Evaluating transit mode choice in the context of the COVID-19 pandemic – A stated preference approach

Abstract

The COVID-19 pandemic and its accompanying restrictions reduced travel demand globally. Public transit ridership was significantly affected, causing transit agencies to lose fare revenue and reduce service. Although transit ridership has recovered significantly since the worst of the pandemic, it is still reduced in many cities. Transit agencies can benefit from understanding how to increase post-pandemic mode share and prepare for future health crises. This paper presents the design and findings of a stated preference (SP) survey conducted in Calgary, Canada to investigate the effects of different safety measures, pandemic risk levels, transit service characteristics, crowding, and demographics on the attractiveness of transit. SP scenarios were generated using Bayesian D-efficient design and were pivoted on respondents’ answers to previous questions. A multinomial logit model and a mixed logit model were estimated using the survey results. The model estimations show that transit agencies can attract riders by implementing mandatory masking policies and reducing in-vehicle crowding. Safety policies such as backdoor boarding and daily deep cleaning are unlikely to attract riders to transit. Higher pandemic risk levels, as measured by the daily number of cases in the study area, decrease the attractiveness of transit. Females and older respondents perceived transit modes as less attractive compared to males and younger respondents. Respondents who had been at least partially vaccinated perceived transit as more attractive compared to those who were unvaccinated. The results of this project can guide transit agencies in the event of future pandemics or health crises.