Impacts of Spatiotemporal and COVID-19 Factors on Bike-Share Ride Duration in Detroit

Abstract

This research explores the factors influencing bike-share usage durations in the Detroit Metropolitan Area over two years, focusing on spatial, temporal, and COVID-19-related variables. Using a fully parametric hazard-based duration model with random parameters, we address data heterogeneity and uncover how different conditions affect bike-share trips. Our findings reveal that (a) intense environmental factors such as high traffic stress, poor weather, and high COVID-19 risk levels are associated with shorter trip durations; (b) in contrast, supportive initiatives like memberships, an affordable USD 5 Access Pass, a free one-month pass during the pandemic, and the introduction of new stations are more likely to encourage longer rides; (c) variables like gym closures due to the pandemic, evening hours, and the addition of new stations, which were set as random variables in our model, exhibit both positive and negative relationships with ride durations. A key finding is the 20-minute mark in ride durations, which helps understand user behaviors and trip purposes. This insight aids urban planning by suggesting strategic bike station placements to enhance bike-share system efficiency and meet diverse community needs. Moreover, the pandemic and related policy responses have clearly impacted user behaviors, showing the necessity for adaptable urban transportation strategies in response to external crises. This study not only deepens our understanding of urban mobility dynamics but also underscores the effectiveness of adaptive strategies in promoting sustainable urban transportation.

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