Deciding between cash-based and in-kind distributions during humanitarian emergencies

Abstract

Purpose The purpose of this paper is to provide an analytical model to decide between cash-based and in-kind distributions during emergency responses considering the needs of beneficiaries and market conditions. To allow the switch between modalities, a preparedness framework for humanitarian organizations (HOs) is provided. Design/methodology/approach A mathematical model is proposed to help humanitarian responders make quantitative decisions on the type of programs to implement in emergency responses. The model was applied to a field response by an international HO during the COVID-19 emergency in Colombia. Findings Cash-based and in-kind distributions are not mutually exclusive response modalities during emergencies, and the real needs of beneficiaries and market effects should be included in the modality selection decision to improve program effectiveness. Research limitations/implications The research is focused on short-term immediate response to emergencies; the proposed model assumes favorable market conditions and limits the aid options to direct in-kind and multipurpose cash assistance, excluding other types of cash transfers. Practical implications The research outlines practical preconditions to operationalize switching between programs during an emergency. The study provides evidence that HOs should consider dynamics decision tools to select aid modalities and evaluate their response depending on market conditions. Social implications Considering aid modality as a dynamic decision and including the needs from beneficiaries in the choice can have profound impact in the dignifying of humanitarian response to emergencies. Originality/value The quantitative model to decide between aid modalities is a novel approach to include beneficiaries' needs and market dynamics into humanitarian supply chain research. The preparedness framework closes the gap between the emergency preparedness literature and the operational constraints that organizations face for fast program implementation.

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