Cao Ting, Xie Na, Hanim Wasifah, Qin Yulu
School of Business, Zhengzhou University, 100 Kexue Road, 450001, Henan, China.
School of Finance and Public Administration, Guangxi University of Finance and Economics, 530007, Nanning, China.
J Environ Manage. 2025 Jun;385:125382. doi: 10.1016/j.jenvman.2025.125382. Epub 2025 May 5.
As a critical pathway to resolve the synergistic dilemma between industrial pollution abatement and sustainable agricultural development, the digital-green synergistic transformation exerts spillover effects on regional agricultural green total factor productivity through restructuring the factor endowment configurations of high-polluting enterprises. Employing a longitudinal dataset of Chinese A-share heavy-polluting firms spanning 2012-2022, this study systematically examines the impact of digital-green synergistic transitions within industrial sectors on agricultural green total factor productivity and their operational mechanisms. Empirical findings confirm that digital-green synergies significantly enhance agricultural green total factor productivity. Mechanism analyses reveal dual channels: First, from the green innovation perspective, this transformation elevates agricultural green total factor productivity by stimulating green management innovations among polluting enterprises. Second, regarding fiscal decentralization dynamics, appropriate decentralization positively moderates the agricultural green total factor productivity enhancing effect of digital-green transitions. Heterogeneity assessments indicate more pronounced agricultural green total factor productivity improvement in enterprises located in non-traditional industrial bases, coastal regions, and non-resource-dependent cities. Notably, a threshold effect exists for fiscal decentralization-when decentralization <0.4018, lagged digital-green transformation inhibits agricultural green total factor productivity, whereas decentralization ≥0.4018 converts this relationship into a promotional effect. These insights suggest policymakers should develop differentiated policy frameworks contingent upon fiscal decentralization elasticity. By optimizing cross-industry data reallocation incentives and institutional constraints, governments can effectively support agricultural green total factor productivity enhancement through multi-tier governance systems.
作为解决工业污染治理与农业可持续发展协同困境的关键路径，数字—绿色协同转型通过重塑高污染企业要素禀赋配置，对区域农业绿色全要素生产率产生溢出效应。本研究利用2012—2022年中国A股重污染企业的纵向数据集，系统考察了工业部门内数字—绿色协同转型对农业绿色全要素生产率的影响及其作用机制。实证结果证实，数字—绿色协同显著提高了农业绿色全要素生产率。机制分析揭示了双重渠道：第一，从绿色创新角度来看，这种转型通过刺激污染企业的绿色管理创新提高了农业绿色全要素生产率。第二，关于财政分权动态，适度分权正向调节数字—绿色转型对农业绿色全要素生产率的提升作用。异质性评估表明，位于非传统工业基地、沿海地区和非资源依赖型城市的企业，其农业绿色全要素生产率提升更为显著。值得注意的是，财政分权存在阈值效应——当分权<0.4018时，滞后的数字—绿色转型抑制农业绿色全要素生产率，而分权≥0.4018时，这种关系转变为促进效应。这些见解表明，政策制定者应根据财政分权弹性制定差异化政策框架。通过优化跨行业数据重新配置激励措施和制度约束，政府可以通过多层治理体系有效支持农业绿色全要素生产率的提高。
