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

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