Abstract
The logistics industry plays a greater role in the sustainable development of regional economies. The development of the logistics industry between regions is not independent, and there is a spatial correlation due to the existence of spatial spillover effect or spatial expansion among regions. This paper uses the method of entropy weight to evaluate the development level of the logistics industry in 31 provinces in China. On this basis, Moran’s index (Moran’s I), Moran’s I scatter plot, and local indicators of spatial association (LISA) agglomeration plot are used to analyze the overall and local spatial agglomeration characteristics of the logistics industry. Four main factors affecting the spatial relationship of the logistics industry are analyzed by choosing the fixed effect of the spatial error model. We find that: (i) There is spatial agglomeration effect in the development level of the logistics industry from the overall perspective; (ii) regional differentiation of the spatial agglomeration effect of logistics industry development level is obvious from the local perspective; and (iii) the influence of human resource factors on the spatial relationship of logistics development level is declining.
Highlights
The logistics industry has increasingly shown its important role and strategic position in regional economic growth
Logistics infrastructure chooses the total mileage of railways, highways, and inland waterways as the length of transport routes, and the personnel choose the number of people employed in transportation, warehousing, and the postal industry as the human resources data to reflect
This study evaluates the development level of the logistics industry in 31 provinces of China by using the method of entropy weight
Summary
The logistics industry has increasingly shown its important role and strategic position in regional economic growth. Chen et al used the method of super-efficiency data envelopment analysis (SE-DEA) to measure the comprehensive technical efficiency and pure technical efficiency of the logistics industry in 31 provinces of China, decomposed the scale efficiency, and analyzed the difference of its efficiency value [16]. Zhang et al used the methods of nuclear density analysis and hot spot analysis to study the spatial distribution characteristics of logistics enterprises in Beijing-Tianjin-Hebei urban agglomeration in 1995, 2005, and 2015, and used the geographic weighted regression model (GWR) to analyze the influencing factors of the evolution of logistics enterprises [26]. Jing et al took Heilongjiang, Jilin, and Liaoning provinces as research objects, chose three-year city-level data, used ArcGIS and GeoDa spatial measurement software to analyze the spatial distribution and structure characteristics of logistics and regional economies, and explained the heterogeneity of logistics and economy in space [32].
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