Monsuur, Fredrik; Enoch, Marcus; Quddus, Mohammed; Meek, Stuart; (2023) Investigating the role of preference variation in the perceptions of railway passengers in Great Britain. Transportation 10.1007/s11116-023-10397-x. (In press).

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Abstract

This study explores the factors associated with passenger satisfaction on the UK railways. To uncover taste variation, the data was segmented into three homogeneous groups of passengers through a latent class ordered logit model, whereby the class allocation was based on observed personal and trip characteristics. The findings suggest that there is significant variation in the impact of service attributes on overall satisfaction across the segments, ‘class a’, ‘class b’ and ‘class c’. Class a (15% of the sample) consists of moderately dissatisfied to highly dissatisfied passengers, for whom ‘punctuality/reliability’ is most impactful on overall satisfaction. Respondents in this class are much more likely to experience adverse service conditions such as delays or crowding conditions. Class b (32% of the sample) consists of passenger who are quite critical and moderately satisfied, for whom ‘hedonic’ factors such as ‘upkeep and repair of the train’ and ‘seat comfort’ were most impactful. Finally, class c (53% of the sample) consists of passengers that are generally satisfied, and for whom the ‘value for money of the ticket price’ is most impactful on overall satisfaction. Interestingly, for both ‘class b’ and ‘class c’, ‘punctuality/reliability’ plays a more limited role in determining overall satisfaction compared to ‘class a’. This suggests that the role of ‘punctuality/reliability’ in determining overall satisfaction is more complex than presented in the literature thus far. Finally, unobserved taste variation plays an important role in the model, as the class allocation is not always easily linked to observed groups in the data. This paper thus highlights the importance of accounting for unobserved and systematic sources of heterogeneity in the data and could provide useful insights for analysts, policy makers and practitioners, to provide more targeted strategies to improve passenger satisfaction.

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