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Collaborative innovation network and knowledge transfer performance: A fsQCA approach

机译：协作创新网络和知识转移绩效：fsQCA方法

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Under the context of "open innovation", scholars increasingly consider collaborative innovation network as an effective framework to enable firms' knowledge transfer. This study examines four factors of collaborative innovation network that affect the level of knowledge transfer performance of firms, viz., network size, network heterogeneity, network tie-strength, and network centrality. Based on a survey to high-tech firms in China, this study uses fuzzy-set Qualitative ComparativeAnalysis (fsQCA) to explore the relationships between collaborative innovation network and knowledge transfer performance. This study supports the argument that different causal paths explain knowledge transfer performance of firms. The findings reveal that the presence of network size, network tie-strength, and network centrality determines the level of knowledge transfer performance. However, network heterogeneity does not show significant impact on the knowledge transfer performance. The findings also identify theoretical and practical implications of collaborative innovation network and knowledge transfer research. (C) 2016 Elsevier Inc All rights reserved.
机译：在“开放式创新”的背景下，学者们越来越多地将协作创新网络视为实现企业知识转移的有效框架。本研究考察了影响企业知识转移绩效水平的四个方面的协作创新网络，即网络规模，网络异质性，网络联系强度和网络中心性。基于对中国高科技企业的调查，本研究使用模糊集定性比较分析（fsQCA）来探索协作创新网络与知识转移绩效之间的关系。这项研究支持以下论点：不同的因果路径可以解释企业的知识转移绩效。研究结果表明，网络规模，网络联系强度和网络中心性的存在决定了知识转移绩效的水平。但是，网络异构性不会对知识转移性能产生显着影响。研究结果还确定了协作创新网络和知识转移研究的理论和实践意义。 （C）2016 Elsevier Inc保留所有权利。

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