Integrating supply chains for emergencies and ongoing operations in UNHCR

TLDR

Humanitarian organizations typically locate warehouses based on experience rather than decision‑support tools, run separate supply chains for emergency and ongoing operations, and have not yet incorporated critical contextual factors such as accessibility, co‑location, security, and human resources into network optimization models. The study proposes a warehouse location model for joint prepositioning that incorporates political and security factors, informed by literature reviews and a UNHCR case study. The authors develop a joint prepositioning warehouse location model that integrates political and security situation factors, drawing on humanitarian network design literature and a detailed UNHCR case study. The model shows that incorporating contextual factors significantly influences network configuration, and that joint prepositioning expands the global warehouse network while reducing costs and response time.

Abstract

Abstract Humanitarian organizations (HOs) often base their warehouse locations on individuals' experience and knowledge rather than on decision‐support tools. Many HOs run separate supply chains for emergency response and ongoing operations. Based on reviews of humanitarian network design literature combined with an in‐depth case study of United Nations High Commissioner for Refugees (UNHCR), this paper presents a warehouse location model for joint prepositioning that incorporates political and security situation factors. Although accessibility, co‐location, security, and human resources are crucial to the practice of humanitarian operations management, such contextual factors have not been included in existing network optimization models before. We found that when quantified, and modeled, such factors are important determinants of network configuration. In addition, our results suggest that joint prepositioning for emergency response and ongoing operations allows for expansion of the global warehouse network, and reducing cost and response time.