Research On The Measurement And Improvement Path Of Low-Carbon Efficiency Of Logistics Industry In Provinces Along The "The Belt And Road"

The logistics industry is the pillar of China’s "Belt and Road" strategy of "interconnection",which helps break the restrictions of space and time distribution and provides material guarantee for the normal organization and implementation of the production process.However,the logistics industry along the "Belt and Road" has long been characterized by "high input,high consumption and high emission" as the main characteristics of the rough development mode,resulting in increasing energy consumption and carbon emissions,and the low-carbon development of the logistics industry is imperative.Therefore,in the context of the "30-60" target,how to accurately measure the low-carbon efficiency level of the logistics industry in the provinces along the "Belt and Road" and explore the improvement path is an urgent problem to be solved.The 17 provinces along the "Belt and Road" route are taken as the research objects of this paper,and proceeds according to the ideas of analysis of current situation,evaluation of efficiency,improvement path,and suggestions for countermeasures.The evaluation system of low-carbon efficiency of logistics industry in the provinces along the Belt and Road was constructed by combining the research of related scholars;the efficiency value of 17 provinces along the Belt and Road between 2013 and 2020 was measured by using the SBM model of non-expected output super-efficiency;the kernel density analysis,Arc GIS spatial analysis technique,variance analysis,and the analysis of the carbon emissions were used,Arc GIS spatial analysis,coefficient of variation and Gini coefficient are used to analyze the spatial and temporal variation characteristics of low-carbon efficiency of logistics industry in the provinces along the route;four macro-environmental factors,namely,political environment,economic environment,industrial environment and technological environment,are selected to explore the improvement path using fs QCA.Finally,based on the research findings,relevant policy recommendations are given,taking into account the realistic characteristics of each region.The main findings of the thesis are:(1)The energy consumption and carbon emissions of logistics industry in 17 provinces along the Belt and Road show an overall growth trend,and the dependence of logistics industry development on energy consumption and carbon emissions increases.(2)The decoupling value of economic growth and carbon emissions of logistics industry in the provinces along the Belt and Road is 0.323,showing a weak decoupling,which needs to be further improved.(3)The average low carbon efficiency value of logistics industry in the provinces along the Belt and Road is 0.726,indicating that the low carbon efficiency level of logistics industry is not high and there is still much room for improvement,and the polarization level of low carbon efficiency of logistics industry in some regions is high.(4)From the time dimension,the number of provinces in the low value area of logistics industry low carbon efficiency decreases and the number of provinces in the high value area increases as time goes by;the overall level of logistics industry low carbon efficiency decreases first and then increases,and the difference of logistics industry efficiency in 17 provinces shows the unbalanced characteristic of fluctuation and expansion.(5)From the spatial dimension,the development of each province is unbalanced,the status quo of regional division is serious,and no good linkage has been formed.(6)The analysis of Gini index and variation index found that the difference of low-carbon efficiency of logistics industry in provinces along the "Belt and Road" is large,and the regional difference has expanded in 2020.(7)Through the group study,four improvement paths are found.First,economic-driven path;second,economic and technological dual-driven path;third,economic and industrial dual-driven path;fourth,political,industrial and technological triple-driven path.