Oksuz, Mehmet Kursat; Satoglu, Sule Itir

Purpose: Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively. Design/methodology/approach: This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics. Findings: Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h. Originality/value: This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Polater, Abdussamet

Purpose: The main purpose of this paper is to examine the extant literature of humanitarian supply chain management (HSCM) which specifically use dynamic capabilities (DCs) view. By this means, the objectives of this study are to identify and assess the DCs used in the HSCM context, the factors positively and negatively affecting the DCs and how the DCs affect humanitarian supply chain (HSC) operations. Furthermore, this research aims to give directions for future research in the field of HSCM. Design/methodology/approach: This study adopts systematic literature review (SLR) approach proposed by Denyer and Tranfield (2009). Based on a SLR, this study synthesizes and compares the evidence, has a specific focus and research questions, has certain inclusion and exclusion criteria and provides evidence-based implications to the researchers and practitioners. This is a method which is replicable, transparent and auditable. The SLR methodology provides scholars and practitioners a basis for comprehending the current situation of relevant topic and taking correct steps in their future actions. Findings: This SLR deduces that applying DCs view is still in its infancy in the HSCM literature. The result of this SLR reveals that supply chain agility (SCA), supply chain resilience (SCR), reconfiguration/transformation, integration, (short-term) collaboration, sustaining, sensing, seizing and knowledge access DCs have been used in the HSCM literature. In addition, it is determined that only one paper analyzed the influence of DCs on predisaster performance while rest of the papers focused on the postdisaster performance. Originality/value: The result of the exhaustive literature search indicates that this is the first SLR that specifically analyzes the application of DCs view in the HSCM domain. This investigation determined the DCs used in HSCM and revealed the relations between the dependent and independent variables through the comprehensive model. In this way, this review provides a guidance to researchers in conduct their future investigations and practitioners to carry out supply chain (SC) operations by considering the factors affecting their operations.