An analysis of tripadvisor reviews of 127 urban rail transit networks worldwide

Abstract

Urban rail transit networks (URTNs) are essential for sustainability, equity and liveability of cities worldwide. Recent studies have explored ways in which URTNs can improve traveller experiences; however, the lack of a comprehensive method to benchmark URTNs worldwide and the lack of travellers’ voices and attitudes in conceptualisation call for a new technique to identify and assess URT traveller experience. This research aimed to uncover the experiential dimensions of URT travellers from TripAdvisor reviews and to compare URTNs worldwide. The research scope included 185,485 reviews on TripAdvisor collected from 127 URTNs in 123 cities. Data were analysed using an unsupervised machine learning technique, latent Dirichlet allocation (LDA). The analysis found eleven experiential dimensions: card, ticketing, direction, communication, architecture, network, performance, safety, crowd, connectivity and traffic. Subsequent salience-valence analyses identified factors that drive positive and negative experiences. This study presents a rapid and insightful method to assess traveller experiences. URTNs worldwide can use this technique to analyse and improve their services.