https://orcid.org/0000-0002-5463-6202
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ABSTRACT
Unlike driving alone, public transportation allows one to engage in extraneous activities while traveling – often referred to as travel-based multitasking. Research involving travel-based multitasking often relies on either generic (i.e. not related to an actual trip) or revealed (i.e. related to an executed trip) data. The data collected for this study provided a unique opportunity to compare the generic and trip-specific preferences while traveling on public transportation. To this end, the study develops two integrated choice and latent variable models with multiple discrete-continuous (MDC) kernels to simultaneously model the activity selection and the time allocation for generic and trip-specific data, respectively. According to the results the trip-specific data could identify more nuances in the travel-based multitasking behavior than the generic data. The heterogeneity identified by the developed models will be helpful for the transit operators in providing appropriate facilities (e.g. internet access, reading lights) along various transit corridors.
Acknowledgments
The data for this work was collected under a grant from the Federal Transit Administration awarded to the University of Chicago in December 2016 (IL-26-7015-01 – Coordinated Transit Response Planning). The authors appreciate the constructive comments of the three anonymous reviewers, which helped improve the quality of the paper.
Disclosure statement
No potential conflict of interest was reported by the authors.
Declarations
The first author will make the code available upon appropriate request. On behalf of all authors, the corresponding author states that there is no conflict of interest.