东北三省企业空间格局演化与区位选择因素

doi:10.13249/j.cnki.sgs.2021.07.010

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

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.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. 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/Abstract

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:

宋飏, 王婷婷, 张瑜, 钱思彤, 王士君. 东北三省企业空间格局演化与区位选择因素[J]. 地理科学, 2021, 41(7): 1199-1209.

Song Yang, Wang Tingting, Zhang Yu, Qian Sitong, Wang Shijun. Spatial Pattern Evolution and Impact Factors of Location Choice of Enterprises in Northeast China[J]. SCIENTIA GEOGRAPHICA SINICA, 2021, 41(7): 1199-1209.

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产业类型	数量/个	产业类型	数量/个
汽车制造业	1355	批发业	14428
农副食品加工业	3501	零售业	8351
医药制造业	948	住宿业	612
化学原料和化学制品制造业	2320	餐饮业	829
石油加工、炼焦和核燃料加工业	422	道路运输业	4611
铁路、船舶、航空航天和其他运输设备制造业	540	仓储业	822
计算机、通信和其他电子设备制造业	430	装卸搬运和运输代理业	1005
食品制造业	981	软件和信息技术服务业	9404
非金属矿物制品业	4960	货币金融服务	2679
黑色金属冶炼和压延加工业	589	房地产业	14129
电气机械和器材制造业	2039	商务服务业	14444
通用设备制造业	4425	研究和试验发展	10748
纺织业	368	科技推广和应用服务业	10912

产业类型	平均观测距离/km	预期平均距离/km	最近邻指数	Z检验值
汽车制造业	2.344	12.252	0.191	-56.014
农副食品加工业	3.259	7.637	0.426	-63.703
医药制造业	3.842	14.579	0.263	-42.871
化学原料和化学制品制造业	3.802	9.432	0.403	-53.704
石油加工、炼焦和核燃料加工业	8.143	22.099	0.368	-24.252
铁路、船舶、航空航天和其他运输设备制造业	6.030	20.356	0.296	-29.342
计算机、通信和其他电子设备制造业	5.286	22.522	0.234	-28.837
食品制造业	6.181	14.401	0.429	-33.638
非金属矿物制品业	1.994	6.374	0.312	-91.477
黑色金属冶炼和压延加工业	6.624	18.533	0.357	-29.425
电气机械和器材制造业	2.339	10.057	0.232	-64.758
通用设备制造业	1.397	6.792	0.205	-99.252
纺织业	8.209	23.680	0.346	-23.415
批发业	0.920	3.796	0.242	-169.364
零售业	1.104	4.918	0.224	-133.810
住宿业	7.247	18.714	0.387	-27.789
餐饮业	6.337	16.071	0.394	-31.985
道路运输业	1.785	6.668	0.267	-93.196
仓储业	7.458	15.834	0.471	-28.354
装卸搬运和运输代理业	5.133	15.926	0.322	-36.113
软件和信息技术服务业	0.553	4.676	0.118	-160.012
货币金融服务	0.998	8.773	0.113	-85.728
房地产业	0.569	3.823	0.148	-188.901
商务服务业	0.623	3.779	0.164	-187.516
研究和试验发展	0.897	4.327	0.207	-155.451
科技推广和应用服务业	1.101	4.325	0.254	-146.292
重点产业整体	0.205	1.307	0.157	-547.045

因素	自变量	变量含义	预期影响
注：+为正向影响，–为负向影响。
经济	经济发展水平	该地区人均GDP	+
市场	市场规模	该地区人口规模	+
劳动力	劳动力成本	该地区职工平均工资	-
交通	交通通达性	该地区公路路网密度	+
技术	技术投入水平	该地区科学技术财政支出占财政支出比例	+
信息	信息化水平	该地区宽带接入户数	+
对外开放	外商投资水平	该地区实际利用FDI金额	+
行政等级	城市等级	省会及副省级城市市区=49，地级市市区=7，县（县级市）=1	+
地方政策	开发区数量	该地区省级以上开发区数量	+

自变量	回归系数
注：^为P<0.05，^为P<0.01，^**为P<0.001。
交通通达性	-0.068^***
信息化水平	0.040
技术投入水平	0.002
劳动力成本	0.044^**
经济发展水平	0.067^***
开发区数量	0.049
外商投资水平	0.129^***
城市等级	0.388^***
市场规模	0.395^***
R²	0.971
Sig.	0.000

自变量	最小值	上分位数	中位数	下分位数	最大值	正值比	负值比	标准差
注：^为P<0.05，^为P<0.01，^**为P<0.001。
城市等级^***	0.013	0.319	0.407	0.468	0.601	100.00%	0	0.135
信息化水平	-0.226	-0.044	0.032	0.278	0.978	59.32%	40.68%	0.268
市场规模^***	-0.115	0.329	0.420	0.439	0.596	96.61%	3.39%	0.140
外商投资水平^***	0.073	0.087	0.104	0.146	1.727	100.00%	0	0.158
劳动力成本^**	0.001	0.045	0.058	0.075	0.104	100.00%	0	0.022
交通通达性^**	-0.154	-0.123	-0.083	-0.046	0.066	9.60%	90.40%	0.051
经济发展水平^*	0.020	0.039	0.049	0.065	0.151	100.00%	0	0.025
开发区数量	-0.028	0.011	0.029	0.046	0.104	85.31%	14.69%	0.022
技术投入水平	-0.228	-0.030	-0.004	0.009	0.066	40.68%	59.32%	0.041

东北三省企业空间格局演化与区位选择因素

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

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