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国际合作网络对科学会聚的影响分析
引用本文:毛荐其,荣雪云,刘娜.国际合作网络对科学会聚的影响分析[J].科技管理研究,2019,39(6):255-261.
作者姓名:毛荐其  荣雪云  刘娜
作者单位:山东工商学院工商管理学院,山东烟台,264005;山东工商学院工商管理学院,山东烟台,264005;山东工商学院工商管理学院,山东烟台,264005
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:构建国际合作网络结构通过知识扩散影响科学会聚的理论模型,并运用社会网络分析法和科学计量分析法进行定量研究。在合作网络结构层面,考虑多层网络结构对知识扩散的影响,即个体网络的中心性和整体网络的密度。以全球各国1992—2016年间在物理储能、化学储能、电磁储能3大领域发表的SCI-E论文数据为样本,通过Spearman相关分析对理论模型的相关性进行验证。结果表明,在国际合作网络中,高中心性的国家更易成为新知识的早期采纳者,从而促进知识扩散;整体网络密度与知识扩散显著正相关关系;知识扩散促进科学会聚的形成;储能领域的科学研究相对集中,形成以"化学""材料科学""能源燃料""物理学"为中心的学科共现网络。

关 键 词:中心性  网络密度  知识扩散  科学会聚
收稿时间:2018/5/2 0:00:00
修稿时间:2018/6/8 0:00:00

Analysis of the impact of international collaborative networks on scientific convergence
Mao Jianqi,Rong Xueyun,Liu Na.Analysis of the impact of international collaborative networks on scientific convergence[J].Science and Technology Management Research,2019,39(6):255-261.
Authors:Mao Jianqi  Rong Xueyun  Liu Na
Institution:(School of Business Administration,Shandong Technology and Business University,Yantai 264005,China)
Abstract:The theoretical model is built that how collaborative network structure impacts scientific convergence through knowledge diffusion, and quantitative investigation in this paper with the methodology of social network analysis and scientific measurement analysis. In the network structure level, this paper considers the impacts of multi-layer network structure on knowledge diffusion, which is the centrality of the ego-network and the density of the entire-network. To verify the correlation of model, by Spearman correlation analysis based on articles of physical, chemical and electromagnetic energy storage extracted from SCI-E database between 1992 and 2016. The results show that countries having higher centrality in international collaborative networks are more likely to be early adopters of new knowledge and promoting the diffusion of knowledge; entire-network density has a significant positive correlation on knowledge diffusion; knowledge diffusion has a positive effect on the formation of scientific convergence. The empirical study indicates that the scientific research in energy storage is relatively-concentrated and forming a scientific co-occurrence network based on chemistry, material science, energy fuel and physics.
Keywords:centrality  network density  knowledge diffusion  science convergence
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