主管单位:中国科学技术协会
主办单位:中国地理学会
承办单位:华东师范大学

世界地理研究 ›› 2018, Vol. 27 ›› Issue (05): 136-146.

• 文化与社会 • 上一篇    下一篇

中国城市间创新网络结构及其邻近性机理

鲜果1,曾刚2,曹贤忠2   

  1. 1. 华东师范大学城市与区域科学学院
    2. 华东师范大学
  • 收稿日期:2017-07-05 修回日期:2017-09-19 出版日期:2018-10-15 发布日期:2018-10-09
  • 通讯作者: 鲜果
  • 基金资助:
    基于长江经济带发展战略的长三角科技创新合作研究;中国装备制造业创新网络研究

Structural and proximity mechanism of Chinese intercity innovation network

    

  1.  
  • Received:2017-07-05 Revised:2017-09-19 Online:2018-10-15 Published:2018-10-09
  • Supported by:
     

摘要: 城市是实施国家创新驱动发展战略的重要空间载体,构建城市间创新网络成为促进城市间知识溢出,优化区域创新资源配置,提升城市创新竞争力的重要途径。本文基于中国290个地级及以上城市联合申请发明专利数据,借助社会网络分析技术和负二项重力模型,对中国城市间创新网络的拓扑结构、空间格局及其邻近性机理进行分析。结果发现:1.拓扑结构上,中国城市间创新网络范围广密度低,大多数城市间合作强度较低,网络连接较为松散;网络等级层次清晰,发育出以北京为强核心,上海、南京、武汉等为核心的“核心—边缘”结构。2.空间结构上,以胡焕庸线为界,网络联系东密西疏、东强西弱,城市等级东高西低;不同等级的网络流强度具有显著的空间异质性,核心、次核心城市在空间上呈现“大分散、小集聚”的特点;3.邻近性机理上,负二项重力模型回归显示,制度邻近性与技术邻近性对我国城市间创新合作均具有显著促进作用,而地理距离阻碍了我国城市间创新合作。

 

Abstract: The city is an important space carrier for the implementation of the national innovation-driven development strategy. Constructing intercity innovation network is an important way to promote knowledge spillover between cities, optimize regional innovation resource allocation and improve the innovation competitiveness of cities. Based on joint applications for invention patent of 290 Chinese cities in 2014 mined from State Intellectual Property Office (SIPO), with the help of social network analysis and gravity model approach, this article aims to reveal the topological structure, spatial pattern of Chinese intercity innovation network and tries to analyze the underlying proximity mechanism. The main conclusions are as follows: Firstly, as to topological structure, Chinese intercity innovation network is extensive but low-density and the network connection is relatively loose. Most intercity innovation cooperation is low- intensity, needing further enhancements. In addition, the entire network has an obvious clustering trend and presents a core- periphery structure with hierarchies, of which the center core layer contains only one city-Beijing but the periphery layer contains more than half of the cities. Secondly, as to spatial pattern, taking Hu's line as boundary, the spatial heterogeneity of Chinese intercity innovation network is significant. The network connections are dense and strong in the east but sparse and weak in the west. Similar to geographical distribution characteristic of the network, the city grade is high in the east but low in the west. Moreover, different levels of network flow intensity have significant spatial heterogeneity. Core and sub-core cities are featured by a ‘big scattered and small gathering’ spatial pattern. Last but not least, the test results of negative binomial regression model show that geographical distance is an impediment to Chinese intercity innovation cooperation, which is a powerful refutation of the claim that geography has died. Meanwhile, institutional proximity and technical proximity both have a significant effect on innovation cooperation between Chinese cities.

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