A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership model. Such feedback allows switching class membership in response to the changes in choice contexts. The model is used for an empirical investigation of commuting mode and departure time choices in the Greater Toronto and Hamilton Area (GTHA) by using a large sample household travel survey dataset. The empirical model reveals that overall 38% of the commuters in the GTHA are more likely to switch modes than departure times and 62% of them are more likely to do the reverse. The empirical model also reveals that the average Subjective Value of Travel Time Savings (SVTTS) of the commuters in the GTHA can be as low as 3 dollars if a single choice pattern of departure time choices nested within mode choices is considered. It can also be as high as 67 dollars if the opposite nesting structure is assumed. However, the LCM estimates the average SVTTS to be around 27 dollars in the GTHA. An empirical scenario analysis by using the estimated model indicates that a 50% increase in morning peak period car travel time does not sway more than 4% of commuters from the morning peak period.

     

An exploratory analysis of observed and latent variables affecting intercity train service quality in developing countries

Transportation - Service quality (SQ) and customer satisfaction as perceived by 1037 passengers on intercity train services in Bangladesh were examined using structural equation modeling to explain...     

Structural equation approach to investigate trip-chaining and mode choice relationships in the context of developing countries

This paper investigates empirical relationships between trip chain type and mode class choice for developing countries. To formulate these two sets of decisions, four empirical models are developed using structural equation modeling (SEM). Those models are calibrated using one-month travel diary data collected in Dhaka city. SEM correlates the observed variables and identifies their relationship with trip-chaining type utility and mode class choice utility. The fitted models are selected based on statistical results and similarity with the real-life situation. Direct relationships between trip-chaining and mode choice utilities are found insignificant. However, several socio-demographic factors influence both simultaneously. Consequently, it is essential to consider mode class choice concurrently for modeling trip chains. This study also investigates the influencing factors for work-based and non-work-based trip chains separately and effects of road users’ heterogeneity. The research results can be utilized to perceive trip chain-mode choice patterns for developing countries.     

Structural equation modeling of user satisfaction of bus transit service quality based on stated preferences and latent variables

Few studies have been conducted on the service quality (SQ) of bus transit in developing countries. This paper presents a structural equation modeling (SEM) approach to identifying the relationships among major attributes that affect the SQ of bus transit in the city of Dhaka in Bangladesh. Specifically, 22 bus transit SQ attributes, drawn from 655 questionnaires, are used to develop different SEM models for the city. Along with stated preferences, the effect of three latent variables on SQ is analyzed. Among the developed models, the best model is selected by using different statistical approaches. With the best model, selected attributes are rated according to their relative importance on SQ. Acknowledging limited resources of a developing nation, this study gives a clear way ahead to planners, operating companies and transport managers to design appropriate transport policies which will ensure more effective services to current bus users as well as attracting new passengers.