The Multiplier Effect Between China’s Digitalization and Low-Carbon Policies: A PMC and Grey Correlation Analysis

The problems of policy structure and coordination must be solved during digital development and low-carbon transitions. Considering the limitations of traditional policy evaluation methods that only focus on one class of policies, we used text mining and ontology semantic methods to build a policy mining dictionary, complete the machine assignment of the Policy Modeling Consistency (PMC) index model, combine the PMC index model with grey association analysis, and explore an optimized policy collaborative evaluation method. We evaluated 34 digitalization policies and 43 low-carbon policies issued in China from 2006 to 2023. Our study explored the degrees of internal and external coordination of digitalization and low-carbon policies from the perspective of dynamic development. The overall design of China’s digitalization and low-carbon policies was found to be reasonable, and policy evaluation scores are increasing. In terms of internal coordination, there are some problems such as unitary policymaking institutions, unitary policy types, and insufficient policy perspectives. In terms of external synergies, there are significant differences in the synergies of policy evaluation, institutions, perspectives, and focuses. Our study suggests that policymakers should pay more attention to cross-sectorial cooperation and improve policy crosscutting in terms of attitudes, types, and timeliness. It has theoretical significance for optimizing the evaluation method based on combining policy text data mining and policy knowledge and improving the analysis of cross-type policy cooperation degrees. This has practical value for policy optimization of the high-quality development of the digital and low-carbon economy.