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人文地理  2020, Vol. 35 Issue (1): 95-103    DOI: 10.13959/j.issn.1003-2398.2020.01.011
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多尺度视角下中国城市创新网络格局及邻近性机理分析
马双1, 曾刚2
1. 上海社会科学院 信息研究所, 上海 200235;
2. 华东师范大学 中国现代城市研究中心/城市与区域科学学院, 上海 200062
ANALYSIS OF CHINA'S URBAN INNOVATION NETWORK PATTERN AND ITS PROXIMITY MECHANISM FROM A MULTI-SCALE PERSPECTIVE
MA Shuang1, ZENG Gang2
1. Institute of Information, Shanghai Academy of Social Sciences, Shanghai 200235, China;
2. The Center for Modern Chinese City Studies/School of Urban & Regional Science, East China Normal University, Shanghai 200062, China

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摘要 借助2016年国家知识产权局的专利合作数据,利用复杂网络和空间分析方法对国家、区际和省内三个尺度的城市创新网络结构进行刻画,并利用负二项回归法对创新合作的邻近性机理进行了剖析。研究表明:①全国城市创新网络的整体联系较弱,网络极化现象明显,空间结构呈现出以北京为核心的放射型网络形态。区际城市创新网络的跨区域网络联系强于区内网络联系,东中西形成以区域中心城市为核心的异质性空间结构。省内城市创新网络的本地结网不足,内部联系强度低,空间形态普遍呈现出以省会城市为中心的核心-边缘结构。②回归结果证实了社会邻近、技术邻近对城市创新结网具有显著的促进作用,地理邻近则呈现出不显著的正向影响。其中,技术邻近的促进作用显著高于社会邻近,而地理邻近则需要通过社会邻近的调节效应对创新结网产生影响。
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马双
曾刚
关键词 多尺度城市创新网络格局邻近性    
Abstract:Actively cultivating and constructing urban innovation network has become the key to promote the development of higher quality economy for country and region. This paper using the co-patent data of the SIPO to construct the city innovation network. Then, depicting its structure of three spatial scales (country, inter-region and province) based on the complex network and spatial analysis methods, and analyzing the proximity mechanism of innovation cooperation based on negative two regression method. The research finds that:1) the overall connection of the national innovation network is weak and the network polarization is obvious. The spatial structure shows a radial network with Beijing as the core, Shanghai, Shenzhen, Nanjing, Hangzhou and Fuzhou as the main nodes. In the south China, Shanghai, Nanjing, Suzhou, Hangzhou, Nanchang, Shenzhen and other cities have formed a number of innovation cooperation loops. The interregional innovation network is stronger than that of intra-regional network at sub-region scale. A heterogeneous spatial structure centered on regional central cities is formed in every sub-region. 2) Regression results confirm that geographical proximity, social proximity and technological proximity play a significant role in promoting urban innovative networking. Among them, geographical proximity plays a significant role in promoting proximity, followed by technological proximity and social proximity. The moderating effect of technological proximity and geographical proximity is not significant, the moderating effect of technological proximity and social proximity is significantly positive, and the moderating effect of social proximity and geographical proximity is not significant.
Key wordsmulti-scale    urban innovation network    pattern    proximity   
收稿日期: 2019-04-03     
PACS: F129.9  
基金资助:国家自然科学基金面上项目(41771143);上海市哲学社会科学规划青年课题(2018EJL002);上海市"科技创新行动计划"软科学研究领域重点项目(19692107400)
作者简介: 马双(1990-),男,浙江江山人,助理研究员,博士,主要研究方向为区域发展与创新网络。E-mail:ms@sass.org.cn。
引用本文:   
马双, 曾刚. 多尺度视角下中国城市创新网络格局及邻近性机理分析[J]. 人文地理, 2020, 35(1): 95-103. MA Shuang, ZENG Gang. ANALYSIS OF CHINA'S URBAN INNOVATION NETWORK PATTERN AND ITS PROXIMITY MECHANISM FROM A MULTI-SCALE PERSPECTIVE. HUMAN GEOGRAPHY, 2020, 35(1): 95-103.
链接本文:  
http://rwdl.xisu.edu.cn/CN/10.13959/j.issn.1003-2398.2020.01.011      或     http://rwdl.xisu.edu.cn/CN/Y2020/V35/I1/95
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