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Why do people take e-scooter trips? Insights on temporal and spatial usage patterns of detailed trip data

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  • Shah, Nitesh R.
  • Guo, Jing
  • Han, Lee D.
  • Cherry, Christopher R.

Abstract

Electric scooters (e-scooters) are becoming one of the most popular micromobility options in the United States. Although there is some evidence of increased mobility, reduced carbon emissions, replaced car trips, and associated public health benefits, there is little known about the patterns of e-scooter use. This study proposes a framework for high-resolution analysis of micromobility data based on temporal, spatial, and weather attributes. As a case study, we scrutinized more than one million e-scooter trips of Nashville, Tennessee, from September 1, 2018, to August 31, 2019. Weather data and land use data from the Nashville Travel Demand Model and scraping of Google Maps Point of Interest (POI) data complemented the trip data. The combination of Principal Component Analysis (PCA) and a K-means unsupervised machine learning algorithm identified five distinct e-scooter usage patterns, namely morning work/school, daytime short errand, social, nighttime entertainment district, and utilitarian trips.

Suggested Citation

  • Shah, Nitesh R. & Guo, Jing & Han, Lee D. & Cherry, Christopher R., 2023. "Why do people take e-scooter trips? Insights on temporal and spatial usage patterns of detailed trip data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    • Handle: RePEc:eee:transa:v:173:y:2023:i:c:s0965856423001258
    DOI: 10.1016/j.tra.2023.103705
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    References listed on IDEAS

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    1. Foissaud, Nicolas & Gioldasis, Christos & Tamura, Shun & Christoforou, Zoi & Farhi, Nadir, 2022. "Free-floating e-scooter usage in urban areas: A spatiotemporal analysis," Journal of Transport Geography, Elsevier, vol. 100(C).
    2. McKenzie, Grant, 2019. "Spatiotemporal comparative analysis of scooter-share and bike-share usage patterns in Washington, D.C," Journal of Transport Geography, Elsevier, vol. 78(C), pages 19-28.
    3. Shaheen, Susan PhD & Cohen, Adam, 2019. "Shared Micromoblity Policy Toolkit: Docked and Dockless Bike and Scooter Sharing," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt00k897b5, Institute of Transportation Studies, UC Berkeley.
    4. Prillwitz, Jan & Barr, Stewart, 2011. "Moving towards sustainability? Mobility styles, attitudes and individual travel behaviour," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1590-1600.
    5. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan PhD, 2016. "Just A Better Taxi? A Survey-Based Comparison of Taxis, Transit, and Ridesourcing Services in San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt60v8r346, Institute of Transportation Studies, UC Berkeley.
    6. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2015. "Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system," Journal of Transport Geography, Elsevier, vol. 44(C), pages 53-64.
    7. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    8. Rayle, Lisa & Dai, Danielle & Chan, Nelson & Cervero, Robert & Shaheen, Susan, 2016. "Just a better taxi? A survey-based comparison of taxis, transit, and ridesourcing services in San Francisco," Transport Policy, Elsevier, vol. 45(C), pages 168-178.
    9. Fitt, Helen & Curl, Angela, 2020. "The early days of shared micromobility: A social practices approach," Journal of Transport Geography, Elsevier, vol. 86(C).
    10. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
    11. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    12. Maximilian Heumann & Tobias Kraschewski & Tim Brauner & Lukas Tilch & Michael H. Breitner, 2021. "A Spatiotemporal Study and Location-Specific Trip Pattern Categorization of Shared E-Scooter Usage," Sustainability, MDPI, vol. 13(22), pages 1-24, November.
    13. Ed Manley & Chen Zhong & Michael Batty, 2018. "Spatiotemporal variation in travel regularity through transit user profiling," Transportation, Springer, vol. 45(3), pages 703-732, May.
    14. Zhang, Ying & Thomas, Tom & Brussel, Mark & van Maarseveen, Martin, 2017. "Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China," Journal of Transport Geography, Elsevier, vol. 58(C), pages 59-70.
    15. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
    16. Jie Bao & Chengcheng Xu & Pan Liu & Wei Wang, 2017. "Exploring Bikesharing Travel Patterns and Trip Purposes Using Smart Card Data and Online Point of Interests," Networks and Spatial Economics, Springer, vol. 17(4), pages 1231-1253, December.
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    1. Shah, Nitesh R. & Ziedan, Abubakr & Brakewood, Candace & Cherry, Christopher R., 2023. "Shared e-scooter service providers with large fleet size have a competitive advantage: Findings from e-scooter demand and supply analysis of Nashville, Tennessee," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    2. Yin, Zehui & Rybarczyk, Greg & Zheng, Anran & Su, Lin & Sun, Bingrong & Yan, Xiang, 2024. "Shared micromobility as a first- and last-mile transit solution? Spatiotemporal insights from a novel dataset," Journal of Transport Geography, Elsevier, vol. 114(C).
    3. Yang, Ying & Zhang, Wei & Lin, Hongyi & Liu, Yang & Qu, Xiaobo, 2024. "Applying masked language model for transport mode choice behavior prediction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 184(C).

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