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Taking the Supply Chain Innovation and Application Demonstration Policy (SCIADP) implemented since 2021 as a quasi-natural experiment, this study constructs an analytical framework of “institutional external shock—supply chain operational efficiency—corporate ESG performance” based on Williamson’s transaction cost economics. Using panel data of Chinese A-share listed companies from 2013 to 2024, and employing a difference-in-differences (DID) approach combined with machine learning–based feature selection, the study systematically evaluates the policy’s overall effects, underlying mechanisms, and heterogeneous impacts.

本研究以2021年起实施的供应链创新与应用示范政策（Supply Chain Innovation and Application Demonstration Policy，SCIADP）作为准自然实验，基于威廉姆森的交易成本经济学，构建了"制度外部冲击—供应链运营效率—企业ESG表现"的分析框架。本研究选取2013年至2024年中国A股上市公司的面板数据，采用结合机器学习特征选择的双重差分法（DID），系统评估了该政策的整体实施效果、内在作用机制与异质性影响。