|Title||The impact of mean time between disasters on inventory pre-positioning strategy|
|Author(s)||Saputra, Tezar Yuliansyah; Pots, Olaf; Smidt-Destombes, Karin S. de; Leeuw, Sander de|
|Source||Disaster Prevention and Management 24 (2015)1. - ISSN 0965-3562 - p. 115 - 131.|
|Publication type||Refereed Article in a scientific journal|
|Keyword(s)||Humanitarian logistics - Inventory pre-positioning - Inventory swap - Mean Time Between Disasters (MTBD) - Shelf life - Zimbabwe|
Originality/value: The authors introduce relevant factors in humanitarian organizations practice that have not yet received attention in literature (i.e. MTBD, inventory swap, and trade-off decisions in transport modes and end-of-shelf life policies).
Purpose: The purpose of this paper is to address the impact of Mean Time Between Disasters (MTBD) to inventory pre-positioning strategy of medical supplies prior to a sudden-onset disaster.
Design/methodology/approach: The authors developed a trade-off model based on the operations of Médecins Sans Frontières (MSF) and implemented this in a spreadsheet-based platform to show the impact of MTBD on determining the pre-positioning strategy. This spreadsheet model identifies the most cost-efficient scenario out of a set of predefined pre-positioning scenarios. The authors implemented the model using a case study of a cholera outbreak in Zimbabwe.
Findings: The authors are able to show the impact of MTBD on determining the pre-positioning strategy. In addition, the authors also capture the trade-off decisions in transport modes and end-of-shelf-life policies. Moreover, from financial perspective, the authors show that an interaction between relief (emergency) and development (regular) programs can be beneficial.
Research limitations/implications: The authors have some limitations on data access and availability. Some data (e.g. uncertainty in needs and lead-time) have to be collected for future research and, then, used to refine such decisions.
Practical implications: The model can be used as a justification for selecting an inventory pre-positioning strategy based on MTBD.