Integrating Big Data and Artificial Intelligence Technology to Build Renewable Energy Supply Chain Resilience: An Empirical Study

作者：Surajit Bag, Muhammad Sabbir Rahman, Susmi Routray, David Roubaud, Sachin Kumar Mangla · 发表于：Business Strategy and the Environment · 年份：2025 · DOI：10.1002/bse.70052 · 被引用次数：13 · 研究领域：Supply Chain Resilience and Risk Management、Digital Transformation in Industry、Sustainable Supply Chain Management

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.