Agile Supply Chain Management Theories, Empirical Data, and Future Directions

Bryan D Berthot
InSITE 2023  •  2023  •  pp. 015
Aim/Purpose.
This is a literature review that defines agile supply chain management (ASCM), discusses several competing theories (particularly ones with some empirical evidence), their research limitations (e.g., cultural and industry homogeneity), and future directions for research that would add to the field’s body of knowledge.

Background.
Agile supply chain management (ASCM) is a relatively recent phenomenon, with most academic articles published between 2001 and the present. However, the ASCM literature is quite fragmented, with no dominant theory. Both the ASCM literature and private industry would benefit from a heterogenous (i.e., multi-site, multi-industry) empirical study in the U.S. In this context, several forward-looking topics are considered as business “problems of practice”, including: 1) elaborating on existing agile supply chain rating instruments; and 2) generating empirical data from industry to support Zhu et al.’s (2022) EDGE supply chain framework. The challenges for supply chain managers are ones of assessing the agility of their firm’s supply chain and deciding on a theoretically based action plan for making targeted improvements.

Methodology.
The literature review was limited to refereed journals (i.e., does not include popular business journals, unpublished dissertations, etc.), yielding approximately 30 topic-relevant papers. The three-step review methodology (i.e., comprehensive material search, descriptive analysis and classification, theoretical and content analysis) attempts to replicate that of Shashi et al. (2020).

Contribution.
This paper defines ASCM and examines some of its key theoretical paradigms, including Christopher’s (2000) three-dimensional model for achieving agility, Lee’s (2004) Triple-A framework, and Lin et al.’s (2006) “route to agility” drivers-capabilities-goals model. It then discusses empirical support for the respective theories as well as some of their research limitations (e.g., cultural and industry homogeneity). Finally, it reviews some of the germane tools developed to assess the appropriateness of an agile approach in industry. This effort groups the literature into major theories with empirical support, identifies existing instruments to gauge an organization’s level of agile supply chain, and proposes several potential lines of research that would help the practitioner assess and improve the agility of the supply chain.

Findings.
In this context, several forward-looking topics are considered as business “problems of practice”, including: 1) elaborating on existing agile supply chain rating instruments; and 2) generating empirical data from industry to support Zhu et al.’s (2022) EDGE supply chain framework.

Recommendations for Practitioners.
The challenges for supply chain managers are ones of assessing the agility of the firm’s supply chain and deciding on a theoretically based action plan for making targeted improvements.

Recommendations for Researchers.
Here are some possibilities going forward:
• Replicate the Balaji et al. (2015) TADS study with a more culturally and industrially diverse sample. In terms of theory, the TADS instrument has a link to Lin et al.’s (2006) notion of the SC agility index. The original pilot study used a small Indian steel industry sample. For example, a sample of 10 to 25 U.S.-based Institute of Supply Management (ISM) member companies might be used. Another variation from the original study might be varying the intervention intended to improve the firm's SC agility.
• Operationalize the Hofman and Cecere (2005) proposed portfolio of agile SC metrics based on dimensions of speed, predictability, ease, and quality. In all likelihood, this would be a series of studies that would include development of scale items, questionnaire administration to an appropriate sample, and a factor analysis to evaluate item conceptual loadings. Here, the factor analysis ostensibly would be part of advancing the inherent theory. The next step would be an instrument reliability and validity study.
• Conduct a correlational study to examine further the relationship between the agile SC and customer satisfaction. Such a study has its roots in the previous work of Jawahar et al. (2020), Kisperska-Moron and Swierczek (2009), and Power et al. (2001).
• Advance Zhu et al.'s (2022) EDGE (i.e., enablers, suppliers, goals, and expertise) supply chain framework by doing a correlational study of firms whose agile SCs are blockchain and Internet of Things (IoT) capable. The authors themselves suggest this approach as no empirical data yet exists to support the EDGE model.
• Similarly, conduct an empirical study to provide support to the Bamakan et al. (2021) six-layer evaluation system of service supply chain performance that is based on a blockchain-IoT-big data framework.

Impact on Society.
Despite the diverse theoretical perspectives, there are tools available for sup-ply chain managers to assess their firm’s supply chain agility.

Future Research.
This author recommends taking the direction suggested by Zhu et al. (2022), one of examining firms whose supply chains are blockchain and IoT capable. This approach would provide some empirical support to the EDGE supply chain framework.
adaptability, agile supply chain management (ASCM), agility, alignment, leagile, lean, supply chain
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