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Measuring knowledge diffusion efficiency in R&D networks

Author

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  • Su Jiafu
  • Yang Yu
  • Yang Tao

Abstract

This paper investigates the issue of measuring knowledge diffusion efficiency in R&D network based on the weighted network method. For the reality of R&D networks, we integrate the node and tie weights to build a weighted R&D network model. On the basis of the weighted R&D network, the multiple factors of knowledge diffusion efficiency are analyzed, and then a novel measurement method is proposed by comprehensively embodying these factors. Furthermore, an extended application of the measurement method is proposed to identify the important members of R&D network. An example of weighted Braess network and a real-world case are employed to illustrate the applicability and effectiveness of the proposed method. Results show that the proposed measurement method can more efficiently and accurately measure the knowledge diffusion efficiency of R&D networks than the traditional methods, and its application can effectively identify the important members with great influence on knowledge diffusion.

Suggested Citation

  • Su Jiafu & Yang Yu & Yang Tao, 2018. "Measuring knowledge diffusion efficiency in R&D networks," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 16(2), pages 208-219, April.
  • Handle: RePEc:taf:tkmrxx:v:16:y:2018:i:2:p:208-219
    DOI: 10.1080/14778238.2018.1435186
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    Cited by:

    1. Kyoo-Man Ha, 2024. "International R&D diffusion in disaster management: a systematic review," Management Review Quarterly, Springer, vol. 74(1), pages 289-302, February.
    2. Chengzhi Niu & Hong He & Yunfei Qi & Shoujie Wang, 2024. "Can Participation in the Green Standard-Setting Process Promote Green Innovation in Heavy-Pollution Firms? Evidence from China," Sustainability, MDPI, vol. 16(14), pages 1-29, July.

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