GEOGRAPHICAL RESEARCH ›› 2019, Vol. 38 ›› Issue (5): 1236-1252.doi: 10.11821/dlyj020170859

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Spatial distribution pattern and influencing factors of manufacturing enterprises in Yangtze River Delta: Scale effects and dynamic evolution

Weixiang XU(), Xiaojuan ZHANG(), Chengjun LIU   

  1. College of Economic and Management, Zhejiang University of Technology, Hangzhou 310023, China
  • Received:2017-08-25 Revised:2019-03-28 Online:2019-05-13 Published:2019-05-14

Abstract:

With the assistance of micro data of manufacturing enterprises in the Yangtze River Delta in 2005 and 2013, this article combined the methods of the nearest neighbor index, Ripley’s K function and space hot clustering analysis to explore the spatial point pattern characteristics of manufacturing enterprises in this region, i.e., space distribution, agglomeration scale and hot spot areas. And then we used the negative binomial regression model to identify the influencing factors of location choice for manufacturing enterprises in the Yangtze River Delta in different spatial scales. The results are obtained as follows. Firstly, the spatial distribution of manufacturing enterprises in the study area is extremely uneven, and manufacturing enterprises overall are significantly space clustering, which applies to the labor-intensive manufacturing enterprises, capital intensive manufacturing enterprises, technology-intensive manufacturing enterprises and resource-intensive manufacturing enterprises. Besides, space agglomeration of manufacturing enterprises has scale effects, the degree of space agglomeration first enhanced and then weakened with the change of geographical distance. Hot spot areas of manufacturing enterprises are mainly distributed on the development axis shaped as a “Z”, which is connected by the nodes of Nanjing, Suzhou, Wuxi, Changzhou, Shanghai, Hangzhou, Shaoxing and Ningbo. In addition, the suburbanization trend of manufacturing enterprises in Yangtze River Delta is fairly common, and for most cities, the manufacturing enterprises mainly cluster in the outer suburbs. Lastly, it is indicated that the effects of influencing factors on the location choice for manufacturing enterprises vary in different spatial scales, among all the influencing factors, the effect of industrial structure and financial environment is positive and stable in both city samples and county samples, while the industrial structure is dominant among the factors influencing the location choice for manufacturing enterprises, which has greater effects than other factors. For the county samples, the effect of wage on the location choice for manufacturing enterprises is obviously enhanced.

Key words: manufacturing enterprises, location choice, scale effects, dynamic evolution