基于金融细分行业的长三角城市网络的组织模式及驱动因素

doi:10.18306/dlkxjz.2022.04.003

Abstract

Abstract:

In the context of the development of regional economic integration, urban network research based on different financial industries has gradually become a research hotspot in financial geography. Using the data of 15524 financial companies in the Yangtze River Delta region from 1990 to 2017 and the interlocking network model, modularity, and QAP (quadratic assignment procedure) regression model, this study explored the organizational models and influencing factors of the urban network in the Yangtze River Delta over 27 years. The study found that: 1) From the perspective of the banking industry, the urban network presents a fan-shaped pattern with Shanghai as the core and radiating to cities such as Nanjing, Hangzhou, and Ningbo. From the perspective of the insurance industry, the multi-centric network pattern with Shanghai as the core and Nanjing, Hangzhou, Hefei, and other cities as the sub-centers is more prominent. From the perspective of the securities industry, the urban network connection pattern is relatively stable. 2) Based on different financial industries, urban networks have obvious characteristics of "small world" and scale-free networks. Geographic proximity and preferential links are important factors that affect the division of network "factions". 3) Core cities such as Shanghai, Nanjing, Hangzhou, and Hefei have strong network radiation and agglomeration capabilities and play the "gatekeeper" role in the overall network connection. However, due to the relatively small number of securities companies and slow expansion speed, their network radiation and agglomeration ability is far lower than that of banking and insurance networks. 4) The per capita GDP difference has an inverted U-shaped relationship with the banking network. Cities within the same administrative division and with geographic proximity can reduce spatial friction and promote the flow of factors. Cities with a similar industrial structure and financial environment can help release the lock-in effect, thereby accelerating the integration of actors into the external network.

Key words: urban network, organizational model, financial industry, Yangtze River Delta

ZHANG Yizhen, WANG Tao, ZHANG Han. Organizational models and driving factors of the Yangtze River Delta urban network based on different financial industries[J].PROGRESS IN GEOGRAPHY, 2022, 41(4): 567-581.

