Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/274910 
Year of Publication: 
2022
Citation: 
[Journal:] Journal of Risk and Financial Management [ISSN:] 1911-8074 [Volume:] 15 [Issue:] 9 [Article No.:] 389 [Year:] 2022 [Pages:] 1-17
Publisher: 
MDPI, Basel
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.
Subjects: 
case study
collaborative agreements
driver
interpretive structural model (ISM)
knowledge leakage
MICMAC analysis
small firm
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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