IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v109y2023ics0966692323000510.html
   My bibliography  Save this article

A data-driven approach to estimating dockless electric scooter service areas

Author

Listed:
  • Karimpour, Abolfazl
  • Hosseinzadeh, Aryan
  • Kluger, Robert

Abstract

With the surging usage of e-scooters worldwide, there is a growing interest in understanding different aspects of e-scooters trips and their impact on urban mobility. Further, the emergence of this new mode of transportation has led to questions regarding the spatial accessibility of e-scooters and understanding how the built environment and urbanism characteristics affect riders' abilities to reach certain destinations. In this study, initially, a data-driven approach was proposed to construct the service areas for dockless e-scooter using origin-destination trip data. Service areas are defined as spatial areas that riders are regularly able to reach via an e-scooter. E-scooter service areas were constructed for traffic analysis zones in Louisville, KY, using agglomerative hierarchical clustering and convex hull algorithms. Then, the relationship between various built environments and urbanism characteristics and the e-scooter service areas was examined using principal component analysis and random forest regression. The results showed that percent of residential properties, length of the block, Walk Score®, Transit Score ®, and Dining and Drinking Score contributed most to the size of the e-scooter service area. The findings of this research offer a transferable method to estimate e-scooter service areas to quantify access to goods and services. Further, the study discusses how the built environment and urbanism characteristics might affect the size of the service areas.

