Forecasting Paratransit Ridership Using Discrete Choice Models with Explicit Consideration of Availability

Abstract

In most developed countries, the population of the elderly and disabled is growing rapidly. These individuals require transportation service suited to their needs. Such service may be provided by applying emerging technologies to dial-a-ride transit. This research develops a methodology to quantitatively evaluate the impact of paratransit services on a traveler’s mode choice behavior. The mode choice model explicitly considers availability of alternative modes and includes latent factors to account for taste heterogeneity. Stated preferences are also used to elicit preferences for new paratransit services. The methodology is empirically tested with data collected in Winston-Salem, North Carolina. The model system developed is applied to evaluate the effect of improving service attributes and the impact of the introduction of new cost-effective modes on modal shares. Results of the policy analysis indicate that ( a) transit policy changes, such as fare reduction, would have little effect on automobile driver and automobile passenger shares; ( b) an improved reservation system for dial-a-ride services would produce shifts in mode share; ( c) the proposed new bus deviation service was favored; ( d) free bus service reduces dial-a-ride share; and ( e) an increase in awareness of a dial-a-ride system would significantly increase its share.

Joint models of attitudes and behavior in evaluation of the San Diego I-15 congestion pricing project

“…In most of these models, both choice behavior and attitude in the form of preference is assumed to be a function of attitudes in the form of perceptions, with no possibility of causal links from preferences and revealed choices 3 back to perceptions (e.g., Benjamin, et al, 1998). This is at odds with evidence from previous studies, which has identified links from behavior to attitudes are at least as strong as links from attitudes to behavior.…”

“…The need to use special estimation methods designed for discrete-choice endogenous variables has been long recognized in travel demand modeling and in attitude-behavior models in particular (e.g., Lyon, 1981a,b;Benjamin, et al, 1998). However, the same consideration has not been given to attitudes as endogenous functions of personal and situational variables, and as potential endogenous functions of choice.…”

“…It is well established in psychometrics that these are ordinal, not interval, measurement scales (Coombs, 1964(Coombs, , 1976Siegel, 1956;Stevens, 1946Stevens, , 1951. However, with some exceptions (Benjamin, et al, 1998 andGolob andHensher, 1998), attitudinal variables are generally assumed to be interval-scaled continuous variables in attitude-behavior models (e.g., as in Bernardino and Ben-Akiva (1996) and Lyon, 1981a,b), and this must lead to biases in hypothesis testing. The method used in the present research attempts to avoid these biases.…”

A Structural Equations Analysis of Revealed and Stated Travel Mode and Activity Choices

“…perception, attitude, preference) in choice model. This framework was applied to model the complex decision-making process of mode and activity choices and their interaction in simultaneous equations (Ben-Akiva et al, 1996;Benjamin et al, 1999). Morikawa et al (2002) and Johansson et al (2006) include latent variables representing various personal attitudes and preferences in an analysis of mode choice.…”

Impacts of Transportation External Cost Pricing and Transit Fare Reductions on Household Mode/Route Choices and Environmental Improvements

“…Meanwhile, subsidies for transit operators can be transferred to passengers, thereby reducing rail transit fares and increasing the attractiveness of rail transit. Some studies analyzed the influences of bus or transit fare changes on traveler mode choice behavior, ridership, and operator revenues ͑e.g., Benjamin et al 1998;Taylor and Carter 1998;Ling 1998͒. Reducing public transportation fares is a transparent strategy for travelers since it allows travelers to know their total travel costs before making their trips.…”