Factors Affecting Knowledge Transfer: A Systematic Literature Review and the Method to Assess Manufacturing Company’s Readiness for Knowledge Transfer Projects
Dubickis Mikus (),
Zarina Agnese () and
Putans Romans ()
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Dubickis Mikus: Riga Technical University, EKA University of Applied Sciences, Riga, Latvia
Zarina Agnese: Riga Technical University, Riga, Latvia
Putans Romans: Riga Stradins University, Riga, Latvia
Economics and Culture, 2024, vol. 21, issue 2, 1-33
Abstract:
In today’s business environment, with organizations enhancing performance, maintaining a competitive edge, and fostering innovation, the efficient transfer of knowledge plays an increasingly pivotal role. As industries recognize the importance of and strive for more and more productive knowledge transfer, understanding the factors affecting this process becomes imperative. Manufacturing is considered a strategic sector, and well-performing knowledge transfer is necessary for higher innovation and competitiveness. To increase knowledge transfer performance, companies must have the awareness, ability, and opportunity to identify the main aspects that need operational improvement. Studies based on systematic literature review and mapping impact factors have shown that knowledge transfer is hypothetically affected by a vast variety of factors, which creates challenges for companies in selecting and applying these factors. Therefore, the two research questions of this study are – RQ1: What are the relationships between the knowledge transfer-influencing factors identified in the literature analysis and the dependent variables? RQ2: What is the weight of the statistically significant factors identified in the empirical study? Research purpose. Based on the results of the systematic literature review and the complex quantitative analysis, the study aims to develop a method to assess readiness for knowledge transfer. Design / Methodology / Approach. To answer the stated research questions, the study compiles diverse research methods: a systematic review of the literature, factors’ mapping, the online survey of manufacturing companies, correlation analysis, and experts’ evaluation using the analytic hierarchy process (AHP) approach, thus ensuring data triangulation. Findings. The qualitative study of the literature review through iterative analysis and mapping resulted in 29 factors affecting knowledge transfer. Further, the empirical results led to 14 statistically significant factors in 3 groups ranked sequentially – individual factors (recipient’s absorptive capacity, recipient‘s experience, recipient’s confidence in their abilities, and recipient’s ability to focus on knowledge transfer), mentoring factors (senior management involvement and support, quick decision-making), and organizational factors (training, finances, internal policy, shared vision, organizational structure, staff turnover, HR quantity, and HR quality). The strongest correlations between the factors affecting knowledge transfer and the defined performance variables to measure knowledge transfer manifested in the group of the recipients’ individual factors. The most critical factor is the absorptive capacity of knowledge recipients, which managers should pay attention to. Originality / Value / Practical implications. As a result of the compound study, including a proposal of a new definition of knowledge transfer, a unified method with equations’ calculations to quantifiably assess a company’s readiness for knowledge transfer projects was developed, tested and validated. With the help of this study, the hypothetical factors affecting the transfer of knowledge in manufacturing have been identified, and the most important ones have been determined. The study also employed a novel approach of combining statistical analysis and AHP assessments to develop equations’ calculations to quantifiably assess the company’s readiness for knowledge transfer projects.
Keywords: Knowledge Transfer; Knowledge Sharing; Systematic literature review; Factors mapping; Knowledge Transfer Performance; Absorptive Capacity; Manufacturing; Mechanical Engineering; Metalworking (search for similar items in EconPapers)
JEL-codes: C38 D24 D80 L61 O14 O31 O32 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:ecocul:v:21:y:2024:i:2:p:1-33:n:1001
DOI: 10.2478/jec-2024-0016
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