An examination of the generative mechanisms of value in big data-enabled supply chain management research

被引:18
作者
Meriton, Royston [1 ]
Bhandal, Rajinder [3 ]
Graham, Gary [4 ]
Brown, Anthony [2 ]
机构
[1] Loughborough Univ London, Innovat & Entrepreneurship, London, England
[2] Loughborough Univ London, London, England
[3] Univ Leeds, Management, Ctr Decis Res, Business Sch, Leeds, W Yorkshire, England
[4] Univ Leeds, Leeds, W Yorkshire, England
关键词
Big data technologies; supply chain management; systematic literature review; value creation; dynamic capabilities; generative mechanisms; microfoundations; RESOURCE-BASED THEORY; DATA ANALYTICS; PREDICTIVE ANALYTICS; DYNAMIC CAPABILITIES; BUSINESS ANALYTICS; OPERATIONAL PERFORMANCE; COMPETITIVE ADVANTAGE; OPTIMIZATION MODEL; EMPIRICAL-RESEARCH; IMPACT;
D O I
10.1080/00207543.2020.1832273
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Big data technologies (BDT) are the latest instalments in a long line of technological disruptions credited with advancing the field of supply chain management (SCM) from a purely clerical function to a strategic necessity. Yet, despite the wave of optimism about the utility of BDT in SCM, the origins of value in a BDT-enabled supply chain are not well understood. This study examines the generative mechanisms of value creation in such a supply chain by a two-pronged approach. First, we interrogate the theoretical raisons d'etre of BDT in SCM. Second, we examine the evidence that support the value-added potential of BDT in SCM informed by extant empirical and quantitative studies (EQS). Taken together, our analyses reveal three key findings. First, in extending the dynamic capabilities perspective, we deduced that micro-founded rather than macro-founded studies tend to be more instructive to practice. Second, we discovered that the generative mechanisms of value in a BDT-enabled supply chain operate at the level of supply chain processes. And thirdly, we found that resilience and agility are the most important dynamic capabilities that have emerged from current BDT-enabled SCM research. Insights for policy, practice, theory, and future research are discussed.
引用
收藏
页码:7283 / 7310
页数:28
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