Measuring knowledge diffusion efficiency in R&D networks. Issue 2 (3rd April 2018)

• Record Type: Journal Article
• Authors: Jiafu, Su; Yu, Yang; Tao, Yang
• Is Part Of: Knowledge management research & practice. Volume 16:Issue 2(2018)
• Page Start: 208
• Page End: 219
• Publication Date: 2018-04-03
• Subjects: R&D network -- knowledge diffusion -- weighted network -- efficiency of knowledge diffusion -- member importance; Organizational learning -- Periodicals; Intellectual capital -- Periodicals; Knowledge management -- Periodicals; 658.403
• DOI: 10.1080/14778238.2018.1435186
• Languages: English
• ISSNs: 1477-8238

Abstract

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.