five

PSM method.

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Figshare2026-03-06 更新2026-04-28 收录
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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.

研究设计与方法 (Design/methodology/approach):本文采用2009—2022年中国A股上市公司数据,探究供应链稳定性对企业环境、社会和治理(ESG)绩效的影响。 研究目的 (Purpose):本研究旨在探讨供应链稳定性对企业ESG绩效的影响及其作用机制。 研究发现 (Findings):本研究发现,提升供应链稳定性可改善企业ESG绩效;该结论在经过工具变量法、系统广义矩估计法、倾向得分匹配法、遗漏变量检验以及双重机器学习(Double Machine Learning,DML)方法的稳健性检验后依然成立。进一步研究表明,供应链稳定性的提升可通过降低企业风险承担、降低代理成本以及缓解融资约束三条路径优化企业ESG绩效,且这一促进效应在大型企业、审计监管标准更高的企业、西部地区企业以及非技术密集型企业中更为显著。 实践启示 (Practical implications):本研究结论可为国家及地方政府积极推动供应链稳定发展以实现经济可持续发展提供现实参考框架。 社会启示 (Social implications):本研究深化了学界对企业可持续发展外部利益相关者的认知,同时为外部利益相关者积极发挥企业发展监督职能、参与企业公司治理,最终实现供应链稳定与环境可持续发展的双赢局面提供了理论契机。 研究创新与价值 (Originality/value):本研究从外部利益相关者视角切入,揭示了供应链稳定性与ESG绩效的关联,丰富了相关领域的文献研究。
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2026-03-06
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