Knowledge retention framework for facilitating critical knowledge loss in R&D organizations / Mohamad Safuan Sulaiman

Sulaiman, Mohamad Safuan (2020) Knowledge retention framework for facilitating critical knowledge loss in R&D organizations / Mohamad Safuan Sulaiman. PhD thesis, Universiti Teknologi MARA.

Abstract

In this decade onwards, some organizations have experienced, and some will be facing knowledge loss (KL) phenomena. The phenomena usually influenced by two main areas which include human resource and knowledge management (KM). Therefore, in this context, no exception that research and development (R&D) organizations would escape from these phenomena. As R&D becomes essential for innovations and important in many industries, it remains important for competitive advantage for organization’s survival. KL phenomena in R&D are crucial to innovations that have direct impact on organizational performance as well as national achievement. Furthermore, the phenomena also crucial to R&D in nuclear and medical industries due to the issues of safety and security. To retain the R&D knowledge, previous works in KL and knowledge retention (KR) have been reviewed. From the review, KR frameworks were identified as the ideal and comprehensive approach to be used at the organizational level. R&D organizations were defined as not the same as other organizations because of the unique differences in terms of people, ideas, funds, and culture. Due to that, this study attempts to improve existing KR frameworks that have overlooked the organizational differences between R&D and non-R&D in the issues of adaptability. Along with that, the study also has resolved problems of understanding critical R&D KL, unstructured design and lack of technological support in existing KR frameworks. The main objective of this study is to develop a new KR framework adaptable (useful and complete) to R&D organizations. This study consists of two main phases that include exploratory and confirmatory phases to achieve the main objective. In exploratory phase, the extensive literature survey was conducted to investigate the phenomena of critical KL in R&D organizations (Objective 1) and to identify KR components for R&D organizations (Objective 2). In this phase, a set of R&D criteria and a conceptual framework are acquired as a basis for developing a new KR framework adaptable to R&D organizations. In confirmatory phase, multiple case studies were conducted in three R&D organizations to propose the new KR framework (Objective 3). The framework is synthesized through a qualitative approach using thematic analysis acquired from interviews with experts from the R&D organizations. The thematic analysis was carried out using qualitative software tool called ATLAS.ti 8. Expert reviews from academic and R&D organizations were used for framework verification to confirm the proposed framework adaptable to R&D organizations. As a result, assessment, mapping and binding, acquire and transfer, critical knowledge store, organizational memory and utilization and integration are the proposed components of the new KR framework adaptable to R&D organizations. This research contributes a new KR framework called RnD-KRef for R&D organizations developed based on the six components. In addition, a R&D value chain and two IT tools called critical knowledge expert directory (CKED) and local expert identification and verification (LEIV) are part of the research contributions discovered during the conduct of the study. The findings of this research are significant to the field of knowledge management (KM), human resources (HR), operational (OM) and quality management (QM) as well as R&D organizations to minimize the effect of KL phenomena at the organizational level.

Metadata

Item Type: Thesis (PhD)
Creators:
Creators
Email / ID Num.
Sulaiman, Mohamad Safuan
2015296484
Contributors:
Contribution
Name
Email / ID Num.
Thesis advisor
Wan Adnan, Wan Adilah (Associate Prof. Dr.)
UNSPECIFIED
Thesis advisor
Nordin, Ariza (Dr.)
UNSPECIFIED
Thesis advisor
Md Noor, Nor Laila (Prof. Dr.)
UNSPECIFIED
Subjects: H Social Sciences > HD Industries. Land use. Labor > Management. Industrial Management > Electronic data processing. Information technology. Knowledge economy. Including artificial intelligence and knowledge management
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Programme: Doctor of Philosophy (Information Technology)
Keywords: Knowledge; retention framework; critical; knowledge loss; R&D; organizations
Date: December 2020
URI: https://ir.uitm.edu.my/id/eprint/59814
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