Big data and AI drive green innovation and supply chain resilience in renewable energy, enhanced by government effectiveness.
Authors
Surajit Bag, CERIIM, Excelia Business School, Paris, France
Muhammad Sabbir Rahman, North South University, Dhaka, Bangladesh
Susmi Routray, Institute of Management Technology, Ghaziabad, India
David Roubaud, MBS School of Business, Montpellier, France; Gulf Financial Center, Gulf University for Science and Technology, Hawally, Kuwait
Sachin Kumar Mangla, Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India; Plymouth Business School, University of Plymouth, Plymouth, United Kingdom
Summary
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.
Published in: Business Strategy and the Environment
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