Artificial Intelligence and Supply Chain Resilience: Evidence from Chinese Listed Firms

Global supply chain disruptions have heightened interest in understanding how firms develop the capacity to withstand, respond to, and recover from external shocks. Drawing on the resource-based view and dynamic capabilities theory, this study examines the relationship between artificial intelligence (AI) application intensity and firm-level supply chain resilience using panel data from Chinese A-share listed firms over the period 2007–2024. Empirical results reveal a positive and statistically significant association between AI application intensity and supply chain resilience, which is further verified via multiple robustness checks, including propensity score matching and an instrumental variable approach. Further analyses examine R&D expenditure and corporate reputation as potential explanatory pathways and identify a negative moderating role of corporate transparency, consistent with an information-substitution explanation. Heterogeneity analyses indicate that the positive association is more pronounced among firms facing greater environmental uncertainty, operating in higher-trust business environments, and exhibiting stronger environmental, social, and governance (ESG) performance. These findings contribute to the understanding of AI-related organizational capabilities and supply chain resilience, highlighting the importance of integrating AI applications with complementary organizational resources and tailoring AI-related strategies to firms’ operating environments.