Fleet sizing for UNHCR country offices

Abstract

Vehicles are important assets generating significant costs. Relief organizations frequently struggle to define the appropriate number of vehicles to support their operations. The high level of decentralization giving country offices the autonomy to decide on the size of their fleet complicates the issue. This study follows a design science approach in collaboration with the Office of the UN High Commissioner for Refugees (UNHCR). We develop a prediction model to support UNHCR's fleet sizing problem. A stepwise linear regression approach is used to construct a model able to predict the number of vehicles required by each country office based on data from comparable countries. Three variables have the best predictive accuracy: the number of locations, small partners, and large partners working for UNHCR. We validate our findings with different regression methods and by applying our approach to another organization. Our model has provided UNHCR with valuable indications on how to help determine the appropriate number of vehicles in many countries. We develop three design propositions that show how our approach can be generalized to other humanitarian operations. These propositions offer insights on how to implement a fleet sizing decision process in highly decentralized humanitarian operations with limited information on optimal fleet sizes.

Humanitarian Operations: A World of Opportunity for Relevant and Impactful Research

“…Evidence-based research needs to work with whatever poor data are available as opposed to beating available databases to death, because the data are conveniently clean and close at hand, sometimes even at the expense of obtaining little of interest in terms of insights or impact (de Vries and Van Wassenhove 2017). Are we prepared to consider the design science literature, moving from learning about and improving operations of a single organization to developing more general theories that can be verified (Holmström et al 2009, van Aken and Romme 2012, Kunz and Van Wassenhove 2019? How far should availability of data and opting for complex methods offering optimal solutions to stylized subsystems drive problem choice (Besiou and Van Wassenhove 2015)?…”

Exploration of a disrupted road network after a disaster with an online routing algorithm

“…Current solution approaches focus on minimizing operational costs and maximizing the coverage of humanitarian assistance. To deal with limited accessibility after a disaster, Kunz and Van Wassenhove (2019) propose a model to determine the vehicle fleet required to reach all locations of victims in a disrupted road network. The authors minimize the cost while estimating the size of the vehicle fleet to determine the right trade-off between these contradicting objectives.…”

Editorial:Intervention‐basedresearch (IBR)—What, where, and how to use it in operations management

“…Kuntz and Van Wassenhove (2019) investigated how changes in fleet sizes affected the ability of relief organizations to support their missions. The authors used data from the fleet management unit of the Office of the United Nations High Commissioner for Refugees to show that both centralizing fleet sizing at the fleet management level and decentralizing it at the country office level resulted in inefficiencies (too many or too few vehicles across county locations).…”

“…Although the first three papers (Groop et al, 2007; Akkermans et al, 2019; Kunz & Van Wassenhove, 2019) were accepted by the DS department editors, they diverged from the traditional DS view of creating and testing an artifact as exemplified by Brusset and Bertrand (2018). Rather, all three papers described research that began from a failed attempt to apply theory to a problem, resulting in a new understanding of the problem or an expansion of the set of theories used to solve the problem.…”

“…Fleet sizing for UNHCR country offices (Kunz & Van Wassenhove, 2019) Humanitarian operations Problem: Relief organizations do not always have the appropriate fleets for supporting their missions. Intervention: Traditional approaches to making centralized decisions fail, while decentralized decision-making leads to inefficiencies or excess fleets when not needed.…”