The Process of University-to-Industry Knowledge Transfer And Influential Factors
Wang Li-ping
Abstract
Wang Li-ping
Abstract
As the firms become increasingly aware that in-house R&D facilities and resources are no longer capable of being the sole source of the research needs, the cooperation between universities and industries are very popular nearly all over the world. This paper focuses on knowledge transfer process in the context of university-industry cooperation. Through literature research and theoretical analysis, this paper establishes five-stage knowledge transfer process model: searching stage, matching stage, learning stage, adaptation stage and integration stage. Besides that, puts communication stage across the whole knowledge transfer process. Basing on the model, this paper suggests the influential factors, which affect university-to-industry effective knowledge transfer. The influential factors are university knowledge factor, firm factors, interactive factor, knowledge characteristics and context distance. Finally, we suggest the further research direction and methods
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As the firms become increasingly aware that in-house R&D facilities and resources are no longer capable of being the sole source of the research needs, the cooperation between universities and industries are very popular nearly all over the world. This paper focuses on knowledge transfer process in the context of university-industry cooperation. Through literature research and theoretical analysis, this paper establishes five-stage knowledge transfer process model: searching stage, matching stage, learning stage, adaptation stage and integration stage. Besides that, puts communication stage across the whole knowledge transfer process. Basing on the model, this paper suggests the influential factors, which affect university-to-industry effective knowledge transfer. The influential factors are university knowledge factor, firm factors, interactive factor, knowledge characteristics and context distance. Finally, we suggest the further research direction and methods
Key concepts: Knowledge transfer, Matching (statistics), Knowledge management, Context (archaeology), Process (computing), Computer science, Adaptation (eye), Stage (stratigraphy)