarding the evaluation methods for assessing new ideas. Here, we define the appropriateness of generated ideas as having high structural and low superficial similarities with their source ideas. This study investigates the relationship between thinking process and the appropriateness of ideas generated through analogical thinking. We conducted four workshops with 22 students in order to collect the data. All generated ideas were assessed based on the definition of appropriateness in this study. The results show that participants who deliberate more before reaching the creative leap stage and those who are engaged in more trial and error for deciding the final domain of a new idea have a greater possibility of generating appropriate ideas. The findings suggest new strategies of designing workshops to enhance the appropriateness of new ideas. http://www.informingscience.org/Publications/3539 analogical thinking idea generation innovation workshops thinking processes in idea generation assessment of new ideas eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-09-20 11 215 234 3567 article Shahram Nasiri sh.nasiri@sirjantech.ac.ir Asiyeh Sa’adati Azar a.saadatiazar@yahoo.com Mohammad Javad Nasiri mj_nasiri@yahoo.com In order to reduce cost, improve functionality and gain competitive advantages, organizations resort to reengineering projects by developing and making changes to organizational processes. The absence of a unified methodology and appropriate analytic approaches prior to the implementation of reengineering projects has made authorities not to adopt correct decision making approaches in this respect. The objective of this paper is to propose a methodology that has to be adopted prior to the implementation of reengineering projects. The statistical population here consists of 25 expert analysts with MA and PhD degrees who are subject to answering a questionnaire. In this proposed methodology the Multi Criterion Decision Making model is applied to allow the analysts to select appropriate models for better and accurate implementation through the least failure coefficient. The Neyriz White Cement Corporation is selected as the subject and the obtained results are compared with the results obtained from similar implemented projects. http://www.informingscience.org/Publications/3567 Business Process Reengineering Redesigning Processes Improvement Process Multiple-criteria decision-making Analytical Hierarchy Process eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-09-27 11 235 260 3571 article Faisal Iddris faisal.iddris@hh.se Purpose: Innovation capability is a growing and significant area of academic research. However, there is little attempt to provide a cumulative overview of this phenomenon. The purpose of this systematic review is to synthesize peer reviewed articles published in the area to develop a conceptual framework and to aid future research. Design/Methodology/Approach: The paper adopted a systematic review of literature on innovation capability. The final screening generated 51 articles from 30 journals from 2000-2015. Findings: The examination and synthesis of the theoretical and the empirical articles show that (1) the authors applied narrow range of conceptual and theoretical foundations; (2) innovation capability is being investigated mostly at the firm level for about 90% of the articles, and marginally about 5% at network (supply) chain level; (3) the authors define innovation capability in different ways and use diverse set of dimensions to measure innovation capability; (4) there is potential for future research across firms in innovation management disciplines. Practical implications: The review contributes to theory development in organizational capability literature in general. Managers wishing to innovate need to examine critically and integrate some of the innovation capability dimensions proposed in this paper. Originality: The review is unique in the sense that it provides conceptualisation of innovation capability framework. http://www.informingscience.org/Publications/3571 innovation capability collaboration creativity innovation systematic review eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-10-06 11 261 271 3572 article Chengyi LE ncycy@126.com According to the different behavior characteristics of knowledge contribution of enterprise employees, a multi-task principal-agent relationship of knowledge contribution between enterprise and employees is established based on principal-agent theory, analyzing staff’s knowledge contribution behavior of knowledge creation and knowledge participation. Based on this, a multi-task principal agent model for knowledge contribution of enterprise staff is developed to formulate the asymmetry of information in knowledge contribution Then, a set of incentive measures are derived from the theoretic model, aiming to prompt the knowledge contribution in enterprise. The result shows that staff’s knowledge creation behavior and positive participation behavior can influence and further promote each other Enterprise should set up respective target levels of both knowledge creation contribution and knowledge participation contribution and make them irreplaceable to each other. This work contributes primarily to the development of the literature on knowledge management and principal-agent theory. In addition, the applicability of the findings will be improved by further empirical analysis. http://www.informingscience.org/Publications/3572 multi-task principal-agent model knowledge contribution knowledge creation and participation Incentive measures eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-10-10 11 273 283 3576 article Jacques