ORIGINAL RESEARCH article
Front. Clim.
Sec. Climate and Economics
Volume 7 - 2025 | doi: 10.3389/fclim.2025.1624297
This article is part of the Research TopicData-Driven Urban Dynamics: Sustainable Urbanization and Mobility in Peripheral AreasView all 6 articles
Spatiotemporal Dynamics and Driving Mechanisms of Total Factor Carbon Productivity in China's Provincial Transportation Sector
Provisionally accepted
- 1School of Transportation, Shandong University of Science and Technology, Qingdao, China
- 2International Cooperation Center of National Development and Reform Commission, Beijing, China
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Based on panel data from 30 Chinese provinces spanning 2007-2022, this study comprehensively employs the Super-Efficiency Slack-Based Measure (SBM) model, nonparametric kernel density estimation, standard deviational ellipse, and global Moran's I index to analyze the spatiotemporal evolution characteristics of Total Factor Carbon Productivity in Transportation (TFCP-T) across provinces. Finally, a spatial Durbin model is utilized to empirically investigate influencing factors. Key findings include:(1) China's provincial TFCP-T exhibits an overall fluctuating upward trend, yet reveals a distinct spatiotemporal differentiation pattern characterized by "high efficiency and intensification in the eastern region versus gradient lag in the central and western regions."(2) Significant spatial positive correlation and club convergence effects exist in China's transportation green total factor productivity, with western provinces facing risks of low-level lock-in.(3) Economic development level, openness to foreign trade, environmental protection intensity, and industrial structure upgrading positively promote TFCP-T, while consumption level and informatization level exert significant inhibitory effects.These results provide critical policy insights for enhancing transportation carbon productivity and fostering regional coordinated development in China.
Keywords: Total Factor Carbon Productivity in Transportation (TFCP-T), Standard deviational ellipse (SDE), moran's I, Spatial Durbin, Kernel Density Estimation
Received: 07 May 2025; Accepted: 24 Jun 2025.
Copyright: © 2025 Sun, Liu and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yanming Sun, School of Transportation, Shandong University of Science and Technology, Qingdao, China
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