| 长三角城市科研合作的邻近性与自组织性 |
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| 引用本文： | 戴靓,刘承良,王嵩,纪宇凡,丁子军.长三角城市科研合作的邻近性与自组织性[J].地理研究,2022,41(9):2499-2515. |
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| 作者姓名： | 戴靓 刘承良 王嵩 纪宇凡 丁子军 |
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| 作者单位： | 1.南京财经大学公共管理学院,南京 2100232.华东师范大学城市与区域科学学院,上海 2002413.华东师范大学全球创新与发展研究院,上海 2000624.东北大学工商管理学院,沈阳 110167 |
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| 基金项目： | 国家社会科学基金重大项目(21ZDA011) |
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| 摘 要： | 随着学者们对知识网络研究的深入,网络关联的影响因素和作用机制成为重要议题。本文基于2019—2020年Web of Science论文合作发表数据构建长三角城市科研合作网络,在空间和拓扑特征分析的基础上,采用加权指数随机图模型定量模拟了城市属性、城际关系和网络结构对合作网络的影响,揭示了科研合作中的邻近性和自组织性。研究发现：① 长三角城市科研合作网络是内外生动力共同作用的结果。就城市禀赋而言,高校数量、研发投入、人均GDP可促进城市的对外科研合作,其中高校数量的边际效应最大。② 就城际关系而言,组织邻近性的正向影响最强,同省城市合作的概率是跨省城市的3.157倍;认知邻近性每提高0.1,城市间的合作概率将是原先的1.981倍;而地理和社会邻近性的促进作用甚微,制度和文化邻近性影响为负,是择优偏好较强和方言壁垒有限的结果。③ 就网络结构而言,长三角城市科研合作具有自组织自演化性,局部星型结构和三角形结构对新合作关系的贡献为0.875和0.540,择优链接性强于传递闭合性。
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| 关 键 词： | 城市网络 科研合作 自组织 邻近性 加权指数随机图模型 长三角 |
| 收稿时间： | 2021-11-02 |
Proximity and self-organizing mechanisms underlying scientific collaboration of cities in the Yangtze River Delta |
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| DAI Liang,LIU Chengliang,WANG Song,JI Yufan,DING Zijun.Proximity and self-organizing mechanisms underlying scientific collaboration of cities in the Yangtze River Delta[J].Geographical Research,2022,41(9):2499-2515. |
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| Authors: | DAI Liang LIU Chengliang WANG Song JI Yufan DING Zijun |
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| Institution: | 1. School of Public Administration, Nanjing University of Finance and Economics, Nanjing 210023, China2. School of Urban and Regional Science, East China Normal University, Shanghai 200241, China3. Institute for Global Innovation and Development, East China Normal University, Shanghai 200062, China4. School of Business Administration, Northeastern University, Shenyang 110167, China |
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| Abstract: | With further research on intercity knowledge networks, the underlying influencing factors and mechanisms have become important issues in urban geography and regional studies. This study constructed an intercity scientific collaboration network of the Yangtze River Delta based on the co-publication data derived from the Web of Science during 2019-2020. After an exploratory analysis of spatial patterns and topological characteristics of the intercity scientific collaboration network, valued exponential random graph models were designed to quantitatively explore the effects of variables at the city, intercity-relation, and network-structure levels on the formation of the network, and then unravel the underlying self-organizing and proximity mechanisms. The results show that: (1) The intercity scientific collaboration network of the study area results from the joint effects of endogenous forces and exogenous forces. Exogenous forces include conventional urban knowledge endowments and multi-dimensional proximities between cities, while endogenous forces are self-organizing and self-evolving forces from local structures of the network per se which is relatively under-reported. In terms of urban endowment variables, cities with more universities, more R&D investment, and larger GDP per capita are more likely to develop scientific collaboration with other cities, among which the number of universities plays the most important role. (2) In terms of intercity relational variables, organizational proximity contributes most to the formation of the intercity scientific collaboration network. The probability of scientific collaboration between cities in the same province is 3.157 times the collaboration between cities in different provinces. For every 0.1 unit increase of cognitive proximity between cities, the probability of scientific collaboration between them would be 1.981 times the previous probability. Geographical proximity and social proximity contribute little to facilitating the intercity scientific collaboration. In contrast, the impacts of institutional proximity and cultural proximity are negative due to the stronger effects of preferential attachment and weaker barriers of regional dialects. (3) In terms of network structural variables, the intercity scientific collaboration network presents significant self-organizing and self-evolving properties. The contribution of local structures, i.e., star configuration and triangle configuration, to the formation of new intercity scientific collaboration is respectively 0.875 and 0.540, suggesting that the preferential attachment effect is stronger than the triadic closure effect. |
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| Keywords: | urban network scientific collaboration self-organization proximity valued exponential random graph models Yangtze River Delta |
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