摘要
The logistics clusters are the result of concentration, scale and specialization of logistics activities, and their quantitative measurement and development evaluation provide an important foundation for improving the land use efficiency and achieving economies of scale. Taking 289 cities at prefecture-level and above as research objects, this paper collected macro-statistical data of transport, postal and warehousing industry during 2000–2014, business registration data of more than 290 thousand logistics enterprises, and 170 thousand logistics points of interest（POI）. With the integration of multi-index and multi-source data, the evolution process and spatial pattern of logistics clusters in China were explored with the methods of Location Quotient（LQ）, Horizontal Cluster Location Quotient（HCLQ）, Logistics Employment Density（LED） and modified Logistics Establishments＇ Participation（LEP）. The development levels, types and modes of different logistics clusters were quantified. Several important findings are derived from the study.（1） The logistics clusters are mainly located on the east side of the Hu Huanyong Line, and the accumulative pattern evolves from group to block structure, featuring wide coverage and high concentration. The evolution of logistics clusters has two stages of rapid convergence and stable change, resulting in gradual increase in the development level and efficiency of logistics clusters and in emergence of spillover effect.（2） 21 mature logistics clusters are distributed in the core and sub-cities of the main metropolitan areas of 16 provincial-level administrative divisions, conforming to the government logistics and transport planning. 43 emerging logistics clusters are distributed in 21 provincial administrative divisions, and different types of cities have huge disparities which highlight the differentiation of the market behaviors and government planning among them.（3） The logistics clusters present differentiated development modes with the change of
The logistics clusters are the result of concentration, scale and specialization of logistics activities, and their quantitative measurement and development evaluation provide an important foundation for improving the land use efficiency and achieving economies of scale. Taking 289 cities at prefecture-level and above as research objects, this paper collected macro-statistical data of transport, postal and warehousing industry during 2000–2014, business registration data of more than 290 thousand logistics enterprises, and 170 thousand logistics points of interest（POI）. With the integration of multi-index and multi-source data, the evolution process and spatial pattern of logistics clusters in China were explored with the methods of Location Quotient（LQ）, Horizontal Cluster Location Quotient（HCLQ）, Logistics Employment Density（LED） and modified Logistics Establishments＇ Participation（LEP）. The development levels, types and modes of different logistics clusters were quantified. Several important findings are derived from the study.（1） The logistics clusters are mainly located on the east side of the Hu Huanyong Line, and the accumulative pattern evolves from group to block structure, featuring wide coverage and high concentration. The evolution of logistics clusters has two stages of rapid convergence and stable change, resulting in gradual increase in the development level and efficiency of logistics clusters and in emergence of spillover effect.（2） 21 mature logistics clusters are distributed in the core and sub-cities of the main metropolitan areas of 16 provincial-level administrative divisions, conforming to the government logistics and transport planning. 43 emerging logistics clusters are distributed in 21 provincial administrative divisions, and different types of cities have huge disparities which highlight the differentiation of the market behaviors and government planning among them.（3） The logistics clusters present differentiated development modes with the change of
基金
National Natural Science Foundation of China,No.71603219,No.41501123
