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Harnessing Generative AI Decision Support for Environmental and Social Supply Chain Sustainability

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  • Rizwan Matloob Ellahi
  • Ke Wang
  • Jawaid Ahmed Qureshi
  • Lincoln C. Wood

Abstract

This study examines the mediating role of Generative AI–based decision support systems in promoting environmental and social sustainability within supply chains. Grounded in resource‐based and stakeholder theories, the research highlights management commitment and technological readiness as critical internal drivers shaping sustainability outcomes. A structural model was developed and validated using survey data collected from supply chain professionals in the logistics sector. Findings reveal that both management commitment and technological readiness significantly influence supply chain sustainability, while AI‐driven decision support systems partially mediate these relationships. The results suggest that integrating Generative AI into decision‐making processes enhances firms' ability to achieve sustainability objectives. By linking internal drivers with advanced technologies, this study contributes to understanding how organizations can leverage emerging tools to meet green supply chain goals. The findings also provide practical implications for managers seeking to strengthen sustainability initiatives through technology adoption and improved decision‐making.

Suggested Citation

  • Rizwan Matloob Ellahi & Ke Wang & Jawaid Ahmed Qureshi & Lincoln C. Wood, 2026. "Harnessing Generative AI Decision Support for Environmental and Social Supply Chain Sustainability," Sustainable Development, John Wiley & Sons, Ltd., vol. 34(3), pages 3641-3653, June.
    • Handle: RePEc:wly:sustdv:v:34:y:2026:i:3:p:3641-3653
    DOI: 10.1002/sd.70511
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