Enhancing Resilience and Sustainability in Humanitarian Procurement: A Supplier Evaluation Framework Using the Best-Worst Method

Ei Myat Kay Khine , Huay Ling Tay , Hui Shan Loh

International Journal of Disaster Risk Science ›› 2026, Vol. 17 ›› Issue (4) : 902 -917.

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International Journal of Disaster Risk Science ›› 2026, Vol. 17 ›› Issue (4) :902 -917. DOI: 10.1007/s13753-026-00757-3
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Enhancing Resilience and Sustainability in Humanitarian Procurement: A Supplier Evaluation Framework Using the Best-Worst Method
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Abstract

With the growing complexity and frequency of humanitarian crises globally, incorporating resilience and sustainability criteria into the supply chains of humanitarian organizations has become essential. This study aimed to enhance the resilience and sustainability of the humanitarian supply chain by integrating economic, resilience, environmental, and social aspects. The Delphi method was employed as the research method, and the best-worst method (BWM) was applied to compute the context-specific supplier evaluation criterion weights. As an outcome of this research, the current and desirable supplier evaluation criteria were identified, and a holistic supplier evaluation framework was developed for humanitarian organizations (HOs). The study revealed that the integration of environmental criteria in supplier evaluation is still in its emerging stage. Moreover, increasing stakeholder engagement and securing donor support are critical for achieving resilience and sustainability in humanitarian procurement. This study provides an easy step-by-step supplier evaluation process that can be applied by HOs to enhance sustainable and resilient humanitarian procurement.

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Best-worst method / Decision support systems / Humanitarian procurement / MCDM / Supplier evaluation criteria / Supply chain resilience and sustainability

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Ei Myat Kay Khine, Huay Ling Tay, Hui Shan Loh. Enhancing Resilience and Sustainability in Humanitarian Procurement: A Supplier Evaluation Framework Using the Best-Worst Method. International Journal of Disaster Risk Science, 2026, 17 (4) : 902-917 DOI:10.1007/s13753-026-00757-3

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