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Analysing Drivers of Knowledge Leakage in Collaborative Agreements: A Magnetic Processing Case Firm

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  • Samuel Foli

    (Department of Business Administration, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia)

  • Susanne Durst

    (Department of Business Administration, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia)

Abstract

Due to the embeddedness of organisations in networks, collaborations, and business relationships, knowledge leakage has become a common concern. In this regard, this paper aims to investigate drivers of knowledge leakage in collaborative agreements using an integrated ISM-MICMAC model. Based on insights from employees including the CEO of a magnetic processing firm, we validate the proposed model. The findings of our study reveal nine key drivers that influence knowledge leakage in collaborative agreements. In terms of level of influence, incomplete contract is the most influential driver, followed by sub-contracting activities. Last, the nine drivers are classified into two main clusters: independency cluster—weak dependence power with high driving power—and linkage cluster—strong dependence and driving power.

Suggested Citation

  • Samuel Foli & Susanne Durst, 2022. "Analysing Drivers of Knowledge Leakage in Collaborative Agreements: A Magnetic Processing Case Firm," JRFM, MDPI, vol. 15(9), pages 1-17, September.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:9:p:389-:d:904307
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    References listed on IDEAS

    as
    1. Joanne Oxley & Tetsuo Wada, 2009. "Alliance Structure and the Scope of Knowledge Transfer: Evidence from U.S.-Japan Agreements," Management Science, INFORMS, vol. 55(4), pages 635-649, April.
    2. Papadas, Karolos-Konstantinos & Avlonitis, George J. & Carrigan, Marylyn & Piha, Lamprini, 2019. "The interplay of strategic and internal green marketing orientation on competitive advantage," Journal of Business Research, Elsevier, vol. 104(C), pages 632-643.
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