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长江中游城市群社团结构演化及其邻近机制 ——基于生产性服务企业网络分析
引用本文:高鹏,何丹,宁越敏,张凡.长江中游城市群社团结构演化及其邻近机制 ——基于生产性服务企业网络分析[J].地理科学,2019,39(4):578-586.
作者姓名:高鹏  何丹  宁越敏  张凡
作者单位:华东师范大学中国现代城市研究中心,上海200062;华东师范大学城市与区域科学学院,上海200241;华东师范大学中国现代城市研究中心,上海,200062
基金项目:国家自然科学基金面上项目(41471138)、国家留学基金委项目(201706145003)、教育部人文社会科学重点研究基地重大项目(17JJD790007)、国家自然基金青年项目(41701181)资助
摘    要:刻画长江中游城市群空间结构演化特征,通过QAP分析定量揭示其影响机制。结果显示:长江中游城市群存在3个分别以武汉、长沙和南昌为核心、以省界为界限的城市社团,社团结构存在显著的异质性特征。城市群层面上,地理邻近、文化邻近和行政邻近均对城市群社团结构产生显著影响,行政邻近中的省级行政邻近影响最大;交流技术进步、金融资源集聚与扩散对社团内外联系也产生显著影响。分析社团层面,发现此时地理邻近在各社团内部结网互动中起决定性作用,且不同影响因素在3个社团中的影响效应存在一定的差异性。

关 键 词:社团结构  邻近机制  生产性服务业  社团发现算法  长江中游城市群
收稿时间:2018-03-08
修稿时间:2018-06-10

Community Structure and Proximity Mechanism of City Clusters in Middle Reach of the Yangtze River: Based on Producer Service Firms’ Network
Peng Gao,Dan He,Yuemin Ning,Fan Zhang.Community Structure and Proximity Mechanism of City Clusters in Middle Reach of the Yangtze River: Based on Producer Service Firms’ Network[J].Scientia Geographica Sinica,2019,39(4):578-586.
Authors:Peng Gao  Dan He  Yuemin Ning  Fan Zhang
Institution:1. The Center for Modern Chinese City Studies, East China Normal University, Shanghai 200062, China
2. School of Urban & Regional Science, East China Normal University, Shanghai 200241, China;
Abstract:Community structure, as an emerging research field of network science, is very critical for us to cognize the spatial structure of city clusters more deeply. So far, however, previous work has failed to examine the spatial structure of the urban system in terms of its community structure systematically. To rectify this situation and provide new research approach, this article uses community detection algorithm to reveal the evolving features of community structure of city clusters in middle reach of the Yangtze River(MRYR) at county scale, based on 2000, 2007 and 2014 producer services firms’ database of city clusters in MRYR. Furthermore, this article introduces the Quadratic Assignment Procedure(QAP) to uncover the proximity mechanism and other influencing factors. The main conclusions are as follows: According to the results of network modularity and PageRank, city clusters in MRYR could be divided into three city communities, including Wuhan community, Changsha community and Nanchang community, and community structure has significant heterogeneity, which reflects in the inequality of both intra and inter communities. At city clusters’ level, geographical proximity, cultural proximity and administrative proximity have dramatic effects on community structure of city clusters in MRYR, but provincial administrative proximity causes dominant effects. Additionally, progress in communications technology and financial resources of the clustering and diffusion spur on connections intra and inter communities of city clusters in MRYR. Once inside communities’ level, geographical proximity plays a key role in the process of cities’ interacting within city community. Moreover, some influencing factors have different effects on different city communities, which provides us some beneficial policy enlightenments.
Keywords:community structure  proximity mechanism  producer services  community detection  city clusters in middle reach of the Yangtze River  
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