Online from: 2011
Subject Area: Operations and Logistics Management
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|Title:||System dynamics for humanitarian operations|
|Author(s):||Maria Besiou, (INSEAD Social Innovation Center, Fontainebleu, France), Orla Stapleton, (INSEAD Social Innovation Center, Fontainebleu, France), Luk N. Van Wassenhove, (INSEAD Social Innovation Center, Fontainebleu, France)|
|Citation:||Maria Besiou, Orla Stapleton, Luk N. Van Wassenhove, (2011) "System dynamics for humanitarian operations", Journal of Humanitarian Logistics and Supply Chain Management, Vol. 1 Iss: 1, pp.78 - 103|
|Keywords:||Decision making, Fleet management, Humanitarian logistics, Systems theory|
|Article type:||Conceptual paper|
|DOI:||10.1108/20426741111122420 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – The purpose of this paper is to illustrate the appropriateness of system dynamics (SD) methodology as a tool for humanitarian decision makers to understand the effect of their decisions on humanitarian operations. The authors seek to present the initial stages and preliminary findings of a SD model used to analyze a well-defined subsystem of humanitarian operations, field vehicle fleet management; then build on this example by identifying an additional area of humanitarian operations for future research using the SD methodology.
Design/methodology/approach – Case-based research was combined with SD methodology to examine the appropriateness of this methodology for use in humanitarian operations.
Findings – Humanitarian operations are characterized by multiple actors, feedback loops, time pressures, resource constraints and uncertainty. The authors find that SD has the capacity to accurately represent the dynamic complexity of humanitarian operations, and is therefore an appropriate tool to study these systems.
Research limitations/implications – The well-defined issue of field vehicle fleet management in humanitarian organizations is used to illustrate an application of SD for humanitarian operations. Due to the difficulty in obtaining necessary data to build the SD model, this study uses estimations based on over three years of research into fleet management in the humanitarian sector. The authors then present an example of a broader but less well-defined subsystem in the humanitarian sector that can be analyzed using SD methodology to the benefit of the overall humanitarian relief operation.
Practical implications – Decision making in humanitarian operations is usually based on intuition and experience which are not always sufficient to fully understand the global impact of these decisions. SD provides humanitarian decision makers with a method to simulate and compare the impact of alternative decisions that would not be possible in real life situations.
Social implications – This paper examines the appropriateness of SD methodology to help humanitarians improve the effectiveness of their relief and development programs through better-informed decision making.
Originality/value – This paper presents one of the first attempts to use SD methodology to build a model for humanitarian operations using a well-defined subsystem, field vehicle fleet management.
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