地理研究 ›› 2019, Vol. 38 ›› Issue (5): 1236-1252.doi: 10.11821/dlyj020170859

• 研究论文 • 上一篇    下一篇

长三角制造业企业空间分布特征及其影响机制研究:尺度效应与动态演进

徐维祥(), 张筱娟(), 刘程军   

  1. 浙江工业大学经贸管理学院,杭州 310023
  • 收稿日期:2017-08-25 修回日期:2019-03-28 出版日期:2019-05-13 发布日期:2019-05-14
  • 作者简介:

    作者简介:徐维祥(1963-),男,浙江东阳人,教授,博士生导师,主要从事产业经济与空间计量研究。 E-mail:xwq02@163.com

  • 基金资助:
    国家自然科学基金项目(71774145、71276824)

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

摘要:

基于2005年、2013年长三角制造业企业微观数据,综合运用最近邻指数、Ripley’s K函数、空间热点聚类等分析方法,探究长三角制造业企业空间布局、集聚尺度及热点分布区域等空间点格局特征,并采用负二项回归模型对不同尺度下长三角制造业企业区位选择的影响机制进行了甄别,研究发现:长三角地区制造业企业空间分布不均衡,制造业企业总体和行业分样本均呈现出显著的空间集聚特性,空间集聚态势随地理距离的变化先增强后减弱,具有尺度效应。制造业企业的热点区域主要分布于由南京、苏州、无锡、常州、上海、杭州、绍兴及宁波为连接节点的 “Z”字型发展轴线上。长三角制造业郊区化现象较为普遍,绝大部分地市的制造业企业主要集聚在远郊。制造业企业区位选择影响机制存在尺度差异,产业结构和融资环境的作用在不同尺度下均具备稳健性,其中产业结构为影响制造业企业区位选择的主导因素,其作用强度远大于其他影响因子。区(县、市)样本中用工成本对制造业企业区位选择的影响显著提升。

关键词: 制造业企业, 区位选择, 尺度效应, 动态演进

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