A Study Of Spatial Differences In The Efficiency Of Regional Logistics Carbon Emissions And Their Influencing Factors

The implementation of the "Double Carbon" strategy fully reflects China’s responsibility and commitment as an international power,organically links national development and sustainable.The continuous change for the better in society has led to a continuous shift towards high-quality economic development.As an important category of green development in China,the logistics industry is the basis for accelerating the promotion of low-carbon logistics by objectively evaluating This indicator varies across different geographic locations in China for the logistics industry.The degree of performance of this indicator carbon emission efficiency is influenced by economic development,science and technology level,etc.By analyzing the relationship between the elements and efficiency,it can be used as a basis for the formulation of low carbon logistics development policies in China.In order to solve the problem of uneven development of the CO2 efficiency of regional logistics,this paper comprehensively examines dynamic and static differences and deeply analyses the factors affecting the CO2 efficiency of regional logistics to effectively improve the CO2 efficiency of regional logistics.The research idea of this paper is,firstly,to select indicators of regional logistics carbon emission efficiency and the role indicators are obtained from the existing published statistics in China.Secondly,a DEA-SBM model chosen to evaluate the level of energy efficiency of carbon release from logistics in different areas of the country during the decade 2011-2020.The Dagum Gini coefficient and Kernel Density Estimates were also selected to analyze the differences and dynamic distribution of the different regions of carbon emission efficiency between different locations in different regional areas from both static and dynamic perspectives.Finally,a spatial measurement model is chosen to study the spatial effects of different indicators on the efficiency of carbon emissions at the national and three regional levels and draw conclusions.By selecting different methods for in-depth analysis and discussion,the following results were concluded: First,the overall efficiency of carbon emissions in China is not very high in different zones.China’s regional logistics carbon emission efficiency level from 2011 to 2020 shows a distribution trend of East > National > Central and West.Among them,the logistics carbon emission efficiency in the central region was lower than that in the western region from 2011 to 2016,and after 2017,the logistics carbon emission efficiency in this indicator for several central provinces are similar to the national level and slightly higher than those for several western provinces.The second is the spatial differences in the different zones of the country logistics carbon emission efficiency levels vary.In terms of static differences,regional differences in logistics carbon emission efficiency show a trend of decreasing and then increasing,the differences between the central region are clear,and the differences between the east and west are also relatively large.The dynamic distribution state indicates that the logistics carbon emission efficiency has different distribution characteristics at different stages,showing a weak polarization distribution situation.Thirdly,there is a clear correlation between logistics carbon emission efficiency in space,and the trend of agglomeration among regions gradually changes to high-high agglomeration and low-low agglomeration.The fourth area is the spatial spillover results between the action indicators and the level of carbon emissions are reflected.There is a significant spatial spillover effect of influencing factors on carbon emission efficiency.The level of economic development and the level of transport facilities have a significant positive contribution to the carbon emission efficiency of regional logistics,while the four factors of urbanization rate,energy structure,environmental regulation and the level of science and technology all have a negative effect on it.