Suggested Citation

  • Karimpour, Abolfazl & Hosseinzadeh, Aryan & Kluger, Robert, 2023. "A data-driven approach to estimating dockless electric scooter service areas," Journal of Transport Geography, Elsevier, vol. 109(C).
    • Handle: RePEc:eee:jotrge:v:109:y:2023:i:c:s0966692323000510
    DOI: 10.1016/j.jtrangeo.2023.103579
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692323000510
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2023.103579?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Samira Dibaj & Aryan Hosseinzadeh & Miloš N. Mladenović & Robert Kluger, 2021. "Where Have Shared E-Scooters Taken Us So Far? A Review of Mobility Patterns, Usage Frequency, and Personas," Sustainability, MDPI, vol. 13(21), pages 1-27, October.
    2. Shixiong Jiang & Wei Guan & Zhengbing He & Liu Yang, 2018. "Measuring Taxi Accessibility Using Grid-Based Method with Trajectory Data," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    3. Nassir, Neema & Hickman, Mark & Malekzadeh, Ali & Irannezhad, Elnaz, 2016. "A utility-based travel impedance measure for public transit network accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 26-39.
    4. Wang, Kailai & Akar, Gulsah & Chen, Yu-Jen, 2018. "Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 1-14.
    5. Niedzielski, Michał A., 2021. "Grocery store accessibility: Different metrics – Different modal disparity results and spatial patterns," Journal of Transport Geography, Elsevier, vol. 96(C).
    6. Li, Zhiming & Fan, Zhengxi & Song, Yan & Chai, Yangbo, 2021. "Assessing equity in park accessibility using a travel behavior-based G2SFCA method in Nanjing, China," Journal of Transport Geography, Elsevier, vol. 96(C).
    7. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    8. Cheng, Yung-Hsiang & Chen, Ssu-Yun, 2015. "Perceived accessibility, mobility, and connectivity of public transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 386-403.
    9. 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).
    10. Fayyaz, S. Kiavash & Liu, Xiaoyue Cathy & Porter, Richard J., 2017. "Dynamic transit accessibility and transit gap causality analysis," Journal of Transport Geography, Elsevier, vol. 59(C), pages 27-39.
    11. Xiaomeng Zhu & Zhijun Tong & Xingpeng Liu & Xiangqian Li & Pengda Lin & Tong Wang, 2018. "An Improved Two-Step Floating Catchment Area Method for Evaluating Spatial Accessibility to Urban Emergency Shelters," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
    12. Javad J. C. Aman & Myriam Zakhem & Janille Smith-Colin, 2021. "Towards Equity in Micromobility: Spatial Analysis of Access to Bikes and Scooters amongst Disadvantaged Populations," Sustainability, MDPI, vol. 13(21), pages 1-15, October.
    13. Yan, Xiang & Liu, Xinyu & Zhao, Xilei, 2020. "Using machine learning for direct demand modeling of ridesourcing services in Chicago," Journal of Transport Geography, Elsevier, vol. 83(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    2. (Ato) Xu, Wangtu & Zhou, Jiangping & Yang, Linchuan & Li, Ling, 2018. "The implications of high-speed rail for Chinese cities: Connectivity and accessibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 308-326.
    3. 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).
    4. Abouelela, Mohamed & Chaniotakis, Emmanouil & Antoniou, Constantinos, 2023. "Understanding the landscape of shared-e-scooters in North America; Spatiotemporal analysis and policy insights," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    5. Kim, Junghwan & Lee, Bumsoo, 2019. "More than travel time: New accessibility index capturing the connectivity of transit services," Journal of Transport Geography, Elsevier, vol. 78(C), pages 8-18.
    6. Jairo Ortega & János Tóth & Tamás Péter, 2021. "A Comprehensive Model to Study the Dynamic Accessibility of the Park & Ride System," Sustainability, MDPI, vol. 13(7), pages 1-17, April.
    7. Sharma, Ishant & Mishra, Sabyasachee & Golias, Mihalis M. & Welch, Timothy F. & Cherry, Christopher R., 2020. "Equity of transit connectivity in Tennessee cities," Journal of Transport Geography, Elsevier, vol. 86(C).
    8. Yuyang Zhou & Minhe Zhao & Songtao Tang & William H. K. Lam & Anthony Chen & N. N. Sze & Yanyan Chen, 2020. "Assessing the Relationship between Access Travel Time Estimation and the Accessibility to High Speed Railway Station by Different Travel Modes," Sustainability, MDPI, vol. 12(18), pages 1-15, September.
    9. Kelobonye, Keone & McCarney, Gary & Xia, Jianhong (Cecilia) & Swapan, Mohammad Shahidul Hasan & Mao, Feng & Zhou, Heng, 2019. "Relative accessibility analysis for key land uses: A spatial equity perspective," Journal of Transport Geography, Elsevier, vol. 75(C), pages 82-93.
    10. Rahimi-Golkhandan, Armin & Garvin, Michael J. & Brown, Bryan L., 2019. "Characterizing and measuring transportation infrastructure diversity through linkages with ecological stability theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 114-130.
    11. Liu, Jixiang & Xiao, Longzhu, 2023. "Non-linear relationships between built environment and commuting duration of migrants and locals," Journal of Transport Geography, Elsevier, vol. 106(C).
    12. Alexandros Nikitas, 2019. "How to Save Bike-Sharing: An Evidence-Based Survival Toolkit for Policy-Makers and Mobility Providers," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    13. Tomasz Bieliński & Łukasz Dopierała & Maciej Tarkowski & Agnieszka Ważna, 2020. "Lessons from Implementing a Metropolitan Electric Bike Sharing System," Energies, MDPI, vol. 13(23), pages 1-21, November.
    14. Siqi Tang & Jianguo Wang & Yuanhao Xu & Shengbo Chen & Jiawang Zhang & Wutao Zhao & Guojian Wang, 2023. "Evaluation of Emergency Shelter Service Functions and Optimisation Suggestions—Case Study in the Songyuan City Central Area," Sustainability, MDPI, vol. 15(9), pages 1-20, April.
    15. Yong Gao & Yuanyuan Chen & Lan Mu & Shize Gong & Pengcheng Zhang & Yu Liu, 2022. "Measuring urban sentiments from social media data: a dual-polarity metric approach," Journal of Geographical Systems, Springer, vol. 24(2), pages 199-221, April.
    16. Mariano J. Rabassa & Mariana Conte Grand & Christian M. García-Witulski, 2021. "Heat warnings and avoidance behavior: evidence from a bike-sharing system," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 23(1), pages 1-28, January.
    17. Lin, Joanne Yuh-Jye & Jenelius, Erik & Cebecauer, Matej & Rubensson, Isak & Chen, Cynthia, 2023. "The equity of public transport crowding exposure," Journal of Transport Geography, Elsevier, vol. 110(C).
    18. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    19. Helai Huang & Jialing Wu & Fang Liu & Yiwei Wang, 2020. "Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data," Sustainability, MDPI, vol. 13(1), pages 1-23, December.
    20. Li, Chuanyao & Wang, Junren, 2022. "A hierarchical two-step floating catchment area analysis for high-tier hospital accessibility in an urban agglomeration region," Journal of Transport Geography, Elsevier, vol. 102(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jotrge:v:109:y:2023:i:c:s0966692323000510. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.