大数据
弹性(材料科学)
可再生能源
供应链
环境经济学
业务
能量(信号处理)
经济
计算机科学
营销
工程类
数据挖掘
物理
电气工程
统计
热力学
数学
作者
Surajit Bag,Muhammad Sabbir Rahman,Susmi Routray,David Roubaud,Sachin Kumar Mangla
摘要
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.
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