Figures/Tables 10

Tab.1

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Tab.2

Tab.3

Tab.4

Fig.6

References 39

[1]	潘峰华, 方成, 李仙德. 中国城市网络研究评述与展望[J]. 地理科学, 2019, 39(7): 1093-1101. doi: 10.13249/j.cnki.sgs.2019.07.007
	[ Pan Fenghua, Fang Cheng, Li Xiande. The progress and prospect of research on Chinese city network. Scientia Geographica Sinica, 2019, 39(7): 1093-1101. ] doi: 10.13249/j.cnki.sgs.2019.07.007
[2]	庄德林, 杨羊, 陈信康. 长江经济带城市网络空间结构的特征[J]. 城市问题, 2016(5): 10-17.
	[ Zhuang Delin, Chen Xinkang. Structural features of urban networks space of the Yangtze River Economic Belt: Based on the perspective of structure relations of listed companies. Urban Problems, 2016(5): 12-19. ]
[3]	汪涛, Hennemann S, Liefner I, 等. 知识网络空间结构演化及对NIS建设的启示: 以我国生物技术知识为例[J]. 地理研究, 2011, 30(10): 1861-1872.
	[ Wang Tao, Hennemann S, Liefner I, et al. Spatial structure evolution of knowledge network and its impact on the NIS: Case study of biotechnology in China. Geographical Research, 2011, 30(10): 1861-1872. ]
[4]	庄德林, 杨羊, 晋盛武, 等. 基于战略性新兴产业的长江三角洲城市网络结构演变研究[J]. 地理科学, 2017, 37(4): 546-553. doi: 10.13249/j.cnki.sgs.2017.04.008
	[ Zhuang Delin, Jin Shengwu, et al. Evolution of the Yangtze River Delta's city network based on the strategic emerging industries. Scientia Geographica Sinica, 2017, 37(4): 546-553. ] doi: 10.13249/j.cnki.sgs.2017.04.008
[5]	焦敬娟, 王姣娥, 金凤君, 等. 高速铁路对城市网络结构的影响研究: 基于铁路客运班列分析[J]. 地理学报, 2016, 71(2): 265-280. doi: 10.11821/dlxb201602007
	[ Jiao Jingjuan, Wang Jiao'e, Jin Fengjun, et al. Impact of high-speed rail on inter-city network based on the passenger train network in China, 2003-2013. Acta Geographica Sinica, 2016, 71(2): 265-280. ] doi: 10.11821/dlxb201602007
[6]	李雪铭, 刘贺, 田深圳, 等. 东北三省城市人居活动网络结构及影响因素分析: 基于百度贴吧分析[J]. 地理科学进展, 2019, 38(11): 1726-1734. doi: 10.18306/dlkxjz.2019.11.008
	[ Li Xueming, Liu He, Tian Shenzhen, et al. Network structure and influencing factors of urban human habitat activities in the three provinces of Northeast China: Based on Baidu Post Bar data. Progress in Geography, 2019, 38(11): 1726-1734. ] doi: 10.18306/dlkxjz.2019.11.008
[7]	王士君, 廉超, 赵梓渝. 从中心地到城市网络: 中国城镇体系研究的理论转变[J]. 地理研究, 2019, 38(1): 64-74. doi: 10.11821/dlyj020180468
	[ Wang Shijun, Lian Chao, Zhao Ziyu. From central place to city network: A theoretical change in China's urban system study. Geographical Research, 2019, 38(1): 64-74. ] doi: 10.11821/dlyj020180468
[8]	王聪, 曹有挥. 生产性服务业视角下城市网络的演化模式与机制研究: 以长江三角洲为例[J]. 地理科学, 2019, 39(2): 285-293. doi: 10.13249/j.cnki.sgs.2019.02.013
	[ Wang Cong, Cao Youhui. The evolution mode and mechanism of urban network from the perspective of producer services industry: A case of the Yangtze River Delta. Scientia Geographica Sinica, 2019, 39(2): 285-293. ] doi: 10.13249/j.cnki.sgs.2019.02.013
[9]	李小建. 金融地理学理论视角及中国金融地理研究[J]. 经济地理, 2006, 26(5): 721-725, 730.
	[ Li Xiaojian. A theoretical review of financial geography and study of financial geography in China. Economic Geography, 2006, 26(5): 721-725, 730. ]
[10]	Taylor P J. Specification of the world city network[J]. Geographical Analysis, 2001, 33(2): 181-194. doi: 10.1111/j.1538-4632.2001.tb00443.x
[11]	季菲菲, 陈雯. 长三角地区金融机构网络分布格局与扩张机理: 以城市商业银行为例[J]. 地理科学进展, 2014, 33(9): 1241-1251.
	[ Ji Feifei, Chen Wen. Distribution pattern and expansion mechanism of financial institution network in the Yangtze River Delta. Progress in Geography, 2014, 33(9): 1241-1251. ]
[12]	薛德升, 邹小华. 基于中资商业银行全球空间扩展的世界城市网络及其影响因素[J]. 地理学报, 2018, 73(6): 989-1001. doi: 10.11821/dlxb201806001
