Abstract

Purpose The purpose of this paper is to present a system dynamics (SD) model that allows one to simulate resource deployment to fulfill increasing needs for commodities such as food and other consumables during disaster situations. The focus is on managing a suddenly increased demand (hoarding behavior) of an affected population under restricted transport conditions. The model aims to support decision makers by fostering comprehension of the systemic behavior and interdependencies of those complex settings. Design/methodology/approach Through literature review and case study analyses the SD model was established and implemented with STELLA 10.1.1. Findings The needs of relief units for response operations and supply of evacuees in the affected region result in conflicting needs under limited transport conditions during disaster situations. Therefore, uncertainties and dynamic parameters as, e.g., occurring delays, limited information, or delivery constraints and their influence on resource deployment under a sudden demand, have been identified and incorporated in this work. The authors found that an oscillating behavior within the system is possible to occur and is more intensified in case of regarding the additional needs of evacuees and relief units. Research limitations/implications Due to the high level of abstraction, it is not possible to incorporate all influencing variables in the SD model. Therefore, the authors focused on the most important ones with regard to the model objective. Practical implications To focus on awareness raising is of importance for decision makers in the context of disaster management. Furthermore, the authors found that the oscillating behavior is more irregular in case of assuming a higher increase rate of the water gauge than if a low increase rate is assumed. Originality/value To the best of the authors’ knowledge, none of the work already done refers to providing a flood-prone area with commodities under consideration of a sudden demand, by applying the SD approach. The presented model contributes on the generation of systemic insights of resource deployment under consideration of conflicting needs in times of a river flood to support decision makers in those situations.

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