Optimizing Humanitarian Supply Chains: Analyzing Consumer Behavior Patterns in Crisis-Affected Communities in Cameroon

This study explores the optimization of humanitarian supply chains (HSCs) in crisis-affected communities in Cameroon by analyzing consumer behavior patterns. Optimization is the process of finding the best possible solutions to a problem within a set of constraints and conditions. Humanitarian supply chain is a specialization system that focuses on timely delivering of goods and services during emergencies and disaster, which is critical in life saving. The purpose is to enhance the responsiveness and efficiency of aid delivery systems by aligning supply chain strategies with the actual needs and behaviors of affected populations. Using secondary data from humanitarian operations and supply chain performance studies, this research applies thematic analysis approach to identify behavioral trends and logistical challenges. Methodologically, the study synthesizes findings from existing literature on humanitarian logistics, performance measurement models, and supply chain design frameworks. The analysis reveals that consumer behavior in crisis settings is influenced by cultural norms, urgency of needs, and trust in aid providers, which in turn affects demand forecasting and inventory positioning. This study contributes both theoretically, by expanding the scope of supply chain models to include behavioral dimensions, and practically, by offering a framework that enhances the responsiveness and relevance of aid delivery in crisis-affected communities. Findings indicate that integrating behavioral data into supply chain design can significantly improve aid effectiveness, reduce waste, and enhance community resilience for life saving. Moreover, the study highlights the importance of localized strategies, stakeholder coordination, and adaptive technologies in optimizing HSCs. Implications for policymakers and humanitarian organizations include the need for data-driven decision-making, community engagement, and flexible supply chain models tailored to dynamic crisis environments.