Artificial intelligence and green supply chain management in Chinese listed firms

Abstract As the core driving force of the new generation of industrial revolution, artificial intelligence technology has brought new opportunities for empowering enterprise green transformation and advancing sustainability. Focusing on Chinese A-share listed companies and based on unbalanced panel data from 2016 to 2024, this study systematically examines the impact, transmission mechanisms, and heterogeneity of AI applications on green supply chain management (GSCM). Drawing on the resource-based view and dynamic capabilities theory, this paper constructs an integrated theoretical framework that traces a causal link between AI applications through firm internal capabilities to green supply chain management. The empirical results show that AI applications significantly promote GSCM. Mechanism tests reveal that AI indirectly enhances GSCM by improving four dimensions of firm internal capabilities: green innovation, ESG performance, supply chain efficiency, and resource integration. In addition, heterogeneity analysis indicates that the enabling effect of AI on GSCM is more pronounced in state-owned enterprises, firms with higher environmental information disclosure quality, and firms in heavily polluting industries. This study deepens theoretical understanding of the relationship between AI and GSCM, reveals the micro-mechanisms and boundary conditions of AI-enabled GSCM, and provides practical insights for policymakers to guide firms in strategically applying AI and building efficient and collaborative green supply chains.