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Environmental credit rating (ECR) is a novel environmental governance tool proposed by China, but its implementation effect is still unknown. This study analyzed whether it achieves the goal of encouraging green innovation in enterprises. Based on the green patent data of listed companies in heavy polluting industries in China from 2010 to 2018, we constructed a heterogeneous timing difference-in-differences model to empirically study the impact of the ECR policy on green innovation. We find that the policy has significantly promoted heavy polluting enterprises’ green innovation. Moreover, the results passed a series of robustness tests. Importantly, we find that the policy has a positive effect on enterprises’ green innovation through the reputation mechanism and financing mechanism. Furthermore, the incentive effect of the policy varies with enterprise characteristics and regional characteristics: the green innovation effect of the policy is more obvious in large-sized and state-owned companies and companies in regions with low fiscal pressure and a high level of financial development are more likely to induce firms’ green innovation. Our research will be of practical value to China's environmental management, as well as global value to other countries.

Artificial intelligence techniques provide more possibilities for supply chain transformations in the face of global warming and environmental degradation. This study examines the Cournot game model of two competing supply chains with various carbon emission technologies as well as the possibility of upgrading machine learning technology. The investment risk of a supply chain's technology upgrade is either symmetric or asymmetric information. In the case of symmetric information, results show that the machine learning technology upgrade risk does not affect the market equilibrium outcomes of the duopoly model. However, in the case of asymmetric information, technology upgrade risk is vital in determining the quantities and prices of competition equilibrium. To achieve the goal of green supply chain transformation, the government should provide more technology and financial support to traditional supply chains to upgrade their machine learning technology on carbon emissions.