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How generative AI adoption affects supply chain resilience: An operations and supply chain management perspective

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  • Guo, Jiguang
  • Jia, Fu
  • Chen, Lujie

Abstract

Generative AI drives profound societal transformations, and there is an urgent need to explore its potential in enhancing business resilience and sustainability. However, its influence on supply chain resilience remains empirically underexplored. Drawing on the operations and supply chain management (OSCM) perspective, this research aims to examine how generative AI improves or impedes supply chain resilience, while exploring the moderating effects of operational capability and supply chain concentration. Using panel data from Chinese A-share listed companies from 2017 to 2022, we employ fixed-effects models and a series of robustness checks to test the predictions. We discover that firms' generative AI enhances their supply chain resilience, and this effect is more pronounced among high-tech companies. Drawing on dynamic capability theory, this research sheds new light on the positive effect of operational capability (i.e., operational efficiency and operational slack), and the negative effect of supply chain concentration (i.e., customer concentration and supplier concentration) in shaping the impact of generative AI adoption on supply chain resilience. This study provides novel empirical evidence for the association between generative AI adoption and supply chain resilience and identifies key OSCM-related contingency factors in this relationship.

Suggested Citation

  • Guo, Jiguang & Jia, Fu & Chen, Lujie, 2026. "How generative AI adoption affects supply chain resilience: An operations and supply chain management perspective," Technological Forecasting and Social Change, Elsevier, vol. 224(C).
    • Handle: RePEc:eee:tefoso:v:224:y:2026:i:c:s0040162525004779
    DOI: 10.1016/j.techfore.2025.124446
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