Ophoff jacques.ophoff@uct.ac.za Alastair Irons alastair.irons@sunderland.ac.uk This paper explores the issues facing digital forensics in South Africa. It examines particular cyber threats and cyber threat levels for South Africa and the challenges in addressing the cybercrimes in the country through digital forensics. The paper paints a picture of the cybercrime threats facing South Africa and argues for the need to develop a skill base in digital forensics in order to counter the threats through detection of cybercrime, by analyzing cybercrime reports, consideration of current legislation, and an analysis of computer forensics course provision in South African universities. The paper argues that there is a need to develop digital forensics skills in South Africa through university programs, in addition to associated training courses. The intention in this paper is to promote debate and discussion in order to identify the cyber threats to South Africa and to encourage the development of a framework to counter the threats – through legislation, high tech law enforcement structures and protocols, digital forensics education, digital forensics skills development, and a public and business awareness of cybercrime threats. http://www.informingscience.org/Publications/3576 digital forensics cybercrime legislation skills development South Africa eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-10-31 11 285 308 3588 article Eeva M. Järvenpää eeva.jarvenpaa@tut.fi Miia-Johanna Kopra miia-johanna.kopra@tut.fi Minna Lanz minna.lanz@tut.fi Efficient knowledge and information management is essential for companies to prosper in the rapidly changing global environment. This article presents challenges of a large Finnish multinational company relating to their current knowledge and information management practices and systems. The focus is on New Product Introduction (NPI) process. The study is based on interviews and facilitated workshops in the Research and Development (R&D) and Production departments. Furthermore, the identified challenges are reflected to the findings presented in knowledge and information management literature. The results gained from the company case study were well in line with the findings in the literature. Three main topics, which can be generalized to cause challenges for knowledge and information management in most companies, were recognized: 1) Issues related to human behavior, individual characteristics and capabilities, different backgrounds, and professional vocabulary; 2) Codifying tacit knowledge into explicit information, which can be saved to company information system; 3) Lack of interoperability between different information systems. The study provides the management of the case company, and other similar organizations, focus points while seeking for better knowledge and information management. From a scientific perspective, the main contribution of this article is to give practical examples of how the theoretical findings presented in literature manifest themselves in real industrial practices. http://www.informingscience.org/Publications/3588 knowledge management information management knowledge creation knowledge sharing information sharing information flows case study eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-11-08 11 309 330 3591 article Brenda M Scholtz brenda.scholtz@nmmu.ac.za Imran Mahmud imranmahmud@daffodilvarsity.edu.bd Ramayah T. ramayah@usm.my Though the field of management information systems, as a sector and a discipline, is the inventor of many guidelines and models, it appears to be a slow runner on practical implications of interface usability. This usability can influence end users’ attitude and behavior to use IT. The purpose of this paper was to examine the interface usability of a popular Enterprise Resource Planning (ERP) software system, SAP, and to identify related issues and implications to the Technology Acceptance Model (TAM). A survey was conducted of 112 SAP ERP users from an organization in the heavy metal industry in Bangladesh. The partial least squares technique was used to analyze the survey data. The survey findings empirically confirmed that interface usability has a significant impact on users’ perceptions of usefulness and ease of use which ultimately affects attitudes and intention to use the ERP software. The research model extends the TAM by incorporating three criteria of interface usability. It is the first known study to investigate usability criteria as an extension of TAM. http://www.informingscience.org/Publications/3591 Enterprise Resource Planning Interface usability ERP usability Technology Acceptance Model Partial Least Squares eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-11-26 11 331 345 3607 article Adebowale I Ojo adebowaleojo@ymail.com Universities have traditionally been leaders in the field of knowledge production, research, and societal development. They are expected to be drivers of innovation, thereby contributing to the development of a learning society. The array of challenges facing universities in Nigeria and other developing countries forces one to question their levels of innovation. While knowledge management has been identified as a strategy for driving innovative processes in business organizations, there is a paucity of literature on its application in Nigerian universities. This paper, therefore, proposes a conceptual model which Nigerian universities could adopt, in order to drive innovation and performance. As the paper is conceptual in nature, a literature survey was conducted to examine the concept of knowledge management and its application in higher education institutions. Findings