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The evolution of a collaboration network and its impact on innovation performance under the background of government-funded support: an empirical study in the Chinese wind power sector

机译:协作网络的演变及其对政府资助支持背景下的创新绩效的影响:中国风电业的实证研究

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摘要

To accelerate the transformation and application of basic research results, the Chinese government has repeatedly mentioned in a government work report that it is necessary to support research and innovation collaborations between knowledge research institutions and enterprises. However, few studies have focused on the evolution of collaborations between these organizations and the impact of collaborations on innovation performance (IP) in the field of renewable energy under the background of government-funded support (GFS). Based on scientific publications, we construct a GFS collaboration network in the wind power field to investigate the evolution of network structure characteristics, attribute proximity variables, and applied research collaboration (ARC), and we study the impact of network evolution on the IP of actors. The results show that the focal actor of the collaboration network prefers to engage in ARC with partners who are familiar and have the same knowledge base in different provinces. This collaboration tendency will reduce geographical proximity and increase the direct ties, indirect ties, technological proximity, and ARC of the ego network. Among them, direct ties have an inverted U-shaped effect on IP, geographical proximity has a significantly negative impact on IP, and the remaining variables have positive impacts on IP. Taken together, when the direct ties is within a certain range, these collaboration tendencies in a GFS collaboration network positively affect the IP of research institutions and enterprises.
机译:为了加快基础研究成果的转化和应用,中国政府在一份政府工作报告中多次提到,有必要支持知识研究机构和企业之间的研究和创新合作。然而,在政府资助支持(GFS)的背景下,很少有研究关注这些组织之间合作的演变以及合作对可再生能源领域创新绩效(IP)的影响。基于科学出版物,我们构建了风力发电领域的GFS协作网络,以研究网络结构特征、属性邻近变量和应用研究协作(ARC)的演化,并研究了网络演化对参与者IP的影响。结果表明,合作网络的主要参与者更喜欢与熟悉的、在不同省份拥有相同知识基础的合作伙伴进行ARC。这种合作趋势将减少地理上的接近,并增加自我网络的直接联系、间接联系、技术接近和弧。其中,直接关系对知识产权具有倒U型效应,地理邻近性对知识产权具有显著的负向影响,其余变量对知识产权具有正向影响。综上所述,当直接关系在一定范围内时,GFS协作网络中的这些协作倾向会对研究机构和企业的IP产生积极影响。

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