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Designing a model for analyzing resilience scenarios using structural equation modeling in the sesame industry supply chain of Yazd province
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A. A. Vakili Ahmad Abadi   , A. Sadeghian , M. T. Honari , M. Rabbani |
| Department of Industrial Management, Ya. C, Islamic Azad University, Yazd, Iran |
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Abstract: (33 Views) |
| This study aims to design and evaluate resilience scenarios for the sesame industry supply chain in Yazd Province, focusing on risks arising from economic changes and market volatility, in order to strengthen the resilience and sustainability of this strategic product’s supply chain. First, 24 criteria influencing supply chain resilience were identified. Using the fuzzy Delphi method, 12 final criteria were selected. Structural Equation Modeling (SEM) was then employed to analyze the relationships among the resilience factors. Several tests, including coefficient of determination, predictive relevance, and effect size, were used to assess model quality. The analysis is based on expert evaluations of resilience criteria in the sesame supply chain of Yazd Province, collected and refined through fuzzy Delphi and subsequently modeled using SEM. The results show that economic, technical, and organizational factors are prioritized, respectively, in influencing supply chain resilience. The tests confirm strong and significant relationships among the variables, indicating the robustness and predictive power of the proposed model. By integrating fuzzy Delphi for criteria selection with SEM for causal analysis, this study provides a structured framework for assessing and improving resilience in an agricultural supply chain. It offers practical scenarios that enable managers to identify strengths and weaknesses under different simulated conditions, adopt effective strategies, and enhance resilience through valid, up-to-date data and stakeholder collaboration. The proposed approach can be applied as a model for similar industries in Yazd Province and other regions. |
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| Keywords: Resilience, Supply Chain, Scenario Design, Prioritization. |
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Type of Study: Applicable |
Subject:
Special
Received: 2025/09/4 | Accepted: 2025/12/1 | Published: 2026/01/11
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