from the literature informed the development of a conceptual model describing ways in which universities can adopt knowledge management practices and strategies in order to drive innovation and improve performance. The conceptual model proposed in this paper could serve as a basis for empirical investigations on knowledge management processes in universities. The paper concludes that, while knowledge management has the potential for improving performance within universities, the proposed model must be subjected to empirical validation for further amendments and improvements. http://www.informingscience.org/Publications/3607 knowledge management higher education innovation university Nigeria eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2016-11-27 11 347 365 3610 article Maxine P Esterhuyse maxine.esterhuyse@nmmu.ac.za Brenda M Scholtz brenda.scholtz@nmmu.ac.za Danie Venter danie.venter@nmmu.ac.za Together, the fields of education and information technology have identified the need for an online solution to training. The introduction of e-learning has optimised the learning process, allowing organisations to realise the many advantages that e-learning offers. The importance of user involvement in the success of e-learning makes it imperative that the forces driving intention to use e-learning and satisfaction thereof be determined. The purpose of this paper is to investigate the relationships between the metrics influencing intention to use and the satisfaction of using e-learning in companies. The results of a survey distributed amongst a South African software development company’s customer base revealed that the 94 respondents have positive enjoyment and self-efficacy levels, and low computer anxiety levels. Correlation analysis revealed significant relationships between enjoyment and self-efficacy and between enjoyment and satisfaction. Companies should therefore ensure that users enjoy using e-learning as it can directly influence satisfaction and self-efficacy. http://www.informingscience.org/Publications/3610 e-learning intention satisfaction survey self-efficacy enjoyment computer anxiety eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-02-23 10 i iii 2118 article Kevin A. Johnston kevin.johnston@uct.ac.za Elsje Scott elsje.scott@uct.ac.za Mike Hart mike.hart@uct.ac.za This table of contents will be updated throughout the year as new papers are published. http://www.informingscience.org/Publications/2118 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-02-23 10 001 019 2120 article Danny Wee Hock Quik danny.quik@aut.ac.nz Nevan Wright nevan@ais.ac.nz Ammar Rashid ammar.rashid@ucp.edu.pk Sivadass Thiruchelvam sivadass@uniten.edu.my The purpose of the study is to identify influential factors in the use of collaborative networks within the context of manufacturing. The study aims to investigate factors that influence employees’ learning, and to bridge the gap between theory and praxis in collaborative networks in manufacturing. The study further extends the boundary of a collaborative network beyond enterprises to include suppliers, customers, and external stakeholders. It provides a holistic perspective of collaborative networks within the complexity of the manufacturing environment, based on empirical evidence from a questionnaire survey of 246 respondents from diverse manufacturing industries. Drawing upon the socio-technical systems (STS) theory, the study presents the theoretical context and interpretations through the lens of manufacturing. The results show significant influences of organizational support, promotive interactions, positive interdependence, internal-external learning, perceived effectiveness, and perceived usefulness on the use of collaborative networks among manufacturing employees. The study offers a basis of empirical validity for measuring collaborative networks in organizational learning and knowledge/information sharing in manufacturing. http://www.informingscience.org/Publications/2120 Employees’ learning collaborative networked learning collaborative networks socio-technical systems theory eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-04-27 10 021 035 2207 article Yan Lu lyan@bgsu.edu Joseph T. Chao jchao@bgsu.edu Kevin R. Parker parkerkr@isu.edu This project shows a creative approach to the familiar scavenger hunt game. It involved the implementation of an iPhone application, HUNT, with Augmented Reality (AR) capability for the users to play the game as well as an administrative website that game organizers can use to create and make available games for users to play. Using the HUNT mobile app, users will first make a selection from a list of games, and they will then be shown a list of objects that they must seek. Once the user finds a correct object and scans it with the built-in camera on the smartphone, the application will attempt to verify if it is the correct object and then display associated multi-media AR content that may include images and videos overlaid on top of real world views. HUNT not only provides entertaining activities within an environment that players can explore, but the AR contents can serve as an educational tool. The project is designed to increase user involvement by using a familiar and enjoyable game as a basis and adding an educational dimension by incorporating AR technology and engaging and interactive multimedia to provide users with facts about the objects that they have located http://www.informingscience.org/Publications/2207 Software Engineering Augmented Reality iOS Application Scavenger Hunt eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-04-28 10 037 046 2208 article George Gatuha ggrpb@yahoo.com