Research on the Enterprise Credit Risk Mitigation Effect of Digital Transformation Empowerment in Agricultural Supply Chain Finance

农业企业因信息不对称、信用风险高和金融服务效率低等问题长期面临融资约束，数字技术的广泛应用和农业供应链金融的发展成为解决这些问题的关键途径。本研究以2007~2022年中国农业上市公司为样本，运用动态面板系统GMM模型，探讨数字化转型对农业企业信用风险的缓释效应及农业供应链金融的中介作用机制。研究发现：1) 数字化转型显著降低农业企业信用风险，主要通过提升信息透明度、缓解融资约束和优化风险控制实现。2) 农业供应链金融在“数字化转型–信用风险”传导路径中发挥部分中介效应，数字化通过提升供应链金融水平间接降低风险。3) 异质性分析揭示国有企业因政策支持与技术转化优势，其数字化降险效果显著优于非国有企业。本研究为农业企业优化数字化转型路径、金融机构创新风控模型及政府部门制定差异化扶持政策提供了理论依据与实践启示。Agricultural enterprises have long faced financing constraints due to information asymmetry, high credit risk and low efficiency of financial services, and the wide application of digital technology and the development of agricultural supply chain finance have become the key ways to solve these problems. Taking China’s listed agricultural companies from 2007 to 2022 as a sample, this study uses the GMM model of dynamic panel system to explore the mitigation effect of digital transformation on the credit risk of agricultural enterprises and the intermediary mechanism of agricultural supply chain finance. The results show that: 1) Digital transformation significantly reduces the credit risk of agricultural enterprises, mainly by improving information transparency, alleviating financing constraints and optimizing risk control. 2) Agricultural supply chain finance plays a part of the intermediary effect in the transmission path of “digital transformation-credit risk”, and digitalization indirectly reduces risks by improving the level of supply chain finance. 3) Heterogeneity analysis reveals that state-owned enterprises have significantly better digital risk reduction effects than non-state-owned enterprises due to their advantages in policy support and technology transformation. This study provides a theoretical basis and practical enlightenment for agricultural enterprises to optimize the digital transformation path, financial institutions to innovate risk control models, and government departments to formulate differentiated support policies.