Jegan, J., Sonwaney, V., Bryde, D. et al. (1 more author) (2024) Achieving Competitive Advantage through Technology-driven Proactive Supply Chain Risk Management: An Empirical Study. Annals of Operations Research, 332. pp. 149-190. ISSN 0254-5330
Abstract
Whilst there has been previous work focused on the role of technologies in enhancing supply chain risk management and, through such an enhancement, increased competitive advantage, there is a research gap in terms of understanding the links between external institution pressures and internal adoption factors. We use institutional theory (IT) and the resource based view (RBV) of the firm to address this gap, developing a framework showing how a proactive technology-driven approach to supply chain risk management, combining both external with internal factors, can result in competitive advantage.We validate the framework through analysis of quantitative data collected via a survey of 218 firms in the manufacturing and logistics industry sectors in India.We specifically focus on the technologies of track-and-trace (T&T) and big data analytics (BDA). Our findings show that firms investing in T&T/BDA technologies can gain operational benefits in terms of uninterrupted information processing, reduced time disruptions and uninterrupted supply, which in turn gives them competitive advantage. We add further novelty to our study by demonstrating the moderating influences of organisational culture and flexibility on the relationship between the technological capabilities and the operational benefits.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2023. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Supply chain risk management; Resource-based view; Institutional theory; Track-and-trace; Big data analytics |
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: | 12 Sep 2023 10:32 |
Last Modified: | 19 Nov 2024 14:34 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s10479-023-05604-y |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:203210 |