Tao Jiang jiangtao@hrbeu.edu.cn Health Data collection is one of the major components of public health systems. Decision makers, policy makers, and medical service providers need accurate and timely data in order to improve the quality of health services. The rapid growth and use of mobile technologies has exerted pressure on the demand for mobile-based data collection solutions to bridge the information gaps in the health sector. We propose a prototype using open source data collection frameworks to test its feasibility in improving the vaccination data collection in Kenya. KenVACS, the proposed prototype, offers ways of collecting vaccination data through mobile phones and visualizes the collected data in a web application; the system also sends reminder short messages service (SMS) to remind parents on the date of the next vaccination. Early evaluation demonstrates the benefits of such a system in supporting and improving vaccination of children. Finally, we conducted a qualitative study to assess challenges in remote health data collection and evaluated usability and functionality of KenVACS. http://www.informingscience.org/Publications/2208 Health Data collection Short Message Service Open Source data frameworks Mobile Technologies Vaccination Kenya eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-08-02 10 047 062 2185 article Ewa Ziemba ewa.ziemba@ue.katowice.pl Iwona Oblak iwona.oblak@ue.katowice.pl It can be argued that public organizations, in order to provide the public with sufficient services in the current, highly competitive and continuously evolving environment, require changes. The changes that become necessary are often related to the implementation of information systems (IS). Moreover, when organizations are faced with changes, a change management (CM) process needs to be put in place. CM theories that are currently available to practitioners and academics are often contradictory; they mostly lack empirical evidence and are supported by unchallenged hypotheses concerning the nature of the contemporary CM. The aim of this paper is, therefore, to identify critical success factors (CFSs) for CM in IS projects. In order to reach this aim an explanation of changes in public organizations and the nature of CM are presented. Following this, a framework of CFSs for CM in IS projects are identified based on the literature review. The paper also examines two IS projects and uses them to demonstrate CFSs influencing CM in IS projects in Polish pubic organizations. A discussion of the research findings is provided and the paper concludes with a presentation of the study’s contributions and limitations as well as the stream of future work. http://www.informingscience.org/Publications/2185 project management change management public organizations information systems IS critical success factors CSF eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-06-09 10 063 080 2265 article Raafat George Saadé rsaade@jmsb.concordia.ca James Wan jwan@icao.int Heliu Dong heliudong199766@gmail.com This research seeks to analyse the project success factors related to project managers’ traits. The context of the research entails a ‘United Nations’ type of organization. Critical success factors from previous recent studies were adopted for this research. Nineteen factors were adopted and a survey methodology approach was followed. Sixty six participants completed the survey. Exploratory factor analysis results revealed the existence of two constructs: project manager engagement, and project manager certification. The total number of factors representing these two constructs after the factor reduction exercise is nine. Our findings indicate that the capacity for a project manager to communicate and lobby for the project to create and sustain positive perceptions, is the most important factor; whereas project manager credentials are viewed as not important for his/her success. The results may seem counter-intuitive, however, in the context of United Nations Organizations, consideration of their political, cultural and international nature reveals that the results apply. http://www.informingscience.org/Publications/2265 Project Manager United Nations Critical Success Factors. eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-07-17 10 081 103 2283 article Ayman Alarabiat sec@dsi.uminho.pt Samer Al-Mohammad samer_f3@yahoo.com The purpose of this paper was to explore the current and potential use of Facebook for learning purposes by Jordanian university students. The paper attempted to compare such use with other uses of Facebook. Further, the paper investigated Jordanian university students’ attitudes towards using Facebook as a formal academic tool, through the use of course-specific Facebook groups. To that end, quantitative data were collected from a sample of 451 students from three Jordanian public universities. Findings indicated that the vast majority of Jordanian students had Facebook accounts, which echoes its popularity amongst Jordanian youth compared to other types of online social networking sites. While both “social activities” and “entertainment” were the primary motivators for Jordanian students to create and use Facebook accounts, a growing number of them were using Facebook for academic purposes too. Further, Jordanian students had a positive attitude toward the use of “Facebook groups” as an educational tool for specific courses, and under specific conditions. Based on its findings, the paper provides suggestions for Jordanian higher institutions to invest in the application of Facebook as a formal academic tool. http://www.informingscience.org/Publications/2283 Facebook social networks academic