地理科学 ›› 2021, Vol. 41 ›› Issue (7): 1199-1209.doi: 10.13249/j.cnki.sgs.2021.07.010

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东北三省企业空间格局演化与区位选择因素

宋飏1,2(), 王婷婷1, 张瑜1, 钱思彤1, 王士君1,2,*()   

  1. 1.东北师范大学地理科学学院,吉林 长春 130024
    2.长白山地理过程与生态安全教育部重点实验室,吉林 长春 130024
  • 收稿日期:2020-09-16 修回日期:2020-12-29 出版日期:2021-07-31 发布日期:2021-09-06
  • 通讯作者: 王士君 E-mail:song0317@nenu.edu.cn;wangsj@nenu.edu.cn
  • 作者简介:宋飏(1978-),女,满族,吉林长春人,博士,高级工程师,主要研究方向为城市地理与城乡规划、环境健康地理。E-mail: song0317@nenu.edu.cn
  • 基金资助:
    国家自然科学基金项目(41630749);国家社会科学基金项目(17BJL051);中央高校基本科研业务费专项资金项目(1709103);中央高校基本科研业务费专项资金项目(2412020FZ001)

Spatial Pattern Evolution and Impact Factors of Location Choice of Enterprises in Northeast China

Song Yang1,2(), Wang Tingting1, Zhang Yu1, Qian Sitong1, Wang Shijun1,2,*()   

  1. 1. School of Geographical Science, Northeast Normal University, Changchun 130024, Jilin, China
    2. Key Laboratory of Geographical Processes and Ecological Security in Changbai Mountains, Ministry of Education, Changchun 130024, Jilin, China
  • Received:2020-09-16 Revised:2020-12-29 Online:2021-07-31 Published:2021-09-06
  • Contact: Wang Shijun E-mail:song0317@nenu.edu.cn;wangsj@nenu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(41630749);National Social Science Fundation of China(17BJL051);Fundamental Research Funds for the Central Universites(1709103);Fundamental Research Funds for the Central Universites(2412020FZ001)

摘要:

企业作为产业空间的核心载体和组织主体,其区位特征和影响因素识别对优化区域产业空间布局、合理配置资源具有重要意义。以东北三省115 852条有效规模以上企业数据为研究对象,采用空间分析方法总结2000年、2010年和2019年东北三省企业空间格局特征,并运用OLS模型和GWR模型解析影响企业区位选择的核心因素。结果表明:① 东北三省企业以“T”字形铁路沿线为轴线逐渐向两端扩展;② 沈阳市区始终保持东北三省企业资本规模领先地位,哈尔滨、长春、大连市区资本规模增长迅速,并与沈阳市区之间的差距逐渐缩小;③ 东北三省企业空间分布可以分为单核心热点型、中心城市集聚型和“大集聚-小分散”型3种类型;④ 市场规模、城市等级是影响东北三省企业空间分异格局的两大核心因素,外商投资水平次之;⑤ 不同区位影响企业空间布局的核心因素存在一定空间差异。

关键词: 企业, 普通最小二乘法(OLS), 地理加权回归(GWR), 区位选择因素, 东北三省

Abstract:

As the core carrier and main body of the industrial space, enterprises play an important role in the regional economy. Accordingly, enterprise investment and location selection will become an important engine for the overall revitalization of Northeast China. This paper analyzes the characteristics of the spatial pattern of enterprises in Northeast China in 2000-2019. For this purpose, a large dataset with 115 852 data information about the above-scale enterprises was used in the analysis of core factors of the location of the enterprises. Multiple spatial data analysis techniques, such as kernel density estimation, nuclear density estimation, nearest neighbor analysis, and geographic weighted regression models were used for location analysis. The results showed that: 1) Enterprises in Northeast China have gradually expanded to both ends with the ‘T’-shaped railway as the axis; 2) Shenyang urban district maintained a leading position for the capital scale of enterprises in Northeast China. The capital scales of Harbin, Changchun, and Dalian have grown rapidly and the gap with Shenyang urban district gradually narrowed; 3) The spatial distribution pattern of enterprises in 26 key industries in Northeast China can be divided into three types: single-core type, central city cluster type and ‘large agglomeration-small dispersion’ type; 4) Six factors are recognized to have a significant impact on the location of enterprises in Northeast China: market size, urban hierarchy, foreign direct investment, economic development, labor cost and transportation accessibility. Among them, market size and urban hierarchy are the two core factors influencing the spatial differentiation pattern of enterprises in Northeast China, followed by FDI. The spatial heterogeneity of these three factors is relatively strong, while the spatial heterogeneity of transportation accessibility, economic development and labor cost is relatively weak; 5) Market size, urban hierarchy and FDI showed obvious differences in the impacts of the location of enterprises in different types of regions.

Key words: enterprises, Ordinary Least Squares, Geographically Weighted Regression, location selection factors, Northeast China

中图分类号: 

  • K9