	[ Xue Desheng, Zou Xiaohua. The world city network based on the global expansion of Chinese commercial banks and its influencing factors. Acta Geographica Sinica, 2018, 73(6): 989-1001. ] doi: 10.11821/dlxb201806001
[13]	潘峰华, 徐晓红, 夏亚博, 等. 境外金融地理学研究进展及启示[J]. 地理科学进展, 2014, 33(9): 1231-1240.
	[ Pan Fenghua, Xu Xiaohong, Xia Yabo, et al. Progresses of financial geography and implications. Progress in Geography, 2014, 33(9): 1231-1240. ]
[14]	尹俊, 甄峰, 王春慧. 基于金融企业布局的中国城市网络格局研究[J]. 经济地理, 2011, 31(5): 754-759.
	[ Yin Jun, Zhen Feng, Wang Chunhui. China's city network pattern: An empirical analysis based on financial enterprises layout. Economic Geography, 2011, 31(5): 754-759. ]
[15]	赵金丽, 王曼曼, 张璐璐, 等. 中国城市群金融联系网络时空格局演化及影响因素[J]. 经济地理, 2018, 38(4): 91-99.
	[ Zhao Jinli, Wang Manman, Zhang Lulu, et al. Space-time pattern evolution and influencing factors of urban agglomeration financial connection network in China. Economic Geography, 2018, 38(4): 91-99. ] doi: 10.2307/142330
[16]	盛科荣, 王云靓, 樊杰. 中国城市网络空间结构的演化特征及机理研究: 基于上市公司500强企业网络视角[J]. 经济地理, 2019, 39(11): 84-93.
	[ Sheng Kerong, Wang Yunjing, Fan Jie. Dynamics and mechanisms of the spatial structure of urban network in China: A study based on the corporate networks of top 500 public companies. Economic Geography, 2019, 39(11): 84-93. ] doi: 10.2307/142497
[17]	李振发, 徐梦冉, 贺灿飞, 等. 金融地理学研究综述与展望[J]. 经济地理, 2018, 38(7): 7-15.
	[ Li Zhenfa, Xu Mengran, He Canfei, et al. Review and prospects on financial geography. Economic Geography, 2018, 38(7): 7-15. ]
[18]	盛科荣, 杨雨, 张红霞. 中国城市网络的凝聚子群及影响因素研究[J]. 地理研究, 2019, 38(11): 2639-2652. doi: 10.11821/dlyj020180729
	[ Sheng Kerong, Yang Yu, Zhang Hongxia. Cohesive subgroups and underlying factors in the urban network in China. Geographical Research, 2019, 38(11): 2639-2652. ] doi: 10.11821/dlyj020180729
[19]	Haberly D, Wójcik D. Regional blocks and imperial legacies: Mapping the global offshore FDI network[J]. Economic Geography, 2015, 91(3): 251-280. doi: 10.1111/ecge.12078
[20]	Coe N M, Lai K P Y, Wójcik D. Integrating finance into global production networks[J]. Regional Studies, 2014, 48(5): 761-777. doi: 10.1080/00343404.2014.886772
[21]	Schmitz B, von Hagen J. Current account imbalances and financial integration in the Euro area[J]. Journal of International Money and Finance, 2011, 30(8): 1676-1695. doi: 10.1016/j.jimonfin.2011.08.003
[22]	Robinson J. Global and world cities: A view from off the map[J]. International Journal of Urban and Regional Research, 2002, 26(3): 531-554. doi: 10.1111/1468-2427.00397
[23]	Clark G L. Money flows like mercury: The geography of global finance[J]. Geografiska Annaler: Human Geography, 2005, 87(2): 99-112.
[24]	Hazir C S, LeSage J, Autant-Bernard C. The role of R&D collaboration networks on regional knowledge creation: Evidence from information and communication technologies[J]. Papers in Regional Science, 2018, 97(3): 549-567. doi: 10.1111/pirs.12267
[25]	赵新正, 李秋平, 芮旸, 等. 基于财富500强中国企业网络的城市网络空间联系特征[J]. 地理学报, 2019, 74(4): 694-709. doi: 10.11821/dlxb201904006
	[ Zhao Xinzheng, Li Qiuping, Rui Yang, et al. The characteristics of urban network of China: A study based on the Chinese companies in the Fortune Global 500 list. Acta Geographica Sinica, 2019, 74(4): 694-709. ] doi: 10.11821/dlxb201904006
[26]	潘峰华, 方成. 从全球生产网络到全球金融网络: 理解全球-地方经济联系的新框架[J]. 地理科学进展, 2019, 38(10): 1473-1481. doi: 10.18306/dlkxjz.2019.10.003
	[ Pan Fenghua, Fang Cheng. From global production network to global financial network: A new framework for understanding global-local economic linkages. Progress in Geography, 2019, 38(10):1473-1481. ] doi: 10.18306/dlkxjz.2019.10.003
[27]	何则, 杨宇, 刘毅, 等. 世界能源贸易网络的演化特征与能源竞合关系[J]. 地理科学进展, 2019, 38(10): 1621-1632. doi: 10.18306/dlkxjz.2019.10.016