context purposes uses universities Jordan eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-07-17 10 105 116 2284 article Nemwel Aming'a nemwel.aming'a@kisiiuniversity.ac.ke Knowledge management and knowledge assets have gained much prominence in recent years and are said to improve organizational performance. Knowledge capture and acquisition mechanisms enhance organizational memory and performance. However, knowledge capture and acquisition mechanisms in higher education institutions are not well known. The aim of this study was to investigate the knowledge capture and acquisition mechanisms at Kisii University. This was a case study in which data were collected through interviews and questionnaires. Purposive sampling was used to determine interview participants while questionnaire respondents were selected through stratified random sampling. Qualitative and quantitative data were analysed using SPSS® student version 14; it revealed that there were various knowledge capture and acquisition mechanisms at Kisii University. It was also established that the University encountered various challenges in knowledge capture and acquisition and lacked some essential knowledge capture and acquisition mechanisms. In this regard, this study proposed knowledge capture and acquisition guidelines that may be adopted by the University to enhance its organizational memory and performance. http://www.informingscience.org/Publications/2284 Knowledge Management Mechanisms Knowledge Capture and Acquisition mechanisms knowledge capture and acquisition eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-07-29 10 117 143 2279 article Thale Kvernberg Andersen thale.k.andersen@sintef.no Power differences affect implementation of information and communication technology (ICT) in a way that creates differences in ICT use. Involuntary non-use of new ICT at work occurs when employees want to use the new technology, but are unable to due to factors beyond their control. Findings from an in-depth qualitative study show how involuntary non-use of new ICT can be attributed to power differences between occupational groups in the same organization. The findings suggest that experience is a moderating variable and that closeness to formal power holders as well as closeness to the new technology increases the probability for expert control of the ICT-organization processes. These power differences favor ICT experts over ICT novices and result in a high-quality learning environment for the ICT experts characterized by autonomy, inclusion, and adequate work processes and technological solutions. The ICT novices try to navigate in a learning-hostile work environment characterized by marginalization through expert control, isolation, and inadequate work processes and technological solutions. This led to involuntary non-use by the ICT novices, while the experts became more proficient in ICT use. These findings give managers facing a technological organizational change tools to understand important mechanisms for implementing the change in their own organization, and help them take the right actions to integrate new technology and new organization of work. http://www.informingscience.org/Publications/2279 ICT implementation power organizational change involuntary non-use working conditions learn-ing ICT resistance eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-10-06 10 145 172 2301 article Soud Almahamid soud.almahamid@ahu.edu.jo Omer Awsi omer_awsi@hotmail.com This study aims to examine the impact of organizational environment (top management support, company-wide support, business process reengineering, effective project management, and organizational culture) and enterprise resource planning (ERP) vendor environment (ERP vendor support) on ERP perceived benefits. In order to achieve the study’s aim, a questionnaire was developed based on the extant literature to collect relevant data from the research informants. The population for this research consisted of all users of Microsoft Dynamics Great Plains (a typical type of enterprise system), which is frequently used in Jordanian companies in Amman City. A random sample of 30% of the research population was selected. The results revealed that business process reengineering, effective project management, company-wide support, and organizational culture have a positive correlation with ERP perceived benefits, whereas top management support does not. In addition, there is a significant positive correlation between vendor support and ERP perceived benefits. Academic and practical recommendations are provided. http://www.informingscience.org/Publications/2301 top management support business process reengineering effective project management company-wide support organizational culture vendor support SMEs ERP benefits eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-10-27 10 173 192 2313 article Ryan Wark warkr@san.rr.com Jon K. Webber drjonwebber@gmail.com Collaboration technologies enable people to communicate and use information to make organizational decisions. The United States Navy refers to this concept as information dominance. Various collaboration technologies are used by the Navy to achieve this mission. This qualitative descriptive study objectively examined how a matrix oriented Navy activity perceived an implemented collaboration technology. These insights were used to determine whether a specific collaboration technology achieved a mission of information dominance. The study used six collaboration themes as a foundation to include: (a) Cultural intelligence, (b) Communication, (c) Capability, (d) Coordination, (e) Cooperation, and (f) Convergence. It was concluded that