Quantifying preference heterogeneity in transit service desired quality using a latent class choice model (original) (raw)

2020, Transportation Research Part A: Policy and Practice

This study aims at quantifying preference heterogeneity in transit service desired quality to better-informing service quality improvements. The analysis is performed using a validated dataset elicited from 906 respondents through an online survey. An unlabelled Stated Preference (SP) experiment was utilized in a Latent class Choice Model (LCM), and an Error Components interaction model. The results of the EC interaction model revealed preference heterogeneity due to differences in respondents' socioeconomic and behavioural characteristics. While the results of the LCM untapped vital information that has not been reported previously in the transit service quality literature. Unlike the traditional user type classification, our study classifies respondents into three segments: Direct Trip Enthusiastic (DTE), Cost-Sensitive (CS), and Real-time Information Supporter (RIS). Each segment exhibits different preferences for transit service attributes, and their willingness to pay for service improvements is distinctly different. Further, the LCM indicates that the heterogeneity of users' preferences is not explicit in their usage pattern nor accessibility to different travel modes; instead, it is a bundle of various parameters. 1. Introduction High-quality public transit service is essential to address the deterioration of traffic conditions and air quality in urban areas resulting from the soaring rates of car ownership. Many research studies have been carried out to identify transit quality aspects that affect service attractiveness and, in turn, promote transit ridership. The dominant approach in the literature is rooted in understanding consumers' preferences with an emphasis on current transit users (Krizek and El-Geneidy, 2007; Mazzulla and Eboli, 2006). Although consumer satisfaction cannot be overemphasized, yet attracting new users is equally vital for a sustainable transit system. Consequently, efficient transit systems should strive to satisfy current users and attract potential users at the same time (Mahmoud and Hine, 2013). That said, both current and potential users exhibit different preferences associated with transit services (Krizek and El-Geneidy, 2007; Mahmoud and Hine, 2016; Mahmoud and Hine, 2013; Mahmoud et al., 2011), and policies aimed at satisfying current users might not necessarily succeed in attracting new users. In this respect, quantifying the gap, or the lack thereof, in the preferences of different users' groups, offers significant advantages. This indeed enables service providers and policymakers to target a broad spectrum of users with directed service quality improvements. Methodologically, there is a clear distinction in the literature associated with measuring the preferences of transit users. Some studies adopt discrete choice models based on stated preference experiments. These are similar to the works of (dell' Olio et al., 2011;