	[ He Ze, Yang Yu, Liu Yi, et al. Characteristics of evolution of global energy trading network and relationships between major countries. Progress in Geography, 2019, 38(10): 1621-1632. ] doi: 10.18306/dlkxjz.2019.10.016
[28]	李影影, 黄琪, 曹卫东, 等. 经济联系视角下泛长三角网络结构研究[J]. 世界地理研究, 2019, 28(1): 68-78.
	[ Li Yingying, Huang Qi, Cao Weidong, et al. Research on spatial network structure of Pan-Yangtze River Delta. World Regional Studies, 2019, 28(1): 68-78. ]
[29]	Fortunato S. Community detection in graphs[J]. Physics Reports, 2010, 486: 75-174. doi: 10.1016/j.physrep.2009.11.002
[30]	宋琼, 赵新正, 李同昇, 等. 多重城市网络空间结构及影响因素: 基于有向多值关系视角[J]. 地理科学进展, 2018, 37(9): 1257-1267. doi: 10.18306/dlkxjz.2018.09.008
	[ Song Qiong, Zhao Xinzheng, Li Tongsheng, et al. Spatial structures and influencing factors of multiple urban networks based on the perspective of directed-multivalued relation. Progress in Geography, 2018, 37(9): 1257-1267. ] doi: 10.18306/dlkxjz.2018.09.008
[31]	范擎宇, 杨山. 协调视角下长三角城市群的空间结构演变与优化[J]. 自然资源学报, 2019, 34(8):1581-1592.
	[ Fan Qingyu, Yang Shan. Evolution and optimization of spatial structure of the Yangtze River Delta urban agglomeration from the perspective of coordination. Journal of Natural Resources, 2019, 34(8): 1581-1592. ] doi: 10.31497/zrzyxb.20190802
[32]	周灿, 曾刚, 尚勇敏. 演化经济地理学视角下创新网络研究进展与展望[J]. 经济地理, 2019, 39(5): 27-36.
	[ Zhou Can, Zeng Gang, Shang Yongmin. Progress and prospect of research on innovation networks: A perspective from evolutionary economic geography. Economic Geography, 2019, 39(5): 27-36. ]
[33]	Goldsmith R W. Financial structure and development[M]. London, UK: Yale University Press, 1969.
[34]	叶雅玲, 林文盛, 李振发, 等. 中国城市间投融资网络结构及其影响因素[J]. 世界地理研究, 2020, 29(2): 307-316.
	[ Ye Yaling, Lin Wensheng, Li Zhenfa, et al. Spatial structure and influencing factors of urban investment and financing network in China. World Regional Studies, 2020, 29(2): 307-316. ]
[35]	李语杨, 谷人旭, 王腾飞, 等. 长三角地区知识守门人空间演变与作用机制研究[J]. 地理科学进展, 2021, 40(6): 925-936. doi: 10.18306/dlkxjz.2021.06.003
	[ Li Yuyang, Gu Renxu, Wang Tengfei, et al. Spatial evolution and mechanism of knowledge gatekeepers in the Yangtze River Delta region. Progress in Geography, 2021, 40(6): 925-936. ] doi: 10.18306/dlkxjz.2021.06.003
[36]	张宇, 曹卫东, 梁双波, 等. 中国春运城际出行网络结构特征与城市角色识别: 基于多元交通客流的测度[J]. 地理研究, 2021, 40(9): 2526-2541. doi: 10.11821/dlyj020200998
	[ Zhang Yu, Cao Weidong, Liang Shuangbo, et al. Structure characteristics of intercity travel network and identification of city role during the Spring Festival travel rush in China: Based on the measurement of multiple traffic passenger flows. Geographical Research, 2021, 40(9): 2526-2541. ]
[37]	Bathelt H, Zeng G. Strong growth in weakly-developed networks: Producer-user interaction and knowledge brokers in the Greater Shanghai chemical industry[J]. Applied Geography 2012, 32(1):158-170. doi: 10.1016/j.apgeog.2010.11.015
[38]	盛科荣, 杨雨, 孙威. 中国城市网络中心性的影响因素及形成机理: 基于上市公司500强企业网络视角[J]. 地理科学进展, 2019, 38(2): 248-258. doi: 10.18306/dlkxjz.2019.02.008
	[ Sheng Kerong, Yang Yu, Sun Wei. Determinants and mechanisms of degree centrality in the urban network in China: A study based on corporate networks of the largest 500 listed companies. Progress in Geography, 2019, 38(2): 248-258. ] doi: 10.18306/dlkxjz.2019.02.008
[39]	马学广, 李鲁奇. 中国城市网络化空间联系结构: 基于银行网点数据的研究[J]. 地理科学进展, 2017, 36(4): 393-403. doi: 10.18306/dlkxjz.2017.04.001
	[ Ma Xueguang, Li Luqi. Network spatial connection structure of Chinese cities based on bank branches data. Progress in Geography, 2017, 36(4): 393-403. ] doi: 10.18306/dlkxjz.2017.04.001

