Simulation of Knowledge Transfer Process Model Between Universities: A Perspective of Cluster Innovation Network. (2nd December 2018)

• Record Type: Journal Article
• Authors: Wei, Fang; Limin, Xiao
• Other Names: Musial Katarzyna Guest Editor.
• Is Part Of: Complexity. Volume 2018(2018)
• Publication Date: 2018-12-02
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2018/5983531
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Combined with the basic properties of the cluster innovation network, with the cluster innovation network, which can be composed of different universities that have knowledge potential difference as the research object, the knowledge transfer process is divided into four stages: knowledge externalization, knowledge sharing, knowledge innovation, and knowledge internalization, and the article constructs a knowledge transfer process model through introducing explicit knowledge and tacit knowledge conversion effect mechanism. According to the theory of complex adaptive system, the principle of network connection oriented the knowledge potential difference and the characteristic of the explicit knowledge and tacit knowledge within universities. We research the knowledge transfer process of universities using the system simulation method and focus on the evolution mechanism of the cluster innovation network's knowledge level at knowledge externalization and knowledge sharing stage. It further reveals the basic topology structure and dynamic evolution law of universities cluster innovation network. We find that both knowledge externalization efficiency and knowledge learning ability have positive correlation with the general knowledge level of network. The evident small-world network characteristic emerges during the dynamic evolution of universities cluster innovation network. Meanwhile, there exists a coupling evolution between the knowledge level of universities and the topology structure of the cluster innovation network.