An integrated multi-stage decision model for upstream supply chain disaster management readiness assessment

Abstract

Supply Chain Disaster Management (SCDM) is essential for mitigating disruptions, ensuring business continuity, and maintaining a competitive advantage. This study introduces a comprehensive decision model to assess disaster management readiness within the upstream supply chain. Through an extensive literature review grounded in Contingency Resource-Based View (CRBV) theory, fifteen initial readiness factors (RFs) are identified. The Fuzzy Delphi Method (FDM) then refines these factors to twelve, enhancing their relevance and applicability. Next, the Fuzzy Linguistic Preference Relation (FLinPreRa) method assesses the relative importance of each RF, providing a profound understanding of their individual and collective impact. Finally, Weight-Variance Analysis (WVA) evaluates the strengths and weaknesses of each RF, enabling targeted strategies for enhancing disaster readiness. A case study involving five automotive manufacturers in Thailand showcases the practical application of this decision model. The results indicate that this approach is an effective tool for assessing SCDM readiness, pinpointing critical areas for improvement, and guiding strategic investment. Beyond enhancing disaster preparedness, the model also strengthens overall supply chain resilience and responsiveness. Moreover, the framework can be easily adapted to other industries aiming to improve their SCDM readiness by tailoring it to address sector-specific challenges.