Author
Abstract
The adoption of Supply Chain 5.0 in any industry is crucial to the project's success and to minimize the risk of failure. This study explores the potential enablers that mitigate the daunting barriers (a) by prioritizing them and (b) by establishing their causal relationship in modern industries within developing economies. This study was validated using literature analysis and qualitative causal modeling. A semistructured questionnaire was used to interview 16 industry experts to standardize data collection. A twofold analysis was used. Firstly, grey influence analysis prioritized enablers, barriers, and their one‐to‐one influences. These influences were retested in the second fold, and stepwise linear regression confirmed the enablers–barriers causality. The results reveal that green energy is the most influential enabler, followed by universal storage and smart contracts. The most critical barriers include “Acceptance and Adaptability of Robots and Other Machines,” “Security and Privacy,” and “Lack of Green Initiatives.” The regression analysis highlights that “Acceptance and Adaptability of Robots and Other Machines” is the most critical barrier, needing multiple enablers. Universal storage, smart contracts, intelligent systems, and innovative technologies are key enablers for most Supply Chain 5.0 adoption barriers. The study aids in adopting Supply Chain 5.0 by prioritizing key enablers and barriers, guiding decision‐makers in developing economies to mitigate risks and enhance project success within the supply chain context. The study uniquely provides an enablers–barriers causality framework for Supply Chain 5.0, offering actionable insights for successful adoption in developing economies and enhancing academic and practical understanding.
Suggested Citation
Sachin Kumar & Vinay Singh, 2025.
"Decoding Supply Chain 5.0 Adoption by Grey Influence Analysis: What Barriers and Enablers Lie Within?,"
Business Strategy and the Environment, Wiley Blackwell, vol. 34(4), pages 4459-4484, May.
Handle:
RePEc:bla:bstrat:v:34:y:2025:i:4:p:4459-4484
DOI: 10.1002/bse.4209
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