Fuzzy inference system for forecasting non-aeronautical revenues considering the customer experience

Abstract

Non-aeronautical revenues are associated with commercial activities at the airport, in which the fundamental factor in managing these revenues is the customers’ experience. This study numerically analyzed the influence of passenger satisfaction and waiting time on consumption made in the commercial facilities of the Airport Passenger Terminal, operating predominantly with domestic flights. This research was made through a structured questionnaire and the passengers in the airport to support the definition of the behavior of the Fuzzy Inference System. The results show that the greater the passenger satisfaction and waiting time, the greater the chances of significantly shopping. Furthermore, this study presents fuzzy modeling of a rule-based computational intelligence system capable of forecasting non-aeronautical revenues referring to shopping and dining experience, with significant contributions to the literature and airport management.