<p>App-based mobility services have changed how we travel in the urban environment, with ride-hailing being one of the most successful examples. The rate of people choosing to pool their hailed trips is still meager despite pooling’s environmental and economic benefits, and the number of materialized pooling trips is even lower. This is especially reflected by the American ride-hailing scene, which became the focus of this study. Using 300 million individual ride-hailing trips from Chicago, IL, and a data-driven approach, this research investigated factors impacting users’ willingness to pool (WTPool) and materialization of ride-pooling trips, considering the impacts of the COVID-19 pandemic. We also developed a systematic methodology to model large, high-dimensional datasets using backward stepwise binary logistic regression and Lasso regression. Various potential factors were investigated, including trip characteristics, meteorological conditions, land use, trips’ spatial and temporal characteristics, transit density, and crime rate. We identified factors driving WTPool and its subsequent success in pre- and post-outbreak contexts. Trip fare and distance, temporal attributes, and weather remain influential in both outcomes; the magnitude and direction of effects could change depending on the pandemic context. This paper also discovered that pandemic-related variables—such as the hospitalization and death rates—might significantly impact willingness to pool and pooling success post-outbreak. Other findings included the potential effects of additional taxation on specific city zones on encouraging users to pool, and how it could be a policy instrument to increase the number of pooled trips. At the same time, the built environment, sociodemographic attributes, and crime rate pose little to no impact.</p>

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What makes us pool our rides within and out of a pandemic context: evidence from Chicago

  • Merindha Arty Sekardani,
  • Mohamed Abouelela,
  • Constantinos Antoniou

摘要

App-based mobility services have changed how we travel in the urban environment, with ride-hailing being one of the most successful examples. The rate of people choosing to pool their hailed trips is still meager despite pooling’s environmental and economic benefits, and the number of materialized pooling trips is even lower. This is especially reflected by the American ride-hailing scene, which became the focus of this study. Using 300 million individual ride-hailing trips from Chicago, IL, and a data-driven approach, this research investigated factors impacting users’ willingness to pool (WTPool) and materialization of ride-pooling trips, considering the impacts of the COVID-19 pandemic. We also developed a systematic methodology to model large, high-dimensional datasets using backward stepwise binary logistic regression and Lasso regression. Various potential factors were investigated, including trip characteristics, meteorological conditions, land use, trips’ spatial and temporal characteristics, transit density, and crime rate. We identified factors driving WTPool and its subsequent success in pre- and post-outbreak contexts. Trip fare and distance, temporal attributes, and weather remain influential in both outcomes; the magnitude and direction of effects could change depending on the pandemic context. This paper also discovered that pandemic-related variables—such as the hospitalization and death rates—might significantly impact willingness to pool and pooling success post-outbreak. Other findings included the potential effects of additional taxation on specific city zones on encouraging users to pool, and how it could be a policy instrument to increase the number of pooled trips. At the same time, the built environment, sociodemographic attributes, and crime rate pose little to no impact.