Evaluating China’s New Energy Vehicle Policy Networks: A Social Network Analysis of Policy Coordination and Market Impact

Abstract

Since 2015, China has witnessed a rapid increase in new energy vehicle (NEV) market penetration, achieving global leadership in this sector. This study employs social network analysis (SNA) and Granger causality tests to examine how policy coordination has influenced China’s NEV market development from 2015 to 2023. We evaluated policy coordination using six network metrics: network density, average path length, transitivity, average clustering coefficient, number of components, and size of largest component. Our findings reveal both correlative and causal relationships between policy coordination and market performance. The analysis demonstrated strong positive correlations between network metrics and market performance indicators (ρ = 0.800–0.850, p < 0.01), while Granger causality tests identified significant temporal effects, particularly in the long term (F = 284.051–281,486.748, p < 0.001). Notably, the largest component size shows immediate causal effects on market performance (F = 4.152, p < 0.05). Based on these results, we recommend establishing a multi-level policy coordination system, optimizing the policy network structure with emphasis on core components, implementing dynamic policy adjustment mechanisms considering time-lagged effects, and strengthening collaborative supervision of policy implementation to further advance China’s NEV market development.