Monsuur Fredrik, Enoch Marcus, Quddus Mohammed, Meek Stuart
Transport and Urban Planning Group, School of Architecture, Civil and Building Engineering, Loughborough University, Loughborough, LE11 3TU UK.
MaasLab, Energy Institute, University College London, 14 Upper Woburn Place, London, WC1H0NN UK.
Transportation (Amst). 2023 Jun 1;52(4):1-27. doi: 10.1007/s11116-023-10397-x.
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.
本研究探讨了与英国铁路乘客满意度相关的因素。为了揭示偏好差异,通过潜在类别有序logit模型将数据分为三组同质的乘客群体,其中类别划分基于观察到的个人和行程特征。研究结果表明,服务属性对总体满意度的影响在“a类”、“b类”和“c类”这几个细分群体中存在显著差异。a类(占样本的15%)由中度不满到高度不满的乘客组成,对他们来说,“准点/可靠性”对总体满意度影响最大。该类别的受访者更有可能经历诸如延误或拥挤等不利的服务状况。b类(占样本的32%)由批判性较强且中度满意的乘客组成,对他们来说,“列车维护与修理”和“座位舒适度”等“享乐”因素影响最大。最后,c类(占样本的53%)由总体满意的乘客组成,对他们来说,“票价性价比”对总体满意度影响最大。有趣的是,与a类相比,“准点/可靠性”在决定b类和c类乘客的总体满意度方面所起的作用更为有限。这表明“准点/可靠性”在决定总体满意度方面的作用比迄今为止文献中所呈现的更为复杂。最后,未观察到的偏好差异在模型中起着重要作用,因为类别划分并不总是容易与数据中观察到的群体相关联。因此,本文强调了考虑数据中未观察到的和系统性的异质性来源的重要性,并可为分析师、政策制定者和从业者提供有用的见解,以制定更具针对性的策略来提高乘客满意度。