collaboration technology was mostly perceived well and helped to achieve some levels of information dominance. Collaboration technology improvement areas included bringing greater awareness to the collaboration technology, revamping the look and feel of the user interface, centrally paying for user and storage fees, incorporating more process management tools, strategically considering a Continuity of Operations, and incorporating additional industry best practices for data structures. Emerging themes of collaboration were collected to examine common patterns identified in the collected data. Emerging themes included acceptance, awareness, search, scope, content, value, tools, system performance, implementation, training, support, usage, structure, complexity, approach, governance/configuration management/policy, and resourcing. http://www.informingscience.org/Publications/2313 Government Business Intelligence Collaboration Information Technology E-collaboration eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-11-07 10 193 215 2322 article Stefan Holgersson stefan.holgersson@liu.se This paper contributes to the limited research on roles ICT can play in impression-management strategies and is based on case studies done in the Swedish Police. It also gives a theoretical contribution by adopting a holistic approach to explain how ICT can contribute to giving a misleading picture of conditions. Output generated by ICT has nowadays a central role in follow-up activities and decision-making. Even if this type of output, often in colourful, presentable, graphical arrangements, gives the impression of being accurate and reliable there is a risk of defective data quality. The phenomena can be described as a process divided into five steps. The first step is about how the data is generated and/or collected. The second step is linked to how the data is registered. The third step is about the output generated from the ICT-systems. The fourth step is how the output of ICT is selected for presentation. The fifth step concerns how output generated by ICT is interpreted. This paper shows that ICT can easily be used in impression-management strategies. For example, that personnel take shortcuts to affect the statistics rather than applying methods that may give the desired effects. http://www.informingscience.org/Publications/2322 ICT information quality output impression-management misleading decision-making eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2015-12-21 10 217 233 2338 article Alexei Botchkarev alexei.botchkarev@ontario.ca Return on Investment (ROI) is one of the most popular performance measurement and evaluation metrics. ROI analysis (when applied correctly) is a powerful tool in comparing solutions and making informed decisions on the acquisitions of information systems. The purpose of this study is to provide a systematic research of the accuracy of the ROI evaluations in the context of information systems implementations. Measurements theory and error analysis, specifically propagation of uncertainties methods, were used to derive analytical expressions for ROI errors. Monte Carlo simulation methodology was used to design and deliver a quantitative experiment to model costs and returns estimating errors and calculate ROI accuracies. Spreadsheet simulation (Microsoft Excel spreadsheets enhanced with Visual Basic for Applications) was used to implement Monte Carlo simulations. The main contribution of the study is that this is the first systematic effort to evaluate ROI accuracy. Analytical expressions have been derived for estimating errors of the ROI evaluations. Results of the Monte Carlo simulation will help practitioners in making informed decisions based on explicitly stated factors influencing the ROI uncertainties. http://www.informingscience.org/Publications/2338 Return on Investment ROI evaluation costs benefits accuracy estimation error error propagation uncertainty information system performance measure business value eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 i iii 1934 article http://www.informingscience.org/Publications/1934 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 001 018 1935 article James N. Morgan James.Morgan@nau.edu Sury Ravindran sury.ravindran@nau.edu http://www.informingscience.org/Publications/1935 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 019 030 1936 article Joseph T. Chao jchao@bgsu.edu Tanxin Du tdu@bgsu.edu Christopher Wagenheim cwagenh@bgsu.edu Theodore Rippey theodor@bgsu.edu http://www.informingscience.org/Publications/1936 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 031 058 1939 article Ewa Ziemba ewa.ziemba@ue.katowice.pl Iwona Oblak iwona.oblak@ue.katowice.pl http://www.informingscience.org/Publications/1939 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 059 088 1946 article Aleksandar Bulajic LANB@45.dk Radoslav Stojic radoslav.stojic@metropolitan.ac.rs Samuel Sambasivam ssambasivam@apu.edu http://www.informingscience.org/Publications/1946 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 089 116 1963 article Joseph Johnson johns369@uwp.edu Susan J. Lincke lincke@uwp.edu Ralf Imhof r.imhof@ostfalia.de Charles Lim charles.lim@sgu.ac.id http://www.informingscience.org/Publications/1963 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 117 130 1993 article Noushin Ashrafi Noushin.ashrafi@umb.edu Lori Kelleher lorikelleher4@gmail.com Jean-Pierre Kuilboer Jeanpierre.kuilboer@umb.edu http://www.informingscience.org/Publications/1993 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 131 152 2023 article Martti Mäkimattila martti.makimattila@lut.fi Minna Saunila minna.saunila@lut.fi Juho Salminen juho.salminen@lut.fi