Double Machine Learning.

Design/methodology/approachThis paper uses the data of Chinese A-share listed companies from 2009 to 2022 to study the impact of supply chain stability on corporate ESG performance.PurposeTo study the impact and mechanism of supply chain stability on corporate ESG performance.FindingsThis paper found that the improvement of supply chain stability can improve the ESG performance of firms, and this conclusion still holds after the instrumental variables method, systematic GMM method, PSM method, omitted variables test and Double Machine Learning (DML) approach, and the improvement of supply chain stability can optimise the ESG performance of firms through the channels of reducing the corporate risk-taking, reducing the agency costs, and reducing the financing constraints, and this facilitating effect is more significant in the large firms, firms with higher-standard audit supervision, firms located in western regions, and non-technology-intensive firms.Practical implicationsThe findings of this paper can provide a realistic framework for national and local governments to actively promote the stable development of supply chains in order to achieve sustainable economic development.Social implicationsThis paper deepens the understanding of the external stakeholders of enterprise sustainable development, and provides an opportunity to actively play the role of external stakeholders in monitoring the development of enterprises, participate in corporate governance of enterprises, and achieve a win-win situation of supply chain stability and environmental sustainability.Originality/valueThis study contributes to the literature by shedding light on the relationship between supply chain stability and ESG in the context of external stakeholders.