Deep learning-based evaluation of China’s new energy vehicle policies: A synergy perspective through policy documents

Policy synergy plays a vital role in ensuring the cohesive implementation of national strategies. This study examines the policy synergy of China’s new energy vehicle (NEV) sector by analyzing 2047 policy documents issued between 2007 and 2024. More specifically, this study utilizes a BERTopic-based analytical framework to classify NEV policy tools into five categories and assess their synergy from three dimensions: Horizontal (interdepartmental synergy), vertical (central-local synergy), and temporal (evolution over time). The results indicate that the Ministry of Finance, the Ministry of Science and Technology, and the Ministry of Transport exhibit higher horizontal synergy than other central government departments. Vertical synergy is more pronounced in the eastern region, primarily due to economic development, industrial structure, and resource endowment disparities. Temporal synergy follows a “low-high-low” pattern across different development stages. Hence, policymakers should consider departmental functions, regional characteristics, and temporal trends to enhance policy synergy and effectiveness.