Study on the Spatial Distribution of China's New Energy Vehicle Fleet and Its Influencing Factors

Xunnan Liu; Liping Du

doi:10.54691/2y885n06

Authors

Xunnan Liu North China University of Science and Technology, Tangshan, Hebei 050000, China
Liping Du North China University of Science and Technology, Tangshan, Hebei 050000, China

DOI:

https://doi.org/10.54691/2y885n06

Keywords:

New Energy Vehicle Fleet; Charging Infrastructure; Spatial Durbin Model; Spatial Spillover Effects.

Abstract

Against the backdrop of the "Dual Carbon" strategy, the new energy vehicle (NEV) industry has become a key driver of China's green and low-carbon transition and the upgrading of its automotive sector. This paper takes China's 31 provinces (autonomous regions and municipalities) in 2017, 2020, and 2023 as the units of analysis. By integrating data on NEV ownership and socioeconomic development, and employing spatial autocorrelation analysis and spatial econometric models, this study investigates the spatial agglomeration characteristics and influencing mechanisms of NEV ownership. The results show that:①the national NEV stock exhibits significant spatial agglomeration characteristics; the global Moran's I index shows an overall upward trend, indicating that the degree of spatial agglomeration is continuously increasing;②the NEV stock displays a distinct pattern of regional imbalance, with high-value areas primarily concentrated in the eastern coastal regions, while the central and western regions lag behind overall, though regional disparities are gradually narrowing;③Regional economic development levels, urbanization levels, permanent resident population size, and per capita disposable income of urban residents all have a significant impact on the number of new energy vehicles in circulation. Among these, the spatial spillover effects of regional economic development levels and resident income gradually strengthen as the industry develops, and the intensity of the various influencing factors varies to some extent across different stages;④As the new energy vehicle industry continues to mature, spatial interconnections among regions are strengthening, and the development of new energy vehicle markets is shifting from localized agglomeration to cross-regional collaborative expansion. Based on this, efforts should be made to strengthen regional coordinated development, refine differentiated support policies, optimize resource allocation, promote the coordinated development of the new energy vehicle industry, and advance the transition to a green and low-carbon economy.

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References

[1] Chen, Y., Guo, Y., Qin, W., et al. (2025). Evolution of spatial pattern and influencing factors of China's new energy vehicle industry. Economic Geography, 45(11), 129-138.

[2] Yan, L. J., & Liao, X. (2025). Analysis of factors influencing China's new energy vehicle sales from the perspective of spatial spillover effect. Pure Mathematics, 15(1), 21-30.

[3] Liu, Y. Q., Song, Z. Y., Gao, H. W., et al. (2023). Research on the 10-year promotion effect of new energy vehicles in China: A spatial effect perspective. Management Review, 35(3), 3-16.

[4] Huang, X. T., Wang, Q., Dang, N., et al. (2025). Spatial distribution and influencing factors of new energy vehicle enterprises from the industrial chain perspective. Journal of Fujian Normal University (Natural Science Edition), 41(5), 11-21.

[5] Xiong, P. P., Zhao, Y. L., Guan, J. X., et al. (n.d.). Application of multivariate gray model with nonlinear shock effect in sales forecasting of new energy vehicles. Chinese Journal of Management Science. Retrieved June 15, 2026.

[6] Xing, W. B., & Zhang, Y. T. (2026). Differences in consumption preferences and the efficiency of demand-side policies: Analysis based on the Chinese NEV market. Soft Science, 40(5), 1-10.

[7] Fang, Y. P., Peng, T., Zhang, Y. S., et al. (n.d.). Innovation spatial pattern evolution and determinants of new energy vehicle industry in the Pearl River Delta. Geographical Science. Retrieved June 20, 2026.

[8] Wang, X. N., Ma, L., Jin, F. J., et al. (n.d.). Spatial synergy and evolutionary pathways of production and innovation in Changzhou's new energy vehicle industry from spatial correlation perspective. Geographical Science. Retrieved June 20, 2026.

[9] Zou, H., Liu, W. H., Gao, Y. Z., et al. (n.d.). Research on the introduction of blockchain in the automotive supply chain under consumer mileage sensitivity. Systems Engineering-Theory & Practice. Retrieved June 20, 2026.

[10] Gong, K., Luo, R., & Chen, H. (2026). Assessing the fiscal impacts of industrial policies: Evidence from China's New Energy Vehicle Purchase Subsidies. Economic Perspectives, 4, 75-99.

[11] Nie, H. G., & Yu, H. R. (n.d.). Effectiveness of Local Government Subsidies for New Energy Vehicles under Policy Overlap. Contemporary Finance & Economics. Retrieved June 20, 2026.