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Unravel the impact of COVID-19 on the spatio-temporal mobility patterns of microtransit

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  • Zhou, Yirong
  • Liu, Xiaoyue Cathy
  • Grubesic, Tony

Abstract

Shared mobility is an essential component of the larger sharing economy. Ride-hailing, bike-sharing, e-scooters, and other types of shared mobility continue to grow worldwide. Among these services is microtransit, a new transport mode that extends transit coverage within a region. Mobile devices enable microtransit services, aggregating riders and using real-time routing algorithms to group customers traveling in similar directions. Meanwhile, the newly emerged coronavirus, COVID-19, has radically reshaped the ridership behavior of all transit services, including microtransit. While existing research evaluates the performance of microtransit pilot programs before the pandemic, there is no information concerning the spatio-temporal pattern of microtransit activities under the impact of COVID-19. The purpose of this paper is to apply eigendecomposition and k-clique percolation methods to uncover the spatio-temporal patterns of microtransit trips. Further, we used these approaches to identify underlying communities using data from a pilot program in Salt Lake City, Utah. The resulting research offers insight into how COVID-19 altered travel behavior. Specifically, eigendecomposition delineated the homogeneity and heterogeneity of travel patterns across temporal dimensions. We identified first mile/last mile trips as a major source of variance in both pre- and post-COVID periods and that transit-dependent users prove to be inelastic despite the threat of COVID-19. The k-clique percolation method detected possible community formations and tracked how these communities evolved during the pandemic. In addition, we systematically analyzed overlapping communities and the network structure around shared nodes by using a clustering coefficient. The workflow developed in this research broadly is generalizable and valuable for understanding the unique spatio-temporal patterns of microtransit. The framework can also help transit agencies with performance evaluation, regional transport strategies, and optimal vehicle dispatching.

Suggested Citation

  • Zhou, Yirong & Liu, Xiaoyue Cathy & Grubesic, Tony, 2021. "Unravel the impact of COVID-19 on the spatio-temporal mobility patterns of microtransit," Journal of Transport Geography, Elsevier, vol. 97(C).
    • Handle: RePEc:eee:jotrge:v:97:y:2021:i:c:s0966692321002799
    DOI: 10.1016/j.jtrangeo.2021.103226
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    References listed on IDEAS

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    1. Muntaser Mohamed Nuttah & Paolo Roma & Giovanna Lo Nigro & Giovanni Perrone, 2024. "The Short- and Long-Term Impacts of COVID-19 Pandemic on the Sharing Economy: Distinguishing Between “Symptomatic” and “Asymptomatic” Platforms," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 9238-9287, June.
    2. Moncayo-Unda, Milton Giovanny & Van Droogenbroeck, Marc & Saadi, Ismaïl & Cools, Mario, 2023. "A longitudinal analysis of the COVID-19 effects on the variability in human activity spaces in Quito, Ecuador," Journal of Transport Geography, Elsevier, vol. 113(C).
    3. Bonner, Taylor & Miller-Hooks, Elise, 2023. "Achieving equitable outcomes through optimal design in the development of microtransit zones," Journal of Transport Geography, Elsevier, vol. 112(C).
    4. Rath, Srushti & Liu, Bingqing & Yoon, Gyugeun & Chow, Joseph Y.J., 2023. "Microtransit deployment portfolio management using simulation-based scenario data upscaling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    5. Song, Jie & Zhang, Liye & Qin, Zheng & Ramli, Muhamad Azfar, 2022. "Spatiotemporal evolving patterns of bike-share mobility networks and their associations with land-use conditions before and after the COVID-19 outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    6. Rauf Ahmed Shams Malick & Syed Kashir Hasan & Fahad Samad & Nadeem Kafi Khan & Hassan Jamil Syed, 2023. "Smart Methods to Deal with COVID-19 at University-Level Institutions Using Social Network Analysis Techniques," Sustainability, MDPI, vol. 15(6), pages 1-17, March.

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