Asset supply networks in humanitarian operations: A combined empirical‐simulation approach

TLDR

IHOs must manage asset supply networks that simultaneously support rapid disaster response and cost‑effective development programs worldwide. The study investigates how resource fluidity—the ability to reallocate assets quickly—affects both mega‑disaster and regular‑operations asset flows and uses these findings to simulate scenarios for IHOs lacking fluidity. Using data from a large IHO’s mega‑disaster response and econometric modeling, the authors quantify the dependency between disaster and regular‑operations flows and incorporate the results into a simulation framework. Results show that higher disaster flows reduce hub‑to‑hub regular‑operations flows while increasing other flows, contradicting the assumption of independent flows, yet resource fluidity prevents compromise of regular operations and influences network costs and optimal configurations.

Abstract

Abstract International humanitarian organizations (IHOs) respond to mega disasters while maintaining development programs in the rest of the world (ROW). This means an IHO's asset supply network must perform the challenging task of supporting a fast disaster response while simultaneously maintaining cost‐effective ROW development programs. We study how supply network asset flows are impacted during a mega disaster response and find that resource fluidity, the capability to reallocate resources quickly, impacts both mega disaster and ROW program asset flows within these supply networks. Using data from a large IHO's response to a mega disaster and econometric models, we find a dependency between ROW asset flow and mega disaster asset flow in IHOs with resource fluidity. As mega disaster flow increases, there is a decrease in hub‐to‐hub ROW asset flows and an increase in other ROW asset flows. This is contrary to most humanitarian operations research, which typically assumes independent asset flows. Because of resource fluidity, the combination of these flows does not compromise ROW operations. We use these empirical results to feed a simulation analysis that extends our research to IHOs without resource fluidity and provides actionable insights for varying types of IHOs in various demand scenarios. Simulation insights illustrate that resource fluidity impacts IHO asset supply network costs and optimal configurations.