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Influence of the built environment on E-scooter sharing ridership: A tale of five cities

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  • Huo, Jinghai
  • Yang, Hongtai
  • Li, Chaojing
  • Zheng, Rong
  • Yang, Linchuan
  • Wen, Yi

Abstract

Electric scooter (e-scooter) sharing systems (ESSs) have been widely adopted by many cities around the world and have attracted a growing number of users. Although some studies have explored the usage characteristics and effects of the built environment on ESS ridership using one city as an example, few studies have considered multiple cities to obtain generalizable and robust results. To fill this research gap, we collect the ESS trip data of five cities in the U.S., namely Austin, Minneapolis, Kansas City, Louisville, and Portland, and explore the effects of the built environment on ESS ridership after controlling for socioeconomic factors. The temporal distributions of e-scooter ridership of different cities are similar, having a single peak period on weekdays and weekends between 11:30 and 17:30. In terms of spatial distribution, the ESS ridership is higher in universities and urban centers compared to other areas. Multilevel negative binomial model results show that ESS trips are positively correlated with population density, employment density, intersection density, land use mixed entropy, and bus stop density in the census block group. E-scooter ridership is negatively correlated with the median age of the population in the census block group and distance to the city center. The findings in this article can help operators understand the factors that affect the ridership of shared e-scooters, determine the changes in ridership when the built environment changes, and identify high-ridership areas when ESS is implemented in new cities.

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  • Huo, Jinghai & Yang, Hongtai & Li, Chaojing & Zheng, Rong & Yang, Linchuan & Wen, Yi, 2021. "Influence of the built environment on E-scooter sharing ridership: A tale of five cities," Journal of Transport Geography, Elsevier, vol. 93(C).
    • Handle: RePEc:eee:jotrge:v:93:y:2021:i:c:s096669232100137x
    DOI: 10.1016/j.jtrangeo.2021.103084
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    2. Yang, Hongtai & Huo, Jinghai & Bao, Yongxing & Li, Xuan & Yang, Linchuan & Cherry, Christopher R., 2021. "Impact of e-scooter sharing on bike sharing in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 23-36.
    3. Theodora Sorkou & Panagiotis G. Tzouras & Katerina Koliou & Lambros Mitropoulos & Christos Karolemeas & Konstantinos Kepaptsoglou, 2022. "An Approach to Model the Willingness to Use of E-Scooter Sharing Services in Different Urban Road Environments," Sustainability, MDPI, vol. 14(23), pages 1-15, November.
    4. Yang, Hongtai & Zhai, Guocong & Liu, Xiaohan & Yang, Linchuan & Liu, Yugang & Yuan, Quan, 2022. "Determinants of city-level private car ownership: Effect of vehicle regulation policies and the relative price," Transport Policy, Elsevier, vol. 115(C), pages 40-48.
    5. 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.
    6. Matteo della Mura & Serena Failla & Nicolò Gori & Alfonso Micucci & Filippo Paganelli, 2022. "E-Scooter Presence in Urban Areas: Are Consistent Rules, Paying Attention and Smooth Infrastructure Enough for Safety?," Sustainability, MDPI, vol. 14(21), pages 1-36, November.
    7. Gao, Kun & Yang, Ying & Gil, Jorge & Qu, Xiaobo, 2023. "Data-driven interpretation on interactive and nonlinear effects of the correlated built environment on shared mobility," Journal of Transport Geography, Elsevier, vol. 110(C).
    8. Liu, Hung-Chi & Lin, Jen-Jia, 2022. "Associations of built environments with spatiotemporal patterns of shared scooter use: A comparison with shared bike use," Transport Policy, Elsevier, vol. 126(C), pages 107-119.
    9. Zoi Christoforou & Christos Gioldasis & Yeltsin Valero & Grigoris Vasileiou-Voudouris, 2022. "Smart Traffic Data for the Analysis of Sustainable Travel Modes," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    10. Tyndall, Justin, 2022. "Complementarity of dockless mircomobility and rail transit," Journal of Transport Geography, Elsevier, vol. 103(C).
    11. 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).
    12. Sujae Kim & Sangho Choo & Sungtaek Choi & Hyangsook Lee, 2021. "What Factors Affect Commuters’ Utility of Choosing Mobility as a Service? An Empirical Evidence from Seoul," Sustainability, MDPI, vol. 13(16), pages 1-15, August.
    13. Yang, Hongtai & Zheng, Rong & Li, Xuan & Huo, Jinghai & Yang, Linchuan & Zhu, Tong, 2022. "Nonlinear and threshold effects of the built environment on e-scooter sharing ridership," Journal of Transport Geography, Elsevier, vol. 104(C).
    14. Kimpton, Anthony & Loginova, Julia & Pojani, Dorina & Bean, Richard & Sigler, Thomas & Corcoran, Jonathan, 2022. "Weather to scoot? How weather shapes shared e-scooter ridership patterns," Journal of Transport Geography, Elsevier, vol. 104(C).

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