On the effect of operational service attributes on transit satisfaction

Public transport (PT) providers aim to offer services that meet users’ satisfaction, and for this, they can control some operational service attributes such as frequency, speed, crowdedness and reliability. Understanding how these objective attributes affect user satisfaction is essential to improve it cost-effectively, but these associations have not been examined enough in the PT literature. This study aims to unveil how key transit operational variables actually experienced by users affect their satisfaction. We analysed data derived from a multiannual consumer satisfaction survey for the Santiago de Chile Metro system; between January 2013 and June 2016 (n?=?41,993), where approximately 1000 questionnaires were completed each month. We also gained access to a set of operational variables managed by Metro for the same period, including more than 1.4 million records. With this unique dataset, we first developed a structural equation model (SEM) with users’ perceived attributes, finding that safety, ease of boarding, response to critical incidents (CI), the number and type of CI endured, and information, were the variables that mostly affected satisfaction. We also examined heterogeneity in transit satisfaction with SEM-MIMIC models, by characterising the user population through their trip and socioeconomic characteristics, finding a striking result: that as users age they are more satisfied with the system. Next, we assessed whether including operational service attributes, such as crowding levels, frequency, commercial speed and CI, added predictive power to the proposed model. We found that the number of CI, speed, frequency and crowdedness, plus their variability (measured through the coefficient of variation), affected transit satisfaction at significant levels. Including these objective service attributes provided more explanatory power to the SEM-MIMIC transit satisfaction models. Policy recommendations for improving satisfaction, derived from our results, are: to implement an automatic control system for the number of passengers on Metro platforms (as safety and ease of boarding are critical issues for passengers); and to deploy a comprehensive tactical plan to address CI: determine which happen more often, take actions to minimise them and provide better responsive actions.

     

Effect of critical incidents on public transport satisfaction and loyalty: an Ordinal Probit SEM-MIMIC approach

Transportation - Supplying public transport systems with high levels of service quality is fundamental for retaining users and attracting new ones. Policies that improve transit service quality...     

About attitudes and perceptions: finding the proper way to consider latent variables in discrete choice models

We provide an in-depth theoretical discussion about the differences between individual-specific latent constructs (representing attitudes, for example, but also other characteristics such as values or personality traits) and alternative-specific latent constructs (that may represent perceptions) affecting the choice-making process of individuals; we also carry out an empirical exercise to analyze their effects. This discussion is of importance, as the majority of papers considering attitudinal latent variables just take these as attributes affecting directly the utility of a certain alternative, while systematic taste variations are rarely considered and perceptions are mostly ignored. The results of our case study show that perceptions may indeed affect the decision making process and that they are able to capture a significant part of the variability that is normally explained by alternative specific constants. Furthermore, our results indicate that attitudes may be a reason for systematic taste variations, and that a proper categorization of latent variables, in accordance with underlying theory, may outperform the customary assumption of linearity.     

Understanding suburban travel demand: Flexible modelling with revealed and stated choice data

We analyse the choice of mode in suburban corridors using nested logit specifications with revealed and stated preference data. The latter were obtained from a choice experiment between car and bus, which allowed for interactions among the main policy variables: travel cost, travel time and frequency. The experiment also included parking cost and comfort attributes. The attribute levels in the experiment were adapted to travellers’ experience using their revealed preference information. Different model specifications were tested accounting for the presence of income effect, systematic taste variation, and incorporating the effect of latent variables. We also derived willingness-to-pay measures, such as the subjective value of time, that vary among individuals as well as elasticity values. Finally, we analysed the demand response to various policy scenarios that favour public transport use by considering improvements in level-of-service, fare reductions and/or increases in parking costs. In general, demand was shown to be more sensitive to policies that penalise the private car than those improving public transport.     

Valuing casualty risk reductions from estimated baseline risk

Stated choice studies have been applied regularly to the valuation of time savings and other attributes of travelling as perceived by individuals. In such experiments, respondents often provide reference levels for the attributes and the hypothetical choices presented to them are pivoted around actual behaviour. However, most individuals are not able to provide reference levels for the number of casualties on the road they travel. Thus, if valuation of this important element is attempted, it is the researcher who must provide casualty risk reference levels to the respondents. Some studies have applied route choice experiments including a safety attribute but the majority has been limited to only one particular road section with a common baseline risk for all respondents.     

Evaluating marginal improvements to a transport network: An application to the Santiago underground

This paper describes a simplified methodology designed for quick investment appraisal of improvements to a transport network, and discusses its limitations and advantages particularly in the context of a developing country. The approach basically considers:

- a method to define the total population (relevant origin-destination pairs) affected by the project

- the selection of a low-cost background model to represent transport demand on a network at an aggregate level

- the choice of a suitable marginal demand model (in this case a discrete mode choice model) capable of providing the required sensitivity and accuracy to model the project

- the estimation of the marginal demand due to the project during all the years of the study horizon, and

- a sensitivity analysis to assess the robustness of the decision recommended using these two models.

Finally, the paper summarises the results of applying the methodology to the case of an extension to the Santiago underground; it was found that the project has a high social rate of return (almost 20 per cent). However, from the point of view of a private evaluation, it can cover its operating costs only.     

Inclusion of latent variables in Mixed Logit models: Modelling and forecasting

Travel demand models typically use mainly objective modal attributes as explanatory variables. Nevertheless, it has been well known for many years that attitudes and perceptions also influence users’ behaviour. The use of hybrid discrete choice models constitutes a good alternative to incorporate the effect of subjective factors. We estimated hybrid models in a short-survey panel context for data among many alternatives. The paper analyses the results of applying these models to a real urban case study, and also proposes an approach to forecasting using these models. Our results show that hybrid models are clearly superior to even highly flexible traditional models that ignore the effect of subjective attitudes and perceptions.     

Telemetric system for monitoring and automation of railroad networks

This paper describes a new method of real-time train monitoring based on the ZigBee/IEEE 802.15.4 protocol. The system consists of a mobile device embedded in the moving train which transmits parameter signals that are being measured by a base unit with the help of routers. When applied, the technique monitors and controls vehicles operating on permanent routes, making a real-time evaluation of their performance and location, and allowing an effective planning of trains. It consists of a low cost, low power consumption and safe modular technology capable of monitoring many different variables simultaneously.     

Implications of Thresholds in Discrete Choice Modelling

Abstract

Individual choices are affected by complex factors and the challenge consists of how to incorporate these factors in order to improve the realism of the modelling work. The presence of limits, cut‐offs or thresholds in the perception and appraisal of both attributes and alternatives is part of the complexity inherent to choice‐making behaviour. The paper considers the existence of thresholds in three contexts: inertia (habit or reluctance to change), minimum perceptible changes in attribute values, and as a mechanism for accepting or rejecting alternatives. It discusses the more relevant approaches in modelling these types of thresholds and analyses their implications in model estimation and forecasting using both synthetic and real databanks. It is clear from the analysis that if thresholds exist but are not considered, the estimated models will be biased and may produce significant errors in prediction. Fortunately, there are practical methods to attack this problem and some are demonstrated.     

Addressing endogeneity in strategic urban mode choice models

Transportation - Endogeneity is a potential anomaly in econometric models, which may cause inconsistent parameter estimates. Transport models are prone to this problem and applications that...