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Modeling the causal relationships between influencing factors in the circular supply chain implementation using fuzzy cognitive mapping and the fuzzy best-worst method (Case study: Steel and Iron Industries)
Mohammad Shanejani *1 , Roxana Fekri2
1- Department of industrial engineering, Payam Noor University, Tehran, Iran , Mshanjani2@gmail.com
2- Department of industrial engineering, Payam Noor University, Tehran, Iran
Abstract:   (54 Views)
In a circular economy, the value of materials and products is preserved to the maximum extent possible to minimize waste generation. This approach prioritizes reducing resource consumption, repurposing products at the end of their lifecycle, promoting reuse, and enhancing value creation. This concept has recently garnered substantial attention in supply chain (SC) research. This study investigates and models the factors that influence the implementation of circular supply chains (CSCs). The relevant factors were initially identified through a comprehensive literature review and expert consultation. Data on the significance of these factors were collected through a questionnaire administered to 107 iron and steel industry professionals. Statistical tests were subsequently conducted to identify less significant factors. The remaining factors were modeled and analyzed using a fuzzy cognitive map (FCM). These factors were categorized into five major groups: economic, qualitative, environmental, cultural, and service level. The best–worst method (BWM) determines their relative importance in CSC implementation. The extended BWM under type-2 fuzzy sets verify the consistency of the proposed approach. This research identified the most significant factors influencing the implementation of a circular supply chain as the using natural resources, energy consumption, willingness for changes in senior management, quality improvement, and financial strength of SC members. 
Keywords: Circular supply chain, Fuzzy cognitive mapping, Best-worst method, Iron and steel industry.
Full-Text [PDF 1018 kb]   (15 Downloads)    
Type of Study: Research | Subject: Logistic & Apply Chain
Received: 2025/06/3 | Accepted: 2026/11/3
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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.