Feature Analysis for Multi-Criteria Rating Values of Airline Companies

Abstract

The development of information and communication technologies offers the possibility of collecting and sharing customer views, comments and ratings about products and services over the Internet. Customers generally make these evaluations based on multiple criteria. This study uses such data recorded on Skytrax to analyse the performance of leading airlines. It does so using the a multicriteria decision making technique (Promethee II), and the criteria weight values required for the Promethee II method are obtained from a Multi-Layer Perceptron (MLP), an artificial neural network method. According to the results obtained, ANA airline has shown improvements in the years and moved up to the top, while the ranking of United airline within two years has not changed. The paper provides details of the technique and graphically presents results to highlight where airlines possess advantages over their competitors.