Research on the Impact of Command-and-Control Environmental Regulations on Green Innovation of Agricultural-Related Enterprises

Abstract

With the intensification of global environmental challenges and the growing demand for sustainable agricultural transformation, understanding how environmental regulation shapes enterprise innovation has become increasingly important. This study examines the impact of command-and-control environmental regulation on green innovation in agricultural enterprises using panel data from agriculture-related enterprises listed on the Shanghai and Shenzhen A-share exchanges. The analysis focuses on the period 2012–2021, which is characterised by relatively stable environmental regulation and reliable data, providing a consistent empirical context for assessing the effects of command-and-control environmental regulation. By analyzing the characteristics of command-and-control environmental regulation and green innovation in agricultural enterprises, this research constructs and estimates a two-way fixed effects model, a moderating effects model, a mediating effects model, and a spatial Durbin model to explore both direct and spillover effects. The empirical results show that the following findings: (1) Command-and-control environmental regulation significantly promotes green innovation in agricultural enterprises, and this effect remains robust across alternative measurements and model specifications. (2) Heterogeneity analysis indicates that the direct effect of command-and-control environmental regulation is most pronounced in eastern regions, non-state-owned enterprises, and enterprises with weaker environmental, social, and governance performance. (3) Moderation analysis shows that agricultural industrial coordination and executive green cognition significantly strengthen the positive relationship between command-and-control environmental regulation and green innovation in agricultural enterprises. (4) Mediation analysis demonstrates that green management costs serve as a partial mediator in this relationship. (5) Spatial analysis reveals that spatial correlation patterns are evolving over time, with significant positive spillover effects observed among geographically and economically adjacent regions. The findings provide theoretical and empirical evidence to inform the design of coordinated environmental regulation frameworks that effectively stimulate green innovation and foster sustainable agricultural development.