Analysis of spatial associations in the energy–carbon emission efficiency of the transportation industry and its influencing factors: Evidence from China

Grasping the structure of the spatial associations in the energy–carbon emission efficiency (ECEE) of the transportation industry is of great importance for ensuring the green and sustainable development of the transportation industry. Based on the panel data on the transportation industry in 30 Chinese provinces from 2003 to 2017, this paper measures the provincial ECEE using the non-radial directional distance function (NDDF) and explores the structure of the spatial associations in ECEE and its influencing factors using social network analysis (SNA). The results show that (1) the average value of transportation ECEE in China is 0.34. The overall ECEE is relatively low and exhibits obvious spatial and temporal heterogeneity. (2) The network structure of the spatial associations for ECEE exhibit a hierarchical gradient characterized by density in the east and sparsity in the west, with provinces in the eastern and central regions, such as Henan, Zhejiang, and Fujian, possessing core leadership positions in the spatial transportation ECEE network. (3) The results of the block model show that the spatial ECEE network in the Chinese transportation industry has an obvious factional structure and that there are significant spatial associations among the blocks. Block 4, which contains several western provinces, exerts clear spatial spillover effects. (4) Regarding the factors affecting the formation of the spatial association network for ECEE, the differences in industrial structures, transportation energy structures, education levels, environmental regulations, and foreign direct investment among the provinces have positive and relatively significant effects on ECEE networks. The findings of this paper have theoretical and policy implications for integrating energy conservation and carbon emission reduction in China's transportation industry across regions.