Inter-organizational knowledge transfer: The perspective of knowledge governance

Shih Chieh Fang, Chen Wei Yang, Wen Yen Hsu

Research output: Contribution to journalReview articlepeer-review

66 Citations (Scopus)


Purpose: The main purposes of this study are to develop a knowledge governance mechanism-fit-barrier matrix mode to resolve transfer problems resulting from knowledge characteristics and to clarify the relationship among knowledge characteristics, barriers of knowledge transfer, and effective knowledge transfer in inter-organizational contexts. Design/methodology/approach: The vast literature on knowledge transfer in inter-organizational context has been reviewed. Moreover, to develop a theoretical framework, the authors developed a set of arguments based on literature pertaining to the knowledge-based view of knowledge characteristics and barriers and the response of network to inter-organizational knowledge transfer. Findings: Knowledge-based view of knowledge characteristics and barriers and knowledge governance may provide a new understanding for network organizations seeking effective knowledge transfer strategies in inter-organizational context. Research limitations/implications: The main contribution to organizational theory is extending information-processing theory to form a new strategic model for inter-organizational knowledge transfer. Practical implications: The fit model of governance mechanisms may help managers to make effective strategies for inter-organizational knowledge transfer. Originality/value: Theoretically, this paper extends Information Processing Theory to inter-organizational relationships research. The developed model here also helps to explain the importance of cognitive dimensions for successful inter-organizational knowledge transfer. In KM practice, the proposed well-developed strategic models may help managers to link inter-organizational knowledge transfer processes to business strategy, and validate of the way to convert the goal of making their network organizations more intelligent into a strategic action.

Original languageEnglish
Pages (from-to)943-957
Number of pages15
JournalJournal of Knowledge Management
Issue number6
Publication statusPublished - 2013

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management of Technology and Innovation


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