Understanding future mode choice intentions of transit riders


Andre Carrel* and Joan L. Walker**

*Dept. of Civil, Environmental and Geodetic Engineering, The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, Columbus, OH 43210, USA
T: +1.614.292.2771
E: carrel.20@osu.edu

**Dept. of Civil and Environmental Engineering, University of California at Berkeley, 111 McLaughlin Hall, Berkeley, CA 94720, USA
T: +1.510.642.6897
E: joanwalker@berkeley.edu

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This paper empirically investigates the causes for transit use cessation, focusing on the influence of users’ personal experiences, resulting levels of satisfaction, and subsequent behavioral intentions. It builds on a novel data set in which observed, objective measures of travel times are mapped to smartphone-based surveys where participants assess their travel experience. An integrated choice and latent variable model is developed to explain the influence of satisfaction with operations (travel times) and satisfaction with the travel environment (e.g., crowding) on behavioral intentions. Satisfaction is modeled as a latent variable, and the choice consists of participants’ stated desire and intention to continue using public transportation. The results show how delays, in particular in-vehicle delays but also transfer times and being left behind at stops, contribute to passengers’ intentions to cease transit use. Furthermore, a number of critical incidents, i.e., particularly memorable negative experiences, are found to have negative and significant effects on overall satisfaction and on willingness to continue using public transportation. The usefulness of the framework is demonstrated in a set of simulations in which the effect of three types of delays on passengers’ willingness to remain transit riders is modeled. This work highlights the value and potential of using new data collection methods to gain insights on complex behavioral processes, and it is intended to form the basis for new modeling tools to understand the causes of transit use cessation and the impact of various strategies and service quality improvements to reduce ridership turnover.

Keywords: Latent Variable Choice Model, Mode Choice, Public Transportation, Rider Loyalty, Satisfaction, Service Quality.