地理学报 ›› 2023, Vol. 78 ›› Issue (2): 334-350.doi: 10.11821/dlxb202302005

• 国家创新体系与科技全球化 • 上一篇    下一篇

中国城市知识合作网络结构演化的影响机制

戴靓1(), 曹湛2,3(), 马海涛4, 纪宇凡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.自然资源部国土空间智能规划技术重点实验室,上海 200092
    4.中国科学院地理科学与资源研究所 中国科学院区域可持续发展分析与模拟重点实验室,北京 100101
  • 收稿日期:2021-08-16 修回日期:2022-02-15 出版日期:2023-02-25 发布日期:2023-02-16
  • 通讯作者: 曹湛(1989-), 男, 湖北潜江人, 博士, 助理教授, 研究方向为国土空间规划、城市网络和创新网络。E-mail: 1989caozhan@tongji.edu.cn
  • 作者简介:戴靓(1989-), 女, 江苏镇江人, 博士, 副教授, 硕士生导师, 中国地理学会会员(S110014330M), 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);国家自然科学基金项目(41971209);江苏省自然科学基金项目(BK20190797)

The influencing mechanisms of evolving structures of China's intercity knowledge collaboration networks

DAI Liang1(), CAO Zhan2,3(), MA Haitao4, JI Yufan1   

  1. 1. School of Public Administration, Nanjing University of Finance and Economics, Nanjing 210023, China
    2. College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    3. Key Laboratory of Spatial Intelligent Planning Technology, Ministry of Natural Resources of the People's Republic of China, Shanghai 200092, China
    4. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
  • Received:2021-08-16 Revised:2022-02-15 Published:2023-02-25 Online:2023-02-16
  • Supported by:
    National Natural Science Foundation of China(41901189);National Natural Science Foundation of China(52008298);National Natural Science Foundation of China(41971209);Natural Science Foundation of Jiangsu Province(BK20190797)

摘要:

城市知识合作网络的影响机制是创新地理的重要研究议题,已有研究大多关注外生动力(城市资源禀赋、多维邻近性等)的影响,而较少关注内生动力因素(择优链接、传递性等)。基于“Web of Science”中的论文合作发表数据构建中国城市知识合作网络,分析其2006—2016年空间结构和拓扑结构的演化特征,并通过加权随机指数图模型(ERGM)定量揭示内生和外生动力对该网络形成的影响。结果显示:① 从空间结构看,东密西疏的格局比较稳定,但整体由北京—上海双核结构向多中心发展,五大国家级城市群成为孕育多极的重要空间。以高能级城市为核心形成的节点区域愈发与规划的城市群范围一致,其发挥着知识资源邻近溢出和远程交互的双重作用。② 从拓扑结构看,知识合作的规模和密度显著增加,对大城市的择优选择效应明显。但随着多中心崛起,网络极化程度和异配性均在弱化;随着城际合作路径不断优化,网络聚合性提升,成为小世界网络。③ 从影响机制看,自演化与择优链接是知识网络的重要驱动力,其作用与城市等级效应相重叠;城市知识规模属性对知识流动的正向影响弱于多维邻近性和路径依赖性;高铁的存在有利于促进知识合作,而地理距离的影响不显著。

关键词: 知识网络, 论文合作, 影响机制, 内生结构变量, 加权指数随机图模型

Abstract:

The study of influencing mechanisms of intercity knowledge collaboration networks is an important research topic of innovative geography. Most existing research focuses on the influence of exogenous forces (e.g., urban resources endowment, multidimensional proximity), whereas less attention has been paid to endogenous factors (e.g., preferential attachment, transitivity). This research constructs an intercity knowledge collaboration network of Chinese cities based on the co-publication data from the Web of Science, analyzes its evolving characteristics of spatial and topological structures from 2006 to 2016, and quantitatively explores the endogenous and exogenous forces underlying the network formation through exponential random graph modelling. The results show that: (1) From the spatial structure perspective, the intercity knowledge flows are dense in the eastern region but spare in the western region, which is stable during 2006-2016. The overall network has developed from a dual-core structure of Beijing and Shanghai to a polycentric structure, in which five national-level urban agglomerations have become important bases for nurturing multiple centers. The nodal regions centered on highly administrative cities have become increasingly consistent with the planned urban agglomeration, which plays the dual role of proximal spillover and remote interaction of knowledge resources. (2) From the topological structure perspective, the scale and density of intercity knowledge flows have increased significantly, and the preferential attachment to big cities is obvious. However, with the rise of multiple centers, the network polarization and disassortativity have been weakened. With the optimization of intercity knowledge collaboration paths, the network cohesion has improved, thus becoming a small-world network. (3) From the influencing mechanism perspective, self-evolution and preferential attachment are important driving forces of knowledge collaboration networks, showing an overlapping effect with urban hierarchy. The positive impact of urban knowledge-related attributes on intercity flows is weaker than multidimensional proximity and path dependence. The presence of high-speed railways promotes knowledge collaboration, while the influence of geographic distance is not significant.

Key words: knowledge network, scientific collaboration, influencing mechanism, endogenous structural variables, exponential random graph model