Chinese Journal of Population, Resources and Environment (Dec 2021)
Spatial network structure of transportation carbon emission efficiency in China and its influencing factors
Abstract
Grasping the spatial correlation structure of transportation carbon emission efficiency (TCEE) and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region. Based on the ideal point cross-efficiency (IPCE) model, the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors. The results obtained showed the following outcomes. (1) During the study period, China’s provincial TCEE formed a complex and multithreaded network association relationship, but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west. (2) The correlation of China’s TCEE formed a block segmentation based on the regional boundaries, and its factional structure was relatively obvious. The eastern region was closely connected with the central region, and generally connected with the western and northeastern regions. The central region was mainly connected with the eastern and western regions, and relatively less connected with the northeastern region. Besides, the northeastern region was weakly connected with the western region. (3) Shanghai, Beijing, Zhejiang, Guangdong, Jiangsu, Tianjin, and other developed provinces were in the core leading position in the TCEE network, which significantly impacted the spatial correlation of TCEE. However, Heilongjiang, Jilin, Xinjiang, Qinghai, and other remote provinces in the northeast and northwest were at the absolute edge of the network, which weakly impacted the spatial correlation of TCEE. (4) Provincial distance, economic development-level difference, transportation intensity difference, and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE. In contrast, the energy-saving technology level difference had a significant positive impact on it. The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant; their response mechanism and effects need to be improved and enhanced.
