长三角地区多尺度城市网络空间演化及互馈效应研究

doi:10.13249/j.cnki.sgs.2022.10.009

Abstract

Abstract:

Based on the cross-national, cross-regional and regional enterprises’ nonlocal investment data in the Yangtze River Delta (YRD) and applying the social network analysis, panel vector auto regression and geographically weighted regression, this paper reveals the spatial evolution characteristics and interaction effects of the YRD’s multi-scalar urban networks. The results are obtained as follows: Global, national, and regional urban networks in the YRD are in the preliminary, steady, and perfect development stages. Besides, the YRD’s multi-scalar urban networks tend to be regionalized: On a global scale, a dense regional network is gradually forming between the YRD and East Asia, Western Europe, and North America; on a national scale, the connectivity between the YRD and Beijing-Tianjin-Hebei and the Pearl River Delta becomes closer; on a regional scale, there are closer economic ties within the provinces compared with trans-provincial economic ties. Additionally, the network spatial structure dominated by the Shanghai-Nanjing-Hefei-Hangzhou-Ningbo development corridor is forming. When it comes to the interaction effects of the YRD’s multi-scalar urban networks, there is a mutual promotion relationship between the global and national functional connectivity. The improvement of the city’s regional functional connectivity can promote its integration into the global and national urban networks. However, the improvement of the city’s global and national functional connectivity cannot promote its further integration into the YRD’s regional urban network, and its integration into the global urban network even has a significant inhibitory effect on the city’s regional functional connectivity. Furthermore, obvious spatial heterogeneity of interaction effects can be observed, which is coupled with regional economic development patterns.

Key words: enterprises’ nonlocal investment, multi-scalar urban networks, interaction effects, the Yangtze River Delta

CLC Number:

F291

Gao Peng, Ning Yuemin, He Dan. Spatial Evolution and Interaction Effects of Multi-scalar Urban Networks in the Yangtze River Delta[J].SCIENTIA GEOGRAPHICA SINICA, 2022, 42(10): 1767-1777.

Figures/Tables 6

Table 1

Fig. 1

Table 2

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Table 3

Fig. 3

References 32

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统计特征	统计指标	全球尺度			全国尺度			区域尺度
统计特征	统计指标	2003年	2010年	2018年	2003年	2010年	2018年	2003年	2010年	2018年
注：全国尺度数据来源于A股上市企业年报，未覆盖到中国香港、中国澳门、中国台湾相关城市数据；全球尺度数据来源于Bureau van Dijk数据库，覆盖到中国香港、中国澳门、中国台湾相关城市数据。
网络规模	企业总部数量/家	181	1534	3312	444	966	2695	177	384	902
	投资总额/亿元	989	6690	21943	839	3885	20726	201	1438	7936
	节点数	97	253	409	182	256	322	41	41	41
	边数	146	603	1182	498	1141	3082	179	345	667
	密度	0.016	0.009	0.007	0.015	0.017	0.030	0.109	0.210	0.407
集聚程度	平均聚类系数	0.000	0.001	0.003	0.007	0.008	0.010	0.462	0.517	0.631
	模块度指数	0.252	0.392	0.365	0.488	0.367	0.310	0.412	0.345	0.321

GFC模型			NFC模型			RFC模型
变量	系数	Z值	变量	系数	Z值	变量	系数	Z值
注：^、^、^*分别代表在10%、5%和1%的水平上显著；括号内为标准误；GFC、NFC、RFC分别表示全球功能联系、全国功能联系和区域功能联系；ΔGFC、ΔNFC、ΔRFC*分别表示全球功能联系、全国功能联系和区域功能联系的1阶差分；全国尺度数据来源于A股上市企业年报，未覆盖到中国香港、中国澳门、中国台湾相关城市数据；全球尺度数据来源于Bureau van Dijk数据库，覆盖到中国香港、中国澳门、中国台湾相关城市数据。
ΔGFC	0.803^*** （0.000）	5.740	ΔGFC	0.362^* （0.053）	1.931	ΔGFC	−0.353^* （0.068）	−1.110
ΔNFC	0.537^** （0.020）	3.112	ΔNFC	0.604^** （0.041）	2.043	ΔNFC	0.431 （0.352）	0.930
ΔRFC	0.234^*** （0.001）	3.272	ΔRFC	0.246^* （0.068）	1.820	ΔRFC	0.981^*** （0.000）	4.831

期数	GFC模型			NFC模型			RFC模型
期数	GFC	NFC	RFC	GFC	NFC	RFC	GFC	NFC	RFC
注：GFC、NFC、RFC分别为全球功能联系、全国功能联系和区域功能联系；全国尺度数据来源于A股上市企业年报，未覆盖到中国香港、中国澳门、中国台湾相关城市数据；全球尺度数据来源于Bureau van Dijk数据库，覆盖到中国香港、中国澳门、中国台湾相关城市数据。
1	70.0	10.2	19.8	10.6	89.4	0	0	13.5	86.5
2	64.0	14.8	21.2	6.1	83.0	10.9	2.0	21.1	76.9
3	47.7	21.5	30.8	4.0	78.5	17.5	2.9	23.6	73.5
4	39.3	25.0	35.7	2.7	75.5	21.8	3.4	24.4	72.2
5	34.5	27.0	38.5	0.9	73.2	24.9	3.8	24.5	71.7
6	29.3	29.2	41.5	0.3	71.3	28.4	4.5	23.2	72.3
7	31.9	26.3	41.8	0.8	69.6	29.6	4.6	22.8	72.6
8	29.9	28.1	42.0	0.7	69.1	30.2	4.7	22.3	73.0
9	27.8	29.5	42.7	0.5	66.0	33.5	5.1	21.8	73.1
10	26.4	30.6	43.0	0.4	65.3	34.3	5.3	21.4	73.3

Spatial Evolution and Interaction Effects of Multi-scalar Urban Networks in the Yangtze River Delta

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