Against the backdrop of the deep reconfiguration of global supply chains, this study aims to select data from listed companies in China’s automobile manufacturing industry to empirically analyze the complex relationship between corporate ESG performance and supply chain network resilience. The primary objective is to identify novel pathways for enhancing supply chain network resilience of enterprises within turbulent environments.
This paper integrates social network analysis (SNA) to map the underlying architecture of supply chains, combined with sophisticated econometric modeling to test the research hypotheses. Crucially, the study uses node removal analysis to quantitatively assess the specific contributions of pivotal network actors to the overall resilience of the structure.
The empirical evidence reveals three key insights: (1) Aggregate ESG performance serves as a significant driver of supply chain resilience, albeit with a time-lag effect. (2) Corporate risk-taking capacity is identified as a key mediating channel through which ESG initiatives translate into heightened resilience. (3) The reduction of corporate cost of agency is identified as a key mediating channel through which ESG initiatives translate into heightened resilience.
Theoretically, this paper synthesizes signal transmission theory with stakeholder theory, extending the analysis of ESG economic consequences from the enterprise level to the entire supply chain network ecosystem, thereby enriching existing literature. Methodologically, it innovatively combines SNA with empirical methods, broadening the research on the structural position of individual firms within the ecosystem. Practically, the study provides quantitative evidence to guide enterprises in optimizing ESG resource allocation and offers empirical support for formulating industrial policies.
