IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v92y2021ics0966692321000697.html
   My bibliography  Save this article

Spatial analysis of shared e-scooter trips

Author

Listed:
  • Hosseinzadeh, Aryan
  • Algomaiah, Majeed
  • Kluger, Robert
  • Li, Zhixia

Abstract

Shared e-scooters have become a common mode of transportation in many cities around the world. E-sooters provide convenient and quick rides for short distances and can act as a connection for first/last mile trips. To date, limited studies have explored the spatial variation of e-scooter trips and there is knowledge to be gained by investigating variables associated with e-scooter trip generation. This study implemented a spatial analysis approach, Geographical Weighted Regression (GWR), to explore how factors relating to demographics, density, diversity, design, urbanism scores, distance to transit and other transportation-related variables influence e-scooter trips in Louisville, KY. More than 400,000 e-scooter trips across 159 Traffic Analysis Zones (TAZs) were included in the study. Results show TAZ-level factors including land use, age distribution, gender distribution, Walk Score and Park Score impacted the density of e-scooters trips in the TAZ. The GWR model showed improvements over a global Ordinary Least Squares (OLS) model. Local goodness of fit ranged from 0.732–0.895 across the study area. This study can help governments and e-scooter sharing companies develop policies that maximize