Meriton, R, Bhandal, R, Graham, G orcid.org/0000-0002-9908-4974 et al. (1 more author) (2021) An examination of the generative mechanisms of value in big data-enabled supply chain management research. International Journal of Production Research, 59 (23). pp. 7283-7310. ISSN 0020-7543
Abstract
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’être 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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an author produced version of a journal article published in International Journal of Production Research. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Big data technologies, supply chain management, systematic literature review, value creation, dynamic capabilities, generative mechanisms, microfoundations |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Business (Leeds) > Management Division (LUBS) (Leeds) > Logistics, Info, Ops and Networks (LION) (LUBS) |
Depositing User: | Symplectic Publications |
Date Deposited: | 16 Sep 2020 12:32 |
Last Modified: | 05 Jul 2022 14:37 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | 10.1080/00207543.2020.1832273 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:165519 |