Spatial Network Evolution And Influencing Factors Analysis Of Green Total Factor Productivity Of Road Transportation

In the context of climate change and sustainable development,the rapid increase demand for energy in the transportation sector and the heavy reliance on petroleum products have attracted increasing social attention.As the transportation sector with the largest carbon emissions in transportation,road transportation has a major impact on the green economy and sustainable social development.Therefore,it is necessary to explore the contribution of the road transport sector to the green economy,in which "green total factor productivity",which measures the quality of green transportation development,is particularly critical.Focusing only on the development of green total factor productivity of road transportation in a province often overlooks the relationship between provinces on green technology,if that,the purpose of improving green total factor productivity from an overall perspective cannot be achieved.This paper has an important theoretical and practical significance for the transportation sector to formulate reasonable emission reduction policies from the perspective of individual and spatial association.The development of green technology in China is showing an increasingly complex state,especially in the road transportation industry.In order to further measure the development of interprovincial road transport quality in China,the paper analyzes all following two aspects.First,from province perspective,calculating the road transportation green total factor productivity,judging the development of green performance of road transportation.Second,from a regional perspective,the network correlation effect of green total factor productivity of road transport is studied,which will improve the green total factor productivity of the road transportation from spatial angle.Based on the related theories of social networks,total factor productivity,etc.,this paper studies the total factor productivity,network characteristics and influencing factors under the constraints of the road transportation environment in 30 provinces in China from 2002 to 2017.First,using the Hicks-Moorsteen TFP index to obtain the static and dynamic total factor productivity of road transport,the study found that: the research found that the sources of the decline in green total factor productivity of road transportation from static and dynamic perspectives are different.The decrease in static green total factor productivity results from the regression of technical efficiency,scale efficiency,and scope efficiency;the decrease in dynamic green total factor productivity originates from The retreat of technological progress,but both dynamic and static total factor productivity presents a trend of east> central> west.The technical level is still the source of the green total factor productivity of road transport.Secondly,the gravitational model is adopted,and the night light data is introduced to construct an inter-provincial green total factor productivity correlation model.attemptting to analyze the spatial network characteristics of green total factor productivity of road transport from from total,individual,spatial clustering,the study found that: the density of road transport networks is fluctuating and rising,there are significant differences in spatial correlation potential,and network aggregation presents a phenomenon of community.The eastern coastal area belongs to the "net income sector" or "bidirectional spillover" sector,and overall network shows that most provinces in the east are the "leaders" of the network,while the provinces in the west and southwest are the edge of the network.Finally,the QAP regression method is used to analyze the factors affecting the green total factor productivity network of road transport,and found that the factors such as regional distance,residents ’income level,and transportation cost,fuel price index,residents’ education level,highway network density,marketization index and other factors will all affect the degree of network connection of green total factor productivity of road transportation.