http://www.informingscience.org/Publications/2023 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 153 174 2073 article Jing-Hua Li jhli@mail.zjgsu.edu.cn Qui-Bo Huang hqb919@163.com Li Lin kantarlily@126.com http://www.informingscience.org/Publications/2073 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-01-01 9 175 191 2080 article Ying Huang samanthanew@gmail.com Xingjun Wang xingjun.wang@qq.com Mickaël Gardoni mickael.gardoni@etsmtl.ca Coulibaly Amadou amadou.coulibaly@insa-strasbourg.fr http://www.informingscience.org/Publications/2080 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2014-12-18 9 193 207 2085 article David J. Cornforth David.Cornforth@Newcastle.edu.au Dean Robinson dj.robinson09@gmail.com Ian Spence ian.spence@sydney.edu.au Herbert Jelinek HJelinek@csu.edu.au This work investigated the suitability of a new tool for decision support in training programs of high performance athletes. The aim of this study was to find a reliable and robust measure of the fitness of an athlete for use as a tool for adjusting training schedules. We examined the use of heart rate recovery percentage (HRr%) for this purpose, using a two-phased approach. Phase 1 consisted of testing the suitability of HRr% as a measure of aerobic fitness, using a modified running test specifically designed for high-performance team running sports such as football. Phase 2 was conducted over a 12-week training program with two different training loads. HRr% measured aerobic fitness and a running time-trial measured performance. Consecutive measures of HRr% during phase 1 indicated a Pearson’s r of 0.92, suggesting a robust measure of aerobic fitness. During phase 2, HRr% reflected the training load and significantly increased when the training load was reduced between weeks 4 to 5. This work shows that HRr% is a robust indicator of aerobic fitness and provides an on-the-spot index that is useful for training load adjustment of elite-performance athletes. http://www.informingscience.org/Publications/2085 heart rate recovery decision support training schedule high performance sport aerobic fitness eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 i iii 1784 article http://www.informingscience.org/Publications/1784 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 001 019 1785 article Ewa Ziemba ewa.ziemba@ue.katowice.pl Iwona Oblak iwona.oblak@ue.katowice.pl http://www.informingscience.org/Publications/1785 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 021 041 1786 article Mirva Hyypiä mirva.hyypia@lut.fi Satu Parjanen satu.parjanen@lut.fi http://www.informingscience.org/Publications/1786 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 043 057 1892 article Olusola I. Akinbobola solaakinbobola@yahoo.co.uk Akinniyi A. Adeleke erinfaith10@yahoo.com http://www.informingscience.org/Publications/1892 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 059 082 1902 article Anna-Maija Nisula anna-maija.nisula@lut.fi Aino Kianto aino.kianto@lut.fi http://www.informingscience.org/Publications/1902 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 083 097 1904 article Fan-Yun Pai fypai@cc.ncue.edu.tw Hung-Fan Chang much2431@pchome.com.tw http://www.informingscience.org/Publications/1904 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2013-01-01 8 99 119 1924 article Momir Beljić momir.beljic@lut.fi Virgilio Panapanaan Virgilio.Panapanaan@lut.fi Lassi Linnanen Lassi.Linnanen@lut.fi Tuomo Uotila tuomo.uotila@lut.fi http://www.informingscience.org/Publications/1924 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 i iii 1547 article http://www.informingscience.org/Publications/1547 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 001 020 1548 article Tantatape Brahmasrene tbrahmasrene@pnc.edu Jung-Wan Lee jwlee119@bu.edu http://www.informingscience.org/Publications/1548 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 021 038 1563 article Anne Kallio anne.kallio@lut.fi Paula Kujansivu paula.kujansivu@prodia.fi Satu Parjanen satu.parjanen@lut.fi http://www.informingscience.org/Publications/1563 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 039 043 1576 article Jelena Jovanovic jeljov@gmail.com Raymond Chiong rchiong@swin.edu.au Thomas Weise tweise@gmx.de http://www.informingscience.org/Publications/1576 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 045 061 1577 article Ruti Gafni rutigafn@mta.ac.il Moran Deri momorr3@gmail.com http://www.informingscience.org/Publications/1577 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 063 090 1578 article Nicole A. Buzzetto-More nabuzzetto-more@umes.edu http://www.informingscience.org/Publications/1578 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 091 107 1579 article Glen Hordemann glenh@bgsu.edu Joseph T. Chao jchao@bgsu.edu http://www.informingscience.org/Publications/1579 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 109 128 1580 article Satu Parjanen satu.parjanen@lut.fi http://www.informingscience.org/Publications/1580 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 129 150 1584 article Celina M. Olszak olszak@ue.katowice.pl Ewa Ziemba ewa.ziemba@ue.katowice.pl http://www.informingscience.org/Publications/1584 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 151 176 1713 article Leif Jarle Gressgård ljg@iris.no http://www.informingscience.org/Publications/1713 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 177 199 1721 article Nina Evans nina.evans@unisa.edu.au James Price james.price@experiencematters.com.au http://www.informingscience.org/Publications/1721 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 201 203 1747 article Jelena Jovanovic jeljov@gmail.com Raymond Chiong