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Enhancing environmental, social, and governance performance through artificial intelligence supply chains in the energy industry: Roles of innovation, collaboration, and proactive sustainability strategy

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  • Wang, Shaofeng
  • Zhang, Hao

Abstract

With the global energy sector under mounting pressure to bolster sustainability, the function of artificial intelligence (AI) in augmenting Environmental, Social, and Governance (ESG) performance is receiving considerable attention. This study investigates the influence of Artificial Intelligence Adaptive Supply Chains (AIASC) on ESG performance within the energy industry, exploring the mediating roles of innovation and collaboration capabilities, alongside the moderating effect of proactive sustainability strategies. Drawing on Resource-Based View and System Dynamics Theory, we analyze data from 314 energy companies using partial least squares structural equation modeling (PLS-SEM). Our findings reveal that AIASC positively influences both innovation capability and collaboration capability, which in turn enhances ESG performance. Moreover, the proactive sustainability strategy strengthens the positive effects of AIASC on these capabilities. This research contributes to the growing body of literature on AI applications in sustainable energy management by elucidating the mechanisms through which AIASC can drive ESG improvements. Our study contributes to the understanding of AI applications in renewable energy supply chains and provides insights for practitioners on leveraging AIASC to improve sustainability performance in the renewable energy sector.

Suggested Citation

  • Wang, Shaofeng & Zhang, Hao, 2025. "Enhancing environmental, social, and governance performance through artificial intelligence supply chains in the energy industry: Roles of innovation, collaboration, and proactive sustainability strat," Renewable Energy, Elsevier, vol. 245(C).
    • Handle: RePEc:eee:renene:v:245:y:2025:i:c:s0960148125005178
    DOI: 10.1016/j.renene.2025.122855
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