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基于创新联系的城市网络特征及影响因素研究--以粤港澳地区为例 被引量:21

Urban Network on Innovation Connection: Case Study of Guangdong-Hong Kong-Macao Area
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摘要 依托世界知识产权组织(WIPO)中专利合作协定(PCT)数据,构建粤港澳地区城市创新联系网络,探讨网络特征及影响因素。研究发现:(1)粤港澳地区创新联系逐渐增强,但联系紧密度与硅谷相比仍存在差距;(2)粤港澳地区创新联系网络呈核心-边缘结构,中心度呈圈层式向外递减;(3)核心圈层网络发育程度较高,边缘城市倾向与核心城市开展创新合作;(4)将节点影响力细化为对外交往能力和中介能力,各核心城市的表现存在差异;(5)地理邻近性、技术邻近性、经济邻近性、网络邻近性、科技邻近性均对城市创新联系产生显著影响。 Based on the data of Patent Cooperation Treaty(PCT) in World Knowledge Patent Organization(WIPO), this study form an innovation connection network within Guangdong-Hong Kong-Macao Area to analyze the characteristics of network and explore the influencing factors. The main findings include:(1) In recent years, urban innovation linkages became closely. But the degree of the closed-connection was not as good as that in Silicon Valley;(2) The innovation connection network has an obvious core-periphery structure, and the degree centrality declines as the city far away from the core circle of innovation connection.(3) The key circle is highly developed. The periphery cities tend to develop innovative cooperation relationship with core cities rather than with the other periphery cities.(4) By defining the influence capacity of innovation connection as external linkage capabilities and intermedia capabilities, the core cities of the network have different performances in these two capabilities.(5) Geographical proximity, technological proximity, economic proximity, network proximity and technological proximity all have a significant impact on the urban innovation network of this area.
作者 钟韵 叶艺华 魏也华 Zhong Yun;Ye Yihua;Wei Yehua Dennis(College of Economics,Jinan University,Guangzhou 510632,China;Department of Geography,University of Utah,Salt Lake City 84112,United States)
出处 《科技管理研究》 CSSCI 北大核心 2020年第7期1-9,共9页 Science and Technology Management Research
基金 国家自然科学基金项目“城市等级与生产性服务业发展的互动关系研究”(41371174) “改革开放以来中国城市全球化:过程、格局、动力与空间”(41130747) 中央高校基本科研专项“粤港澳大湾区协同发展的理论与实证研究:兼与西方湾区发展模式对比”(19JNYH09)。
关键词 城市网络 创新联系 空间结构特征 影响因素 社会网络分析 urban network innovation connection characteristics of spatial structure influence factors social network analysis
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