Unleashing supply chain agility: Leveraging data network effects for digital transformation

Lin Wu, Jimmy Huang, Miao Wang and Ajay Kumar ()
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Lin Wu: Nottingham University Business School [Nottingham]
Jimmy Huang: Nottingham University Business School [Nottingham]
Miao Wang: University of Nottingham Ningbo [China]
Ajay Kumar: EM - EMLyon Business School

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Abstract: The global manufacturing supply chain is undergoing a digital transformation (DT) powered by various digital technologies. In both stable and turbulent environments, DT helps safeguard supply chain performance by enhancing supply chain agility. While research on the use of digital technologies and their impacts on supply chains is growing, there is a lack of an overarching theoretical lens to synthesize their diverse functionalities, effects, and benefits. To address this gap, we adapt the concept of the data network effect to the supply chain context and propose that DT improves supply chain performance by enhancing supply chain resilience (SCRes) and robustness (SCRob) capabilities. To validate our hypotheses, we conducted a large-scale survey for data collection and performed Partial Least Squares Structural Equation Modelling (PLS-SEM) for data analysis. The results confirm the positive effect of DT on supply chain performance and the mediating roles of SCRob and SCRes. Our study contributes to the ongoing discussion on DT in the context of supply chains by introducing a novel theoretical perspective on the supply chain data network effect.

Keywords: Data-driven digital transformation; Data network effect; Supply chain resilience; Supply chain robustness; Supply chain performance (search for similar items in EconPapers)
Date: 2024-11-01
New Economics Papers: this item is included in nep-int
Note: View the original document on HAL open archive server: https://hal.science/hal-04850421v1
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Published in International Journal of Production Economics, 2024, 277, 12 p. ⟨10.1016/j.ijpe.2024.109402⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04850421

DOI: 10.1016/j.ijpe.2024.109402

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