Bag, Surajit, Rahman, Muhammad Sabbir, Routray, Susmi, Roubaud, David and Mangla, Sachin Kumar
(2025)
Integrating Big Data and Artificial Intelligence Technology to Build Renewable Energy Supply Chain Resilience : an empirical study.
Business Strategy and the Environment.
pp. 1-23.
ISSN 1099-0836
(In Press)
Abstract
This study examines how big data and AI technology integration influence green innovation and supply chain resilience in the renewable energy sector. The study also examines the mediating role of big data and AI-powered green innovation in enhancing resilience, as well as the moderating effect of government effectiveness. Based on the dynamic capability view, the hypotheses are formulated and further tested using primary data collected through surveys. By explaining the mechanisms through which resilience can be cultivated, the study contributes to the resilience literature and provides real world suggestions for managers seeking to prepare their organizations for unforeseen challenges. Therefore, this research not only contributes to the theoretical understanding of resilience but also provides actionable insights for industry practitioners. Organizations can leverage big data and AI technologies to drive innovation and develop better supply chain resilience strategies under varying levels of government effectiveness to effectively manage the complexity of renewable energy use, drive, and contribute to a green future. © 2025 ERP Environment and John Wiley & Sons Ltd.
Item Type: | Article |
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Keywords: | AI technology | big data | developing economies | energy sector | green innovation | renewable energy | resilience |
Subjects: | Social Sciences and humanities > Business, Management and Accounting > Accounting Social Sciences and humanities > Business, Management and Accounting > General Management |
JGU School/Centre: | Jindal Global Business School |
Depositing User: | Mr. Luckey Pathan |
Date Deposited: | 21 Jul 2025 09:22 |
Last Modified: | 21 Jul 2025 09:41 |
Official URL: | https://onlinelibrary.wiley.com/doi/10.1002/bse.70... |
URI: | https://pure.jgu.edu.in/id/eprint/9868 |
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