Evaluation of the efficiency of world airports using WENSLO-ARTASI and Monte-Carlo simulation

Abstract

This study addresses the challenge of evaluating and ranking airport efficiency by proposing a novel multi-criteria decision-making (MCDM) framework. The framework integrates the WENSLO (Weights by ENvelope and SLOpe) method for robust weight determination and the ARTASI (Alternative Ranking Technique based on Adaptive Standardized Intervals) method for impartial alternative evaluation. This innovative approach, WENSLO-ARTASI, utilizes a distinctive algorithm for logical reasoning and facilitates effective decision-making in evaluating airport efficiency. The research employs real-world data from the Skytrax website, encompassing airport evaluations across four-star categories (2–5 stars). Nine primary criteria and 49 sub-criteria belonging to 413 airports that remained in the dataset after the cleaning process were identified. The WENSLO technique determined distinct weight sets for each star category, revealing varying priorities among different airport levels. Notably, ground transportation emerged as a critical factor for 2, 3, and 5-star airports, while shopping facilities held greater importance at four-star airports. The proposed WENSLO-ARTASI framework was rigorously evaluated for accuracy and stability through sensitivity and comparative analyses. Parameter fine-tuning within the utility function was performed to assess its impact, followed by comparing the model's results with established MCDM techniques like MABAC, MARCOS, TOPSIS, and WASPAS. The validity of the findings was further corroborated through a Monte Carlo simulation, statistically demonstrating the non-outlier nature of both WENSLO and ARTASI assessments. Additionally, the comparative superiority of alternatives was statistically examined, providing robust evidence for the effectiveness of the proposed framework in airport ranking.