rchiong@swin.edu.au http://www.informingscience.org/Publications/1747 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 205 220 1748 article M. O. Thirunarayanan thiru@fiu.edu Manuel Vilchez mvilc002@fiu.edu http://www.informingscience.org/Publications/1748 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 221 236 1749 article Goran Pero Šimi? gshimic@gmail.com http://www.informingscience.org/Publications/1749 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2012-01-01 7 237 255 1750 article Joseph Barjis J.Barjis@tudelft.nl Ashish Gupta gupta@mnstate.edu Ramesh Sharda ramesh.sharda@okstate.edu Tatiana Bouzdine-Chameeva tatiana.chameeva@bem.edu Peggy D. Lee pedalee@iupui.edu Alexander Verbraeck a.verbraeck@tudelft.nl http://www.informingscience.org/Publications/1750 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 1338 article http://www.informingscience.org/Publications/1338 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 001 016 1337 article Matthew Jelavic matthew.jelavic@gmail.com http://www.informingscience.org/Publications/1337 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 017 033 1360 article Hamid Rahimi dr.hamid.rahimi@gmail.com Azizollah Arbabisarjou arbabisarjou2007@gmail.com Sayeed Mohsen Allammeh dr_allameh@ase.ui.ac.ir Razieh Aghababaei http://www.informingscience.org/Publications/1360 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 035 072 1361 article Raafat George Saadé rsaade@jmsb.concordia.ca Fassil Nebebe fnebebe@jmsb.concordia.ca Tak Mak takmak@jmsb.concordia.ca http://www.informingscience.org/Publications/1361 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 073 083 1365 article Kirby McMaster kmcmaster@weber.edu Samuel Sambasivam ssambasivam@apu.edu Nicole Anderson nanderson@winona.edu http://www.informingscience.org/Publications/1365 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 085 094 1366 article Sabra E. Brock sabraebrock@gmail.com Yogini Joglekar Yogini_joglekar@yahoo.com http://www.informingscience.org/Publications/1366 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 095 106 1367 article Jo Coldwell-Neilson jo.neilson@deakin.edu.au Annemieke Craig Annemieke.craig@deakin.edu.au Annegret Goold agoold@deakin.edu.au http://www.informingscience.org/Publications/1367 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 107 118 1370 article Hans Lehmann hans.lehmann@vuw.ac.nz http://www.informingscience.org/Publications/1370 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 119 135 1371 article Rachel Or-Bach orbach@yvc.ac.il Bert Bredeweg B.Bredeweg@uva.nl http://www.informingscience.org/Publications/1371 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 137 150 1372 article Maja Dimitrijevic majadimi@gmail.com Zita Bošnjak bzita@ef.uns.ac.rs http://www.informingscience.org/Publications/1372 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 151 161 1373 article Yair Levy levyy@nova.edu Timothy J. Ellis ellist@nova.edu http://www.informingscience.org/Publications/1373 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 163 176 1374 article Dimitar Grozdanov Christozov dchristozov@yahoo.com Stefanka Chukova stefanka@gmail.com Plamen Mateev pmat@fmi.uni-sofia.bg http://www.informingscience.org/Publications/1374 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 177 196 1375 article Bob Travica btravica@cc.umanitoba.ca http://www.informingscience.org/Publications/1375 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 197 216 1392 article Celina M. Olszak olszak@ue.katowice.pl Ewa Ziemba ewa.ziemba@ue.katowice.pl http://www.informingscience.org/Publications/1392 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2011-01-01 6 217 230 1431 article Ojiabo Ukoha oukoha@umes.edu Hart Okorie Awa awa.hartouph@yahoo.com Christen A. 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Michael Mcgrath Michael.McGrath@vu.edu.au http://www.informingscience.org/Publications/1120 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 061 072 1121 article Dimitar Grozdanov Christozov dchristozov@yahoo.com Stefanka Chukova stefanka@gmail.com Plamen Mateev pmat@fmi.uni-sofia.bg http://www.informingscience.org/Publications/1121 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 073 081 1124 article Pao-Nan Chou sigurdchou@gmail.com Hsi-Chi Hsiao hchsiao@csu.edu.tw http://www.informingscience.org/Publications/1124 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 083 099 1125 article Olga Ormandjieva ormandj@encs.concordia.ca Adel Khelifi a.khelifi@alhosnu.ae Leon Jololian leon.jololian@zu.ac.ae http://www.informingscience.org/Publications/1125 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 101 114 1126 article Jim Everett Jim.Everett@uwa.edu.au http://www.informingscience.org/Publications/1126 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 115 125 1127 article Ruti Gafni rutigafn@mta.ac.il Nitza Geri nitzage@openu.ac.il http://www.informingscience.org/Publications/1127 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 127 137 1134 article Jorge Pérez jperez@kennesaw.edu Meg Coffin Murray isdoctor@gmail.com http://www.informingscience.org/Publications/1134 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 139 151 1133 article Kevin Johnson kevin.johnson@ul.ie Catherine Lillis Catherine.Lillis@UL.ie http://www.informingscience.org/Publications/1133 eng Informing Science Institute Interdisciplinary Journal of Information, Knowledge, and Management (IJIKM) 1555-1229 1555-1237 2010-01-01 5 153 166 1153 article Olufunke R. Vincent vincent.rebecca@gmail.com Olusegun Folorunso folorunsolusegun@yahoo.com Adio Taofiki Akinwale aatakinwale@yahoo.com Adebayo D. 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