Examining the evolving structures of intercity knowledge networks: the case of scientific collaboration in China

IF 2.9 3区 工程技术 Q2 ENVIRONMENTAL STUDIES
Liang Dai, B. Derudder, Zhan Cao, Yufan Ji
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引用次数: 4

Abstract

ABSTRACT Drawing on data on scientific co-publications derived from the Web of Science for the periods 2002–2006 and 2012–2016, we construct and analyse a key element of China's intercity knowledge networks (CIKNs): scientific collaboration networks. Employing network-analytical and exponential random graph modelling techniques, we examine the evolving structures and driving mechanisms underlying these CIKNs. Our results show that the density of the CIKNs has significantly increased over time. CIKN flows are dense in the Southeastern but sparse in the Northwestern part of China, with the Hu Line acting as a clearly visible border. As the dominant knowledge centre, Beijing is involved in scientific collaboration networks throughout the country, with the diamond-shaped structure anchored by Beijing-Shanghai-Guangzhou-Chengdu becoming evident. We find that preferential attachment and transitivity are significant endogenous processes driving scientific collaboration, while a city's administrative level and R&D investment are the strongest exogenous factors. The impact of GDP and geographical proximity is limited, with institutional proximity being the most sizable of the well-known suite of proximity effects.
考察城市间知识网络的演变结构——以中国的科学合作为例
利用2002-2006年和2012-2016年科学网络的科学合作出版物数据,构建并分析了中国城际知识网络(CIKNs)的关键要素:科学协作网络。采用网络分析和指数随机图建模技术,我们研究了这些cikn的演变结构和驱动机制。我们的研究结果表明,随着时间的推移,cikn的密度显著增加。中国东南地区的环流密集,西北地区的环流稀疏,胡线是一个清晰可见的边界。北京作为主要的知识中心,参与了全国的科学合作网络,以北京-上海-广州-成都为中心的菱形结构越来越明显。研究发现,优先依恋和传递性是推动科技合作的重要内生因素,而城市行政水平和研发投入是最强大的外生因素。GDP和地理邻近性的影响是有限的,制度邻近性是众所周知的邻近效应中规模最大的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
5.90
自引率
6.90%
发文量
36
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