Presenting an Effective Motivational Model on the Knowledge Acquisition Process Using Fuzzy Best-Worst Method (FBWM)

Mostafa Jafari, Mohammadreza Zahedi and Shayan Naghdi Khanachah ()
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Mostafa Jafari: Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
Mohammadreza Zahedi: ��Department of Industrial Engineering, Malek Ashtar University of Technology, Tehran, Iran
Shayan Naghdi Khanachah: Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran

Journal of Information & Knowledge Management (JIKM), 2024, vol. 23, issue 01, 1-18

Abstract: In the knowledge economy, knowledge-based organisations, in particular, open a special account for their employees. Knowledge acquisition is important for organisations, because it enables them to improve their skills and creates value, credibility and competitive advantage. This research has been made to identify the motivational factors effective for knowledge acquisition and prioritise these factors, as well as providing a framework for managers to enable knowledge sharing from knowledge workers and increase their desire to overcome current problems. The organisation has been paid. The statistical population of the research is 300 managers and experts in the automotive industry, and in this research, the opinions of 20 experts have been used to analyse the results. The results were analysed using the fuzzy technique to answer the research questions. The calculations obtained by applying the proposed method show that among the six factors affecting knowledge acquisition, Behavioural factors, with a weight of 0.296, have the most impact on knowledge acquisition compared to other factors. After that, the factor of Information Technology in the organisation, with a weight of 0.17, is in second place concerning the level of influence on knowledge acquisition. Also, the Organisational Learning Criteria are ranked third with a weight of 0.165. And the factors of Organisational Culture, Reward and Structure are placed in the next priorities with weights of 0.153, 0.094 and 0.121, respectively.

Keywords: Knowledge acquisition; knowledge management; motivation; fuzzy (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1142/S0219649223500612

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