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.

To systematically reveal the policy efforts and evolutionary logic behind China's sustainable transition in the building sector, this study conducts a large-scale text analysis of 2,945 central and local policy documents from 2004 to 2024, integrating non-negative matrix factorization (NMF) topic modeling, policy instrument coding, and multi-level governance (MLG) comparison. The findings indicate that the policy agenda for green building in China has followed a clear trajectory from “foundation-laying” (macro-planning and standard-setting) to “implementation-deepening” (certification management and process supervision), closely linked with national sustainable development strategies. The policy mix is characterized by a “regulation-dominant” approach, with mandatory instruments at its core, supplemented by organizational and capacity-building tools. Incentive-based instruments are applied periodically, while informational and system-changing instruments remain relatively underutilized. In the multi-level governance structure, the central government focuses on strategic guidance, whereas local governments exhibit significant strategic adaptation based on regional heterogeneity. This study provides empirical evidence and theoretical insights into how China utilizes dynamic policy mixes and evolving governance to foster a sustainable transition in a specific sector, offering practical implications for optimizing future policy design to better cultivate endogenous market drivers.

Rural tourism is a key engine for sustainable development, elevated to a strategic level under China’s “Rural Revitalization Strategy”, creating a complex multi-level governance (MLG) policy system whose internal mechanisms are not fully understood. This study aims to analyze the thematic structure, spatio-temporal evolution, and transmission mechanisms of China’s rural tourism policy across central, provincial, and city/county levels. We applied BERTopic topic modeling and spatio-temporal analysis to a corpus of 1174 policy documents from 2005 to 2024. The results reveal a “centrally guided Type I governance” model with a clear functional division: the central level acts as a “top-level strategic designer”, the provincial level as a “key regional hub” for adaptation, and the city/county level as the “frontline of policy implementation”. We identified a vertical transmission chain characterized by a 1–2-year lag, alongside spatial differentiation driven by regional resource endowments at the provincial level and functional needs at the city/county level. This study concludes that China’s rural tourism governance framework is an efficient synergistic system that combines strong central guidance with dynamic local adaptation, providing empirical support for MLG theory in a unitary state and offering insights for optimizing policy coordination.