Network Modeling and Risk Assessment of Multi-Stakeholder-Coupled Unsafe Events in the Airspace System

Unsafe events in civil aviation increasingly arise from multi-stakeholder interactions, motivating system-level methods to quantify event risk and coupling. This study analyzes 1551 airspace unsafe-operation reports and models each report as a node with four attributes; edges capture co-occurrence based on cosine similarity, and risk is scored via an entropy-weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) scheme. Risk scores range 0–0.858, with 7% of nodes above 0.8 forming a high-risk tail; entropy weights emphasize recovery time and hazard level. Community detection yields three modules aligned with Controller, Resource, and User stakeholders; key nodes occur predominantly in Controller and Resource groups, with Controller nodes showing the highest betweenness. Coupling analysis using an N–K perspective and edge-based inter-stakeholder strength further highlights controller-centric links. The proposed framework objectively ranks node risk, reveals cross-stakeholder coupling patterns, and isolates structurally influential events, providing evidence to prioritize monitoring and mitigation in airspace safety management.