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Multi-network embeddedness and innovation performance of R&D employees

Author

Listed:
  • Taiye Luo

    (South China University of Technology)

  • Zhengang Zhang

    (South China University of Technology
    Guangzhou Digital Innovation Research Center)

Abstract

Taking the perspective of multi-network embeddedness, this paper constructs the collaboration network of R&D organizations, the collaboration network and knowledge network of R&D employees based on the patent data of 879 R&D employees from 224 R&D organizations, and analyses factors that have significant impacts on R&D employees’ innovation performance. The results show that R&D employees’ knowledge combinatorial potential and knowledge diversity have significant positive impacts on their innovation performance. R&D employees’ degree centralities in the collaboration network mediate the impacts of their knowledge combinatorial potential and knowledge diversity on innovation performance. The degree centralities of R&D organizations moderate the impacts of R&D employees’ degree centralities on innovation performance.

Suggested Citation

  • Taiye Luo & Zhengang Zhang, 2021. "Multi-network embeddedness and innovation performance of R&D employees," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(9), pages 8091-8107, September.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:9:d:10.1007_s11192-021-04106-7
    DOI: 10.1007/s11192-021-04106-7
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    References listed on IDEAS

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