Latent Classes Exploring the Sense of Passengers Well-Being in the Terminal: Evidence from a Peripheral Airport

This paper aims to explore the sense of passengers well-being in the terminal of an airport. The proposed methodology is performed into two stages: firstly, we use a basic latent class modeling approach in order to identify the latent classes representing air passengers’ attitude towards the different provided service quality aspects, and detecting the sense of passengers well-being in the terminal; then, we introduce covariates in order to better explore latent class memberships as a function of socio-economic characteristics, travel habits and flight features. Evidences from a peripheral airport placed in the south of Italy were used for testing the proposed methodology and for obtaining practical issues. Specifically, we found that three latent classes of air passengers can be identified, namely no-sensitive passengers, cleanliness-sensitive and information-sensitive passengers. We found also that among the socio-economic characteristics, gender does not very influence very much class memberships, whereas age and level of education strongly affect class population shares. At the same time, travel purposes, country and arrival time before the flight showed a certain influence in predicting passengers class memberships.