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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 12, 2021.
Abstract: Implementing a knowledge retention (KR) strategy is crucial to overcome the loss of expert knowledge due to employee turnover and retirement. The knowledge loss phenomenon caused organizations to face enormous risks which affect performance. KR frameworks and models are made available beyond research and development (R&D) organizations, to address knowledge retention strategies for administrative, operational, and manufacturing organizations. For research-intensive portfolios within R&D organizations, using the available KR frameworks requires fitting. The difficulty to address knowledge loss due to the uniqueness of the R&D organization’s knowledge artifacts requires an extended KR framework. Before designing the extended KR framework, it is crucial to determine the framework’s additional criteria. The paper reports the use of value chain mapping to determine the extended criteria of the KR framework fit for R&D organizations. The value chain mapping method identifies the knowledge activities in the R&D using Porter Value Chain (PVC) as the reference model. The output is a Knowledge Chain Model (KCM) that defines the critical points of knowledge loss in the R&D value chain. These critical points are project-based expert critical knowledge focus, project-based tacit knowledge transfer, and project-based knowledge repository which are nominated extended criteria of the KR Framework fit for R&D organizations.
Mohamad Safuan Bin Sulaiman, Ariza Nordin, Nor Laila Md Noor and Wan Adilah Wan Adnan, “Use of Value Chain Mapping to Determine R&D Domain Knowledge Retention Framework Extended Criteria” International Journal of Advanced Computer Science and Applications(IJACSA), 12(12), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0121263
@article{Sulaiman2021,
title = {Use of Value Chain Mapping to Determine R&D Domain Knowledge Retention Framework Extended Criteria},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0121263},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0121263},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {12},
author = {Mohamad Safuan Bin Sulaiman and Ariza Nordin and Nor Laila Md Noor and Wan Adilah Wan Adnan}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.