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Shifting Mobility Behaviors in Unprecedented Times: A Multigroup MIMIC Model Investigating Intentions to Use
Maher Said1, Jason Soria1, Amanda Stathopoulos1
1Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL.
Abstract:
The spread of COVID-19 has been a major disruptive force in people's everyday lives and mobility behavior. The demand for on-demand ride services, such as taxis and ridehailing, has been specifically affected given both restrictions in service operations and users' concerns about virus transmission in shared vehicles. In the early months of the pandemic, demand for these modes decreased by as much as 80%. This study examines intentions to use on-demand ride services in the early lockdown stage of the pandemic in the United States, a period of unprecedented mobility reductions, changing household routines and transforming travel behaviors. Using data from a survey disseminated in June 2020 to 700 U.S. respondents, we use multigroup MIMIC (Multiple Indicator Multiple Cause) models to investigate the stated shift in intentions to use on-demand modes of travel. By using group-based segmentation we control for variation in ridership intentions according to personal, household, attitudinal factors, and pandemic experiences. The results point to a reduction across the board in the likelihood of using on-demand mobility associated with a significant COVID-19 effect. Beyond this general decrease, several groups are found to have more positive intentions, including younger adults, urban residents, graduate-degree holders, and people of Hispanic, Latino, Asian, and Pacific Islander ethnicities/races. The attitudinal effect of "tech-savviness" drives higher user intentions, revealing indirect effects of gender, education, and age. Multigroup analysis provides further evidence of potential COVID-triggered shifts in on-demand ridership intentions. The most significant drops in likelihood are observed for younger respondents (below 45), Black compared with all other racial/ethnic status, and for past users of on-demand mobility. This latter result is somewhat surprising, as riders who are younger and more experienced with on-demand travel are more likely to have been users in the past, but also more likely to reduce use during the pandemic. To conclude, we discuss the need to investigate pandemic experiences, risk attitudes, and circumstances to understand evolving mobility behavior and specific service model impacts.
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