Influence Factors on the Adoption of a Financial Application [Abstract]
InSITE 2019
• 2019
• pp. 227-229
Aim/Purpose: Today more and more transactions and acquisitions are controlled directly from mobile devices, especially smartphones applications. Previous studies have examined the adoption of financial applications based on a single theory as a theoretical basis. In order to examine the phenomenon in a wider way, we used in this study two theories as a theoretical basis.
Background: It is important to define the main technological and psychological factors that affect the choice of potential customers to adopt or prefer financial applications. By combining two theories in the study, we expanded the examination of the phenomenon of adopting financial technology.
Methodology: The study questionnaire was based on two questionnaires from previous studies. The questionnaire was tested on a focus group and certain adjustments were made based on the feedback. Thereupon, the questionnaire was sent online via social media. A total of 497 questionnaires were received, 402 were filled correctly and found suitable for statistical analysis. The statistical analysis included Alpha Cronbach Test, Pearson correlation test, and linear regression.
Contribution: By combining DIT theory (Diffusion of Innovative Technology) suggested by Rogers, and TAM model (Technology Acceptance Model) presented by Davis, we expanding our understanding of the technological and psychological factors affecting financial application validation. Finding the influencing factors can help develop and implement future financial applications. Banks will be able to develop applications that truly meet the needs, desires and concerns of their target customers, thus able to save costs and improve their services to their customers.
Findings: Six factors were tested in this study: relative advantage, complexity, compatibility, observability, experiencing, and perceived risk. The main findings showed significant negative correlation between age and relative advantage, so that as the age of the user increased the relative advantage decreased. In addition, a significant positive correlation was found between age and observability, so that as the age of the user increased the observability decreased. Also was found a significant negative correlation between age and the variable adoption of a financial application, so that as the age of the subject increases the financial application adoption decreases. No significant correlation was found between age and compatibility, complexity, relative risk. In addition, a significant positive correlation was found between the numbers of months of experience that the bank offers to the customers to the positive decision to adopt a financial application. No significant correlation was found between the demographic variables, education and wages, and financial application adoption. The regression analysis led to a significant result, so that the variables together explain 69.3% adoption of financial application. According to the research hypothesis, the relative advantage, compatibility, experiencing, and observability have the most significant positive effect on financial application adoption.
Recommendations for Practitioners: We recommend programmers to focus on meeting the customers’ needs that best match the criteria delineated above. In addition, by understanding the influencing factors, marketers should use these criteria to reduce the psychological concerns of customers that delay the adoption of a financial application.
Recommendations for Researchers: Since financial applications are becoming more useful as financial transfers, other behavioral aspects that influence the adoption of technology should be examined. We recommend conducting further research based on behavioral, economic, and technological theories.
Impact on Society: A better understanding of the influencing factors will derive a better planning and development of financial applications, regarding the three most significant factors: relative advantage, compatibility, and observability. This process will result better and wider adoption of financial applications by customers, and will bring more customers to use financial transfers by smartphones.
Future Research: Other studies can be used other theoretical basis for research; to examine specific populations, for example, in terms of older populations; to examine cultural and social influences factors on the adoption of financial applications.
Background: It is important to define the main technological and psychological factors that affect the choice of potential customers to adopt or prefer financial applications. By combining two theories in the study, we expanded the examination of the phenomenon of adopting financial technology.
Methodology: The study questionnaire was based on two questionnaires from previous studies. The questionnaire was tested on a focus group and certain adjustments were made based on the feedback. Thereupon, the questionnaire was sent online via social media. A total of 497 questionnaires were received, 402 were filled correctly and found suitable for statistical analysis. The statistical analysis included Alpha Cronbach Test, Pearson correlation test, and linear regression.
Contribution: By combining DIT theory (Diffusion of Innovative Technology) suggested by Rogers, and TAM model (Technology Acceptance Model) presented by Davis, we expanding our understanding of the technological and psychological factors affecting financial application validation. Finding the influencing factors can help develop and implement future financial applications. Banks will be able to develop applications that truly meet the needs, desires and concerns of their target customers, thus able to save costs and improve their services to their customers.
Findings: Six factors were tested in this study: relative advantage, complexity, compatibility, observability, experiencing, and perceived risk. The main findings showed significant negative correlation between age and relative advantage, so that as the age of the user increased the relative advantage decreased. In addition, a significant positive correlation was found between age and observability, so that as the age of the user increased the observability decreased. Also was found a significant negative correlation between age and the variable adoption of a financial application, so that as the age of the subject increases the financial application adoption decreases. No significant correlation was found between age and compatibility, complexity, relative risk. In addition, a significant positive correlation was found between the numbers of months of experience that the bank offers to the customers to the positive decision to adopt a financial application. No significant correlation was found between the demographic variables, education and wages, and financial application adoption. The regression analysis led to a significant result, so that the variables together explain 69.3% adoption of financial application. According to the research hypothesis, the relative advantage, compatibility, experiencing, and observability have the most significant positive effect on financial application adoption.
Recommendations for Practitioners: We recommend programmers to focus on meeting the customers’ needs that best match the criteria delineated above. In addition, by understanding the influencing factors, marketers should use these criteria to reduce the psychological concerns of customers that delay the adoption of a financial application.
Recommendations for Researchers: Since financial applications are becoming more useful as financial transfers, other behavioral aspects that influence the adoption of technology should be examined. We recommend conducting further research based on behavioral, economic, and technological theories.
Impact on Society: A better understanding of the influencing factors will derive a better planning and development of financial applications, regarding the three most significant factors: relative advantage, compatibility, and observability. This process will result better and wider adoption of financial applications by customers, and will bring more customers to use financial transfers by smartphones.
Future Research: Other studies can be used other theoretical basis for research; to examine specific populations, for example, in terms of older populations; to examine cultural and social influences factors on the adoption of financial applications.
financial application, IT adoption, mobile banking, technology acceptance model, diffusion innovation theory
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