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Dehghani M R, Sadeghian R, Jafari Eskandari M. Evaluating Knowledge Sharing Barriers Using a Robust Group BWM Based on Goal Programming in a Network Structure (Case Study: Fars Combined Cycle Power Plant). jor 2025; 22 (4)
URL: http://jamlu.liau.ac.ir/article-1-2335-en.html

Evaluating Knowledge Sharing Barriers Using a Robust Group BWM Based on Goal Programming in a Network Structure (Case Study: Fars Combined Cycle Power Plant)

M. R. Dehghani ^*

, R. Sadeghian

, M. Jafari Eskandari

Department of Industrial Engineering, Payame Noor University, Tehran, Iran , m.r.dehghani@student.pnu.ac.ir

Abstract: (10 Views)

Knowledge sharing is a strategic process for enhancing organizational competitive advantage; however, its effective implementation faces multiple barriers. The nature and intensity of these barriers vary depending on each organization’s structure and culture, making their identification and assessment a strategic necessity. Since there are interdependencies among these barriers, adopting a network-based structure for their analysis is essential. The Best–Worst Method (BWM) is one of the efficient approaches in Multi-Attribute Decision-Making (MADM). In this study, a novel group decision-making algorithm based on a robust goal programming BWM within a network structure is proposed to evaluate and prioritize knowledge-sharing barriers in the Fars Combined Cycle Power Plant. In the proposed model, pairwise comparison data were defined as intervals to capture uncertainty in expert judgments. The results indicated that strategic, cultural, individual, and technological barriers have the highest impact on knowledge sharing, with respective weights of 0.4002, 0.3599, 0.1600, and 0.0800. The use of an interval-data consistency mechanism enhanced the precision and stability of the results. The proposed algorithm provides an effective tool for evaluation and decision-making under real-world uncertainty.

Keywords: Knowledge Sharing, Robust Group Best–Worst Method (BWM), Goal Programming, Network Structure, Robust Optimization, Uncertainty, Thermal Power Plant.

Type of Study: Research | Subject: Special
Received: 2025/06/24 | Accepted: 2025/11/11 | Published: 2025/12/22

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