Passenger experience and market segmentation in airports: Evidence from online reviews

Abstract

This study examines passengers' perceptions of airport experiences using user-generated content and explores the potential for market segmentation by traveller type, airport experience, region, and culture. Data were gathered from 39,070 text reviews and ratings on the Skytrax platform. A mixed-methods approach was used, incorporating econometric modelling (multiple and logistic regression) to analyse traveller ratings and recommendations, alongside text mining (via Leximancer) to assess online reviews. To account for passenger heterogeneity, the models were estimated for distinct traveller groups. The text review analysis identified ten key dimensions of the airport experience: Airport Staff, Airline Services, Queuing Times, Airport Overall Experience, Terminal Signage, Airport Shopping, Terminal Cleanliness, Terminal Seating, Food & Beverages, and Wi-Fi Connectivity. The model estimates showed that Airport Staff and Queuing Times carried the greatest weight in overall ratings and recommendations. The weight of each attribute in the overall rating and in the recommendation varied across passenger segments. These findings contribute to the literature by clarifying how airport quality attributes influence passengers' recommendations and overall ratings, while highlighting heterogeneity across culturally diverse passenger segments.