The Impact of Artificial Intelligence and Group Effects on Supply Chain Resilience in Enterprises

As a key pathway for technological diffusion, examining the role of artificial intelligence peer effects in enhancing corporate supply chain resilience represents a crucial focus for the manufacturing sector in addressing supply chain risks and achieving high-quality development. Utilising panel data from Chinese A-share listed manufacturing enterprises between 2018 and 2024, this study employs a multi-period difference-in-differences model and spatial econometric models to empirically test the impact of artificial intelligence peer effects on corporate supply chain resilience. Findings reveal that the AI peer effect significantly enhances corporate supply chain resilience. This conclusion remains robust after undergoing multiple stability tests—including instrumental variables, placebo tests, and PSM-DID—alongside endogeneity checks. Mechanism analysis indicates that technological absorption capacity partially mediates the relationship between the AI peer effect and supply chain resilience, while supply chain network complexity exerts a positive moderating effect. Extension analyses reveal that the impact of the AI peer effect exhibits heterogeneity across large versus small and medium-sized enterprises (SMEs) and across high versus low technology-intensive industries. Spatial spillover tests indicate that the AI peer effect exerts spatial spillover effects on corporate supply chain resilience. These findings provide novel empirical evidence and policy implications for re-examining the relationship between the AI peer effect and corporate supply chain resilience.