The pre-positioning of warehouses at regional and local levels for a humanitarian relief organisation

The pre-positioning of warehouses at regional and local levels for a humanitarian relief organisation

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Article ID: iaor201529901
Volume: 170
Start Page Number: 616
End Page Number: 628
Publication Date: Dec 2015
Journal: International Journal of Production Economics
Authors: , , ,
Keywords: supply & supply chains, economics, analytic hierarchy process, decision
Abstract:

Using pre-positioned warehouses at strategic locations around the world is an approach commonly taken by some humanitarian relief organisations to improve their capacities to deliver sufficient relief aid within a relatively short time frame, and to provide shelter and assistance to disaster victims. Although research into the facility location problem is extensive in both theory and application, such approaches have received little attention from the humanitarian relief perspective. In this paper we consider the pre-positioning of warehouses for humanitarian relief organisations from both macro- (which country, which region) and micro-(the immediate locality) perspectives, and analyse the managerial implications of those decisions. In case study A, managerial level officers were interviewed in order to obtain data for an analysis of the positioning of warehouses at a regional level. Case study B identifies a specific location in the Dubai area where stakeholders from different organisations participated in both discussions and interviews. Through the use of the Analytic Hierarchy Process, the relative importance of individual criteria was determined. The fuzzy-TOPSIS method was used to obtain the final ranking of locations where linguistic values handle the vagueness and subjectivity of decisions. The contribution of this work is as follows: useful managerial insights and implications related to the pre-positioning of warehouses at both macro- and micro-levels are provided; further, a range of possible locations for a humanitarian relief organization, using a robust multicriteria decision making framework, is proposed.

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