Chinese Geographical Science ›› 2020, Vol. 30 ›› Issue (3): 505-515.doi: 10.1007/s11769-020-1124-1

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Spatial Pattern Evolution and Influencing Factors of Cold Storage in China

LI Jinfeng1,2, XU Haicheng1, LIU Wanwan3, WANG Dongfang4, ZHOU Shuang3   

  1. 1. School of Economics and Management, Chang'an University, Xi'an 710064, China;
    2. School of Logistics and E-Commerce, Henan University of Animal Husbandry and Economy, Zhengzhou 450044, China;
    3. School of Management, Zhengzhou Institute of Technology, Zhengzhou 450044, China;
    4. School of Business, Wuyi University, Wuyishan 354300, China
  • Received:2019-06-05 Revised:2019-10-11 Online:2020-05-20 Published:2020-04-28
  • Contact: LI
  • Supported by:
    Under the auspices of the National Social Science Fund of China (No.15BGL185, 19XJL004), General Project of Humanities and Social Sciences Research and Planning Fund of Ministry of Education (No. 19YJA790097), Social Science Fund of Fujian Province (No. FJ2017C080), A Key Discipline of Henan University of Animal Husbandry and Economy ‘Business Enterprise Management’ (No. MXK2016201)

Abstract: Cold storage is the vital infrastructure of cold chain logistics. In this study, we analyzed the spatial pattern evolution characteristics, spatial autocorrelation and influencing factors of cold storage in China by using kernel density estimation (KDE), spatial autocorrelation analysis (SAA), and spatial error model (SEM). Results showed that:1) the spatial distribution of cold storage in China is unbalanced, and has evolved from ‘one core’ to ‘one core and many spots’, that is, ‘one core’ refers to the Bohai Rim region mainly including Beijing, Tianjin, Hebei, Shandong and Liaoning regions, and ‘many spots’ mainly include the high-density areas such as Shanghai, Fuzhou, Guangzhou, Zhengzhou, Hefei, Wuhan, Ürümqi. 2) The distribution of cold storage has significant global spatial autocorrelation and local spatial autocorrelation, and the ‘High-High’ cluster area is the most stable, mainly concentrated in the Bohai Rim; the ‘Low-Low’ cluster area is grouped in the southern China. 3) Economic development level, population density, traffic accessibility, temperature and land price, all affect the location choice of cold storage in varying degrees, while the impact of market demand on it is not explicit.

Key words: cold storage, spatial pattern evolution, kernel density estimation (KDE), spatial autocorrelation analysis (SAA), spatial error model (SEM), China