نوع مقاله : پژوهشی
تازه های تحقیق
عنوان مقاله English
نویسندگان English
Effective risk management in power plant maintenance and repair (M&R) is critical for ensuring operational reliability and minimizing unexpected downtime. This study designs and validates an optimal risk management model for power plant M&R by integrating fuzzy logic with an exploratory sequential mixed-methods approach. In the qualitative phase, semi-structured interviews (17 conducted; theoretical saturation confirmed from the 14th interview onward) with domain experts—analyzed via grounded theory (Strauss and Corbin) in MAXQDA yielded 122 initial codes and 41 key components organized into a five-category paradigm model (causal conditions, contextual conditions, intervening conditions, strategies, and consequences). In the quantitative phase, a researcher-designed questionnaire was administered to a stratified random sample of n=226 power plant M&R specialists. Fuzzy Delphi confirmed expert consensus above the 0.70 threshold for all 41 components in a single round (defuzzified values 0.84–0.90). Partial Least Squares Structural Equation Modeling (PLS-SEM) validated the conceptual model: all path coefficients were statistically significant (t > 1.96), R² = 0.663 for the core Risk Management construct, and the overall model fit index (GOF = 0.525) confirmed strong fit. The proposed model which integrates technical, human, organizational, and environmental dimensions provides a validated, locally grounded framework for power plant risk governance in Iran.
کلیدواژهها English
Copyright © Mehdi Baghandeh, Arshad Farahmandian, Firouzeh Hajialiakbari, Mohammad Hasan Abdolahi
License
This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.
