Humanitarian logistics in archipelagic countries such as Indonesia face complex, multi-dimensional risks, including operational disruptions, coordination failures, and reputational challenges. This study develops a risk-robust incentive mechanism for disaster response using expected utility theory with risk premium adjustments. A principal–agent model is formulated in which the disaster management agency (BNPB) designs incentive contracts for humanitarian actors, such as NGOs and logistics providers, who hold private information regarding their capacity and effort. The model incorporates multi-dimensional risks into both the principal’s social welfare function and the agents’ utility functions, including empirically derived risk aversion parameters. Monte Carlo simulation is applied to 10,000 hypothetical disaster scenarios with varying risk conditions to illustrate the mechanism’s application. The study emphasizes theoretical and methodological contributions rather than numerical outcomes. Illustrative simulation results suggest that, under hypothetical parameter settings, the proposed mechanism can generate higher fulfillment rates and shorter response times than a risk-neutral benchmark. Sensitivity analysis further shows that accounting for correlated risks and ambiguity aversion enhances robustness. These findings offer practical insights for designing incentive-aligned and risk-aware humanitarian logistics systems in disaster-prone regions.
Ladesi et al. (Thu,) studied this question.