Journal
TRAVEL BEHAVIOUR AND SOCIETY
Volume 26, Issue -, Pages 193-205Publisher
ELSEVIER
DOI: 10.1016/j.tbs.2021.10.007
Keywords
Urban rail transit; Traveller experience; Metro; Subway; LDA; Textual analysis
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This research uncovered experiential dimensions of URT travellers from TripAdvisor reviews and compared URTNs worldwide using unsupervised machine learning technique. The analysis identified eleven experiential dimensions and factors that drive positive and negative experiences. This study presents a rapid and insightful method for assessing traveller experiences, which can be used by URTNs worldwide for service improvement.
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.
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