资源科学 ›› 2021, Vol. 43 ›› Issue (5): 886-897.doi: 10.18402/resci.2021.05.03

• 资源管理 • 上一篇    下一篇

中国城市群知识多中心发展评价

戴靓1(), 曹湛2(), 朱青3, 殷亚若1   

  1. 1.南京财经大学公共管理学院,南京 210023
    2.同济大学建筑与城市规划学院,上海 200092
    3.中国科学院南京地理与湖泊研究所,南京 210008
  • 收稿日期:2020-04-06 修回日期:2020-08-22 出版日期:2021-05-25 发布日期:2021-07-25
  • 通讯作者: 曹湛,男,湖北潜江人,博士后,研究方向为城乡规划、城市与区域发展规划和城市网络。E-mail: 1989caozhan@tongji.edu.cn
  • 作者简介:戴靓,女,江苏镇江人,副教授、硕士生导师,研究方向为城市网络与区域发展。E-mail: 9120181027@nufe.edu.cn
  • 基金资助:
    国家自然科学基金项目(41901189);国家自然科学基金项目(52008298);江苏省自然科学基金项目(BK20190797);中国科学院区域可持续发展分析与模拟重点实验室开放基金项目(KF2018-07)

Analyzing polycentric urban development in China: Evidence from intercity knowledge collaboration

DAI Liang1(), CAO Zhan2(), ZHU Qing3, YIN Yaruo1   

  1. 1. School of Public Administration, Nanjing University of Finance & Economics, Nanjing 210023, China
    2. College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    3. Nanjing Institute of Geography & Limnology, CAS, Nanjing 210008, China
  • Received:2020-04-06 Revised:2020-08-22 Online:2021-05-25 Published:2021-07-25

摘要:

在新型城镇化和高质量发展背景下,城市群的空间结构及其多中心发展成为城市研究的热点议题。本文基于Web of Science(WOS)数据库中国学者2012—2016年的论文发表数据,采用Taylor的多中心性测度,从知识规模和知识网络层面,对中国19个城市群知识形态多中心与功能多中心进行量化,进而分析不同城市群知识多中心的发展状况、原因及对策,主要结论如下:①中国城市群的知识规模分布和知识合作格局均具有较强的空间异质性,东部城市群知识多中心发育优于中西部城市群,城市群形态与功能多中心发展整体匹配度高。②以中国19个城市群知识形态和功能多中心度的平均值为界,可将城市群分为4类:Ⅰ知识形态与功能均相对多中心发展的城市群,以长三角城市群最为典型;Ⅱ知识形态相对单中心但功能相对多中心发展的城市群,如珠三角城市群;Ⅲ知识形态与功能均相对单中心发展的城市群,以宁夏沿黄城市群最为典型;Ⅳ知识形态相对多中心但功能相对单中心发展的城市群,如成渝城市群。③中国城市群知识多中心发展是市场驱动和政策引导共同作用的结果,对于知识形态相对单中心发展的城市群,需重点加强知识创新资源的合理规划与布局;对于知识功能相对单中心发展的城市群,需积极打破知识流通壁垒,形成多元合作共享机制。

关键词: 城市群, 城市网络, 知识合作, 形态多中心, 功能多中心, 多中心度

Abstract:

Against the backdrop of new urbanization and high-quality development, the spatial structure of urban agglomerations and their polycentric development have become a hot issue in urban studies. Based on the publication data of Chinese scholars from 2012 to 2016 derived from the Web of Science (WOS), this research assessed the knowledge morphological polycentricity and functional polycentricity of 19 urban agglomerations in China by employing Taylor’s polycentricity measurement through the lens of scientific knowledge output and knowledge collaboration network. After quantifying and analyzing the development status, this research explored the determinants of polycentric urban development in China and made some policy recommendations for future development. The results show that: (1) There exists an obvious spatial heterogeneity in both knowledge resources distribution and the knowledge collaboration patterns among different urban agglomerations. The polycentric development of urban agglomerations in the east is better than their central and western counterparts. The overall development of morphological and functional polycentricities is consistent. (2) Urban agglomerations can be divided into four categories: Ⅰ. urban agglomerations with both morphologically and functionally polycentric development, which is typical for the Yangtze River Delta urban agglomeration; Ⅱ. urban agglomerations with morphologically monocentric but functionally polycentric development consisting of the Pearl River Delta urban agglomeration; III. urban agglomerations with both morphologically and functionally monocentric development, which is typical for the northern Ningxia urban agglomeration along the Yellow River; IV. urban agglomerations with morphologically polycentric but functionally monocentric development consisting of the Chengdu-Chongqing urban agglomeration. (3) The knowledge polycentric development of China’s urban agglomerations is driven by both market and policies. For urban agglomerations with the development of knowledge morphological monocentricity, emphasis should be put on the scientific planning and layout of knowledge innovation resources; for those with relatively functionally monocentric development, local governments need to break the barriers of knowledge flows and form a diversified collaboration and sharing mechanism.

Key words: urban agglomeration, urban network, knowledge collaboration, morphological polycentricity, functional polycentricity, degree of polycentricity