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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
引用本文:章屹祯,汪涛,张晗.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[J].地理科学进展,2022,41(4):567-581.
作者姓名:章屹祯  汪涛  张晗
作者单位:1.南京师范大学地理科学学院,南京 210023
2.江苏省地理信息资源开发与利用协同创新中心,南京 210023
基金项目:国家自然科学基金项目(41471103);江苏高校哲学社会科学研究重大项目(2020SJZDA135);江苏省研究生科研创新计划项目(KYCX21_1286)
摘    要:在区域经济一体化发展背景下,基于金融细分行业的城市网络研究逐渐成为金融地理学的研究热点。论文以1990—2017年长三角15524家金融企业为研究对象,应用连锁网络模型、模块度及QAP(quadratic assignment procedure)关系回归模型,探究长三角城市网络的组织模式及驱动因素。研究发现:① 银行业视角下,城市网络呈现以上海为核心向南京、杭州、宁波等城市辐射的扇形格局;保险业视角下,以上海为核心,以南京、杭州、合肥等城市为次核心的多中心网络格局较为凸显;证券业视角下,城市网络联系形态相对稳定。② 不同金融行业下,城市网络均具有明显的“小世界”与无标度网络特性,地理邻近、择优链接是影响网络“派系”划分的重要因素。③ 上海、南京、杭州、合肥等核心城市具备较强的网络辐射与集聚能力,在整体网络连接中扮演“守门人角色”;但由于证券企业数量相对较少、扩张速度较慢,导致其网络辐射与集聚能力远低于银行与保险网络。④ 人均GDP差值与银行网络呈倒U型关系;同一行政区划和地理邻近的城市能减小空间摩擦,促进要素流动;产业结构与金融环境相似的城市有助于解除锁定,从而加快其融入外部网络。

关 键 词:城市网络  组织模式  金融业  长三角  
收稿时间:2021-06-28
修稿时间:2021-09-27

Organizational models and driving factors of the Yangtze River Delta urban network based on different financial industries
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.
Authors:ZHANG Yizhen  WANG Tao  ZHANG Han
Institution:1. School of Geography, Nanjing Normal University, Nanjing 210023, China
2. Jiangsu Province Geographic Information Resources Development and Utilization Collaborative Innovation Center, Nanjing 210023, China
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.
Keywords:urban network  organizational model  financial industry  Yangtze River Delta  
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