International Journal of Industrial Engineering & Production Research
Iran University of Science & Technology
Tue, Aug 18, 2026
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Volume 37, Issue 3 (IJIEPR- In Progress 2026)
IJIEPR 2026, 37(3): 108-120 |
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hechlaf O, EL OUALIDI M A, MHARZI H. Measuring Humanitarian Supply Chain Resilience under Natural Hazards: A Methodological Typology and Cross-Phase Research Agenda. IJIEPR 2026; 37 (3) :108-120
URL: http://ijiepr.iust.ac.ir/article-1-2564-en.html
URL: http://ijiepr.iust.ac.ir/article-1-2564-en.html
1- Laboratory of Advanced Research in Industrial and Logistic Engineering (LARILE), Hassan II University of Casablanca, Morocco , oumayya.hechlaf-etu@etu.univh2c.ma
2- Laboratory of Advanced Research in Industrial and Logistic Engineering (LARILE), Hassan II University of Casablanca, Morocco
2- Laboratory of Advanced Research in Industrial and Logistic Engineering (LARILE), Hassan II University of Casablanca, Morocco
Abstract: (265 Views)
Natural hazards place humanitarian supply chains under pressure by damaging infrastructure, increasing uncertainty, and making the delivery of relief assistance more difficult. Although humanitarian supply chain resilience has become an important topic in logistics and disaster management research, the way it is measured remains fragmented across hazard contexts, methodological approaches, and disaster phases. This paper reviews how humanitarian supply chain resilience has been assessed under natural hazard conditions through a PRISMA-guided systematic literature review of 54 studies identified through searches in the Scopus and Web of Science databases and published between 2014 and May 2026.
The analysis combines descriptive results, VOS viewer keyword co-occurrence mapping, and a coding framework covering hazard context, methodological family, resilience phase, measurement focus, and contribution to humanitarian decision-making. The results show that floods and earthquakes receive attention, while cyclones, typhoons, landslides, droughts, and cascading hazards remain less represented. Optimization models are the common methodological family, followed by multi-criteria decision-making, simulation, statistical and probabilistic modeling, qualitative case-based approaches, AI/data-driven methods, and hybrid decision-support models.
The review also shows that most studies emphasize operational indicators, including response time, cost, routing efficiency, facility location, accessibility, and relief allocation. Coordination capacity, deprivation cost, social vulnerability, recovery, organizational learning, and feedback between disaster phases are weakly integrated into existing measurement frameworks. The paper contributes by developing a methodological typology of humanitarian supply chain resilience measurement approaches and by proposing a hazard-sensitive and cross-phase research agenda for future studies.
The analysis combines descriptive results, VOS viewer keyword co-occurrence mapping, and a coding framework covering hazard context, methodological family, resilience phase, measurement focus, and contribution to humanitarian decision-making. The results show that floods and earthquakes receive attention, while cyclones, typhoons, landslides, droughts, and cascading hazards remain less represented. Optimization models are the common methodological family, followed by multi-criteria decision-making, simulation, statistical and probabilistic modeling, qualitative case-based approaches, AI/data-driven methods, and hybrid decision-support models.
The review also shows that most studies emphasize operational indicators, including response time, cost, routing efficiency, facility location, accessibility, and relief allocation. Coordination capacity, deprivation cost, social vulnerability, recovery, organizational learning, and feedback between disaster phases are weakly integrated into existing measurement frameworks. The paper contributes by developing a methodological typology of humanitarian supply chain resilience measurement approaches and by proposing a hazard-sensitive and cross-phase research agenda for future studies.
Type of Study: Review |
Subject:
Logistic & Apply Chain
Received: 2025/10/6 | Accepted: 2026/07/1 | Published: 2026/09/8
Received: 2025/10/6 | Accepted: 2026/07/1 | Published: 2026/09/8
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