Designing an Analytical Model for Assessing Supply Chain Resilience to different Types of Risks: Case Study of Iran Petro-chemical Industries

The study aims to develop and validate an analytical model for assessing the resilience of supply chains in the face of system-wide and individual tier risks. To accomplish this, a multi-method research approach is employed, involving the utilization of data envelopment analysis (DEA) and fuzzy set theory. Specif-ically, a fuzzy network DEA model is introduced to evaluate risks across entire supply chains and their individual tiers. This model is then put to the test through a survey involving 130 respondents from select petrochemical compa-nies in Iran. The survey results reveal significant disparities in resilience ratings between the overarching petrochemical supply chains and their specific tiers. The research findings emphasize that the resilience of a system may not neces-sarily reflect the resilience of its individual tiers. Conversely, high efficiency scores within supply chain tiers have only a limited impact on the overall resili-ence of the supply chain. The analytical model proposed in this study facilitates the evaluation of supply chain flexibility at various levels while addressing a broad spectrum of supply chain risks in the upstream, downstream, and inter-mediary processes.