年份	地区	银行	保险	证券
2000	上海	512	39	59
	江苏	844	28	86
	浙江	165	9	24
	安徽	82	2	26
2008	上海	707	1471	160
	江苏	1125	734	230
	浙江	300	610	131
	安徽	320	213	134
2017	上海	1409	2110	310
	江苏	1831	2841	716
	浙江	1822	2060	329
	安徽	844	977	275

因变量(Y)	自变量(X)	自变量的解释	预期符号
城市网络关联矩阵	经济发展	人均GDP差值(X₁)	+
		人均GDP差值的平方(X₂)	-
		第三产业产值占GDP 比重(X₃)	-
	金融发展	金融相关比率(X₄)	-
	政府干预	地方政府财政支出(X₅)	-
	行政区划	行政边界0-1矩阵(X₆)	+
	地理距离	城市行政中心间距离(X₇)	-

被解释变量	银行业		保险业		证券业
被解释变量	回归系数	P值	回归系数	P值	回归系数	P值
经济发展
人均GDP差值	0.201^**	0.014	0.139^**	0.011	0.119^**	0.015
人均GDP差值的平方	-0.279^**	0.035	-0.126	0.753	-0.194	0.672
第三产业产值占GDP比重	-0.245^***	0.007	-0.362^***	<0.001	-0.201^***	0.005
金融发展
金融相关比率	-0.073	0.318	-0.198^**	0.012	-0.117^*	0.054
政府干预
地方政府财政支出	-0.031	0.322	0.035	0.185	0.031	0.383
行政区划
行政边界0-1矩阵	0.082^**	0.047	0.078^**	0.034	0.064^*	0.066
地理距离
城市行政中心间距离	-0.156^***	<0.001	-0.223^***	<0.001	-0.144^***	0.004

被解释变量	银行业		保险业		证券业
被解释变量	回归系数	P值	回归系数	P值	回归系数	P值
经济发展
人均GDP差值	0.255^**	0.017	0.338^***	0.006	0.067^**	0.018
人均GDP差值的平方	-0.301^**	0.042
第三产业产值占GDP比重	-0.531^***	0.010	-0.476^***	<0.001	-0.138^***	0.002
金融发展
金融相关比率			-0.207^*	0.066	-0.124^*	0.076
行政区划
行政边界0-1矩阵	0.163^***	<0.001	0.116^***	<0.001	0.025^***	0.004
地理距离
城市行政中心间距离	-0.077^***	<0.001	-0.138^***	<0.001	-0.378^***	<0.001

Organizational models and driving factors of the Yangtze River Delta urban network based on different financial industries

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 10

References 39

Related Articles 15

Metrics

Comments

Recommended 0

[1]	FANG Yelin, SU Xueqing, HUANG Zhenfang, CHENG Xuelan. Spatial spillover effect of urban resilience on tourism economy: A case study of the Yangtze River Delta urban agglomeration [J]. PROGRESS IN GEOGRAPHY, 2022, 41(2): 214-223.
[2]	LI Yuyang, GU Renxu, WANG Tengfei, BI Xuecheng. Spatial evolution and mechanism of knowledge gatekeepers in the Yangtze River Delta region [J]. PROGRESS IN GEOGRAPHY, 2021, 40(6): 925-936.
[3]	TANG Zhaopei, WU Wei, LIU Weichen, LI Xiaoli. Effects of high-speed rail on the spatial agglomeration of producer services: A case study of the Yangtze River Delta urban agglomeration [J]. PROGRESS IN GEOGRAPHY, 2021, 40(5): 746-758.
[4]	ZHANG Rong, PAN Jinghu, LAI Jianbo. Characteristics of intercity trip network structure of residents under different traffic modes: A case study of Spring Festival travel rush [J]. PROGRESS IN GEOGRAPHY, 2021, 40(5): 759-773.
[5]	ZHU Dongfang, YU Hu, LIU Qingqing, LIU Limin. Network structure characteristics and organizational models of tourist flow to Tibet: Comparative analysis based on group and self-guided tours [J]. PROGRESS IN GEOGRAPHY, 2021, 40(5): 812-824.
[6]	CHENG Yuhong, SU Xiaomin. Review on the urban network externalities [J]. PROGRESS IN GEOGRAPHY, 2021, 40(4): 713-720.
[7]	LIANG Xinyuan, JIN Xiaobin, HAN Bo, SUN Rui, ZHANG Xiaolin, ZHOU Yinkang. Landscape multifunctionality change in rapidly urbanized areas of the Yangtze River Delta:A case study of Suzhou City [J]. PROGRESS IN GEOGRAPHY, 2021, 40(2): 207-219.
[8]	YANG Qingke, DUAN Xuejun, WANG Lei, WANG Yazhu. Mechanism of interaction between urban land expansion and ecological environment effects in the Yangtze River Delta [J]. PROGRESS IN GEOGRAPHY, 2021, 40(2): 220-231.
[9]	HAN Gang, SHI Xiusong, LIU Zhimin. Formation mechanism of network compactness in Jiangsu Province based on exponential random graph models [J]. PROGRESS IN GEOGRAPHY, 2021, 40(12): 2025-2034.
[10]	FAN Qingyu, YANG Shan. Spatial characteristics and formation mechanism of coordinated development of urbanization in the Yangtze River Delta [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 124-134.
[11]	ZHANG Haina, ZHU Yiwen, DENG Xiaoxiang. Mechanism of residential spatial differentiation affecting the social integration of landless farmers in suburbs: An empirical analysis on the Yangtze River Delta [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 135-146.
[12]	SUN Biao, YANG Shan. Economic spillover effects and convergence patterns of urban innovation input features in the Yangtze River Delta region [J]. PROGRESS IN GEOGRAPHY, 2021, 40(1): 147-160.
[13]	HU Guojian, LU Yuqi. Progress, thoughts, and prospect of urban network research based on enterprise perspective [J]. PROGRESS IN GEOGRAPHY, 2020, 39(9): 1587-1596.
[14]	YANG Yanjie, YIN Dan, LIU Ziwen, HUANG Qingxu, HE Chunyang, WU Kang. Research progress on the space of flow using big data [J]. PROGRESS IN GEOGRAPHY, 2020, 39(8): 1397-1411.
[15]	YAN Dongsheng, SUN Wei, WANG Yue, XU Shiyao. Change in distribution and growth shifts of population in the Yangtze River Delta and influencing factors [J]. PROGRESS IN GEOGRAPHY, 2020, 39(12): 2068-2082.