4.7 Article

Do built environment factors have different effects on ridesourcing usage before and after the COVID-19 pandemic?

Journal

CITIES
Volume 141, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.cities.2023.104520

Keywords

Ridesourcing; Travel behavior analysis; COVID-19; Generalized additive mixed models (GAMMs); Nonlinearity; Shared mobility

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The objective of this research is to understand the impact of COVID-19 on ridesourcing usage and how it has changed the effects of built environment factors. The study shows that COVID-19 has long-term effects on ridesourcing usage in Chicago and the influence of built environment factors has also changed in the post-pandemic era. Therefore, relevant policies and land-use interventions should be updated.
Ridesourcing has undergone a magnificent development pre pandemic and has had a transformative impact on travel behavior and urban mobility. While an individual's travel behavior has been found to be inevitably influenced by the pandemic, how COVID-19 influences the utilization of ridesourcing has rarely been discussed in previous studies. Understanding how COVID-19 has reshaped people's ridesourcing usage may also be helpful for providing updated policy implications in the post-pandemic era. The objective of this research is to investigate the extent to which the impact of the built environment on the utilization of ridesourcing has changed post pandemic, as compared to pre-pandemic period. This study analyzes the spatiotemporal difference in ride sourcing usage before and after the pandemic, and the differential impacts of built environment factors on ridesourcing usage using real-world trip data in Chicago. Generalized additive mixed models (GAMMs) are applied to analyze the nonlinear built environment effects on ridesourcing usage. Results show average ride sourcing usage in the post-pandemic period failed to recover to pre-pandemic trip volumes by June 2022. There are significant differences in the effects of population density, intersection density, land use mix, population employment balance index, and bus accessibility on ridesourcing pick-up usage between the post-pandemic and pre-pandemic periods. For example, population density had an overall positive effect pre pandemic. However, a significant negative effect was observed in areas with extremely high population density post pandemic. The positive effect of land use mix before the pandemic also turns into a negative effect after the pandemic. It seems that COVID-19 is having long-term effects on ridesourcing usage, at least in Chicago. Relevant policies and tailored land-use interventions should be updated regarding the differentiated built environment effects in the post-pandemic era.

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