A Hybrid AHP-BN Framework for Sustainable Aviation Supply Chain Risk Assessment: Integrating Environmental, Social, and Economic Dimensions

Sustainable aviation supply chains (SCs) are increasingly exposed to risks arising from environmental regulations, social responsibility pressures, and economic uncertainties. These risks are associated with different SC members and may propagate through operational dependencies among suppliers, maintenance service providers, and airline operators. To support systematic risk assessment, this study proposes a hybrid Analytical Hierarchy Process-Bayesian network (AHP-BN) framework for sustainable aviation SC risk management. The intended contribution is a contextual and structural extension of existing AHP-BN logic to member-level sustainability risk propagation in aviation SCs, rather than a claim that AHP-BN integration itself is fundamentally new. The proposed framework first classifies sustainability risks into environmental, social, and economic dimensions and identifies the risk exposure relationship between SC members and risk factors. For the weighting component, Analytical Hierarchy Process (AHP) is used to derive relative importance weights from specified illustrative pairwise comparison matrices in the numerical experiment. Bayesian network (BN) is employed to model probabilistic dependencies among nodes defined by SC members and risk factors. The two methods are coupled through a weighted expected risk index, which integrates AHP-derived weights, member-specific exposure intensities, probabilities inferred by BN, and losses associated with different risk states. A numerical illustration based on a synthetic aviation SC with suppliers, maintenance service providers, and airline operators is conducted to demonstrate the computational procedure and diagnostic use of the proposed framework rather than to validate an empirical risk profile of the aviation industry. Within this illustrative setting, cost volatility, supplier reliability, emissions regulation, and sustainable aviation fuel availability emerge as the major contributors to the overall risk index under the assumed inputs. The analysis further indicates that the proposed framework can identify critical active pairs of SC members and risk factors, reveal vulnerabilities at the levels of SC members and sustainability dimensions, and provide a transparent decision-support tool for sustainable aviation SC risk assessment, while the resulting rankings should be interpreted as conditional outputs under the assumed input parameters.