Abstract

Airports are one of the most important facilities in the transportation system of critical infrastructure. In the face of particular disasters, it is difficult to build a risk prediction model based on past statistical data. To strengthen the airports resilience, it is feasible to develop protection strategies using the expert-based Multiple Criteria Decision Making (MCDM) approach. This study proposes a novel evaluation model that uses the Bayesian Best Worst Method (Bayesian BWM) to determine the optimal group weights for the criteria, and uses the modified Preference Ranking Organization Method for Enrichment Evaluations (modified PROMETHEE) to calculate the difference between each alternative and the aspiration level and then rank it. Taiwan’s airports were used to demonstrate the practicality and effectiveness of the model. In addition, the sensitivity analysis and the model comparisons also confirmed the reliability of the proposed model. The research results show that the proposed evaluation system effectively assists policy makers and airport security departments to formulate improvement strategies, thereby enhancing the resilience of airports.

Keywords: Airport resilience, MCDM, Bayesian BWM, modified PROMETHEE

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