Risk Analysis and Resilience of Humanitarian Aviation Supply Chains: A Bayesian Network Approach

The humanitarian aviation supply chain (HASC) serves as a critical conduit for delivering essential aid to populations affected by disasters and conflicts, especially when ground routes are inaccessible. However, HASCs operate in high-risk environments marked by instability, infrastructure damage, and operational challenges. Existing risk assessment approaches often struggle to account for the complex interdependencies among the many factors influencing mission success and supply chain resilience. This study introduces a comprehensive risk analysis framework for HASCs using Bayesian networks (BNs). The BN model integrates data on factors such as political instability, infrastructure damage, adverse weather, crew fatigue, and aircraft maintenance. Through quantitative analysis, the framework identifies critical vulnerabilities and assesses the likelihood of mission failure.