preprints.org > engineering > civil engineering > doi: 10.20944/preprints202408.0844.v1 (registering DOI)

Preprint Article Version 1 This version is not peer-reviewed

Version 1 : Received: 9 August 2024 / Approved: 12 August 2024 / Online: 12 August 2024 (23:40:35 CEST)

[3:46 PM] Anahita Zahertar This research explores the factors influencing bikeshare 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 bikeshare 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 $5 Access Pass, a free one-month pass during the pandemic, and the introduction of new stations have been more likely to encourage longer rides c) furthermore, the study examines how 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 bikeshare system efficiency and meet diverse community needs. This study not only deepens our understanding of urban mobility dynamics but also underscores the effectiveness of adaptive strategies in promoting sustainable urban transportation.

bikeshare; covid-19 ; survivalanalysis; urbanmobility; riderbehavior

Engineering, Civil Engineering

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