中国交通碳排放效率的空间关联网络结构及其影响因素

Spatial network structure of transportation carbon emissions efficiency in China and its influencing factors

准确把握交通碳排放效率空间关联结构及其影响因素对促进交通运输业乃至区域高质量协调发展具有重要意义。在利用基于理想决策单元参照的交叉效率模型对中国省域交通碳排放效率进行科学测度的基础上,运用社会网络分析法探究中国省域交通碳排放效率的空间关联网络结构及其影响因素。研究表明:①研究期间中国省域交通碳排放效率已形成较为复杂的、多线程的网络关联关系,但其网络关联结构仍较疏松,且呈现出“东密西疏”的等级梯度特征。②中国交通碳排放效率关联关系在空间上形成了以区域为边界的“条块分割”,派系结构较为明显。其中,东部地区与中部地区联系较为紧密,与西部和东北地区联系一般;中部地区则主要表现出与东部和西部地区较强的连接状态,与东北地区的联系相对较少;而东北地区与西部地区的联系较弱。③上海、北京、浙江、广东、江苏、天津等发达省份在交通碳排放效率关联网络中处于核心主导地位,对交通碳排放效率空间关联性的影响显著;而黑龙江、吉林、新疆、青海等东北和西北偏远省份在网络中则处于绝对边缘位置,对交通碳排放效率空间关联性的影响较弱。④省区距离、经济发展水平差异、交通运输强度差异和交通运输结构差异对中国省域交通碳排放效率空间关联网络产生显著负向影响;节能技术水平差异则对其产生显著正向影响,而交通能源结构差异和环境规制差异的回归系数为正但不显著,其响应机制和响应效果仍有待完善和增强。

Grasping the spatial correlation structure of transportation carbon emissions efficiency and its influencing factors is of great significance for the promotion of high-quality and coordinated development of the transportation industry and even that of relevant region.Based on the ideal point cross efficiency(IPCE)model,this paper used the social network analysis method to explore the spatial correlation network structure of China’s provincial transportation carbon emissions efficiency and its influencing factors.The results showed that:①During the study period,China’s provincial transportation carbon emissions efficiency formed a complex and multi-threaded network association relationship,but its network association structure was still relatively loose,and presented the hierarchical gradient characteristics of‘dense in the East while sparse in the West’.②The correlation of China’s transportation carbon emissions efficiency formed a‘block segmentation’based on the regional boundaries,and its factional structure was relatively obvious.Among them,the eastern region was closely connected with the central region,and generally connected with the western region and the northeastern region;the central region was mainly connected with the eastern region and the western region,and relatively less connected with the northeastern region;while the northeastern region was weakly connected with the western region.③Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin and other developed provinces were in the core leading position in the transportation carbon emissions efficiency network,which had a significant impact on the spatial correlation of transportation carbon emissions efficiency.However,Heilongjiang,Jilin,Xinjiang,Qinghai and other remote provinces in the northeast and northwest were in the absolute edge of the network,which had a weak impact on the spatial correlation of transportation carbon emissions efficiency.④Provincial distance,economic development level difference,transportation intensity difference and transportation structure difference had significant negative impact on the spatial correlation network of China’s provincial transportation carbon emissions efficiency,and energy saving technology level difference had significant positive impact on it,while the regression coefficients of transportation energy structure difference and environmental regulation difference were positive but not significant;their response mechanism and effects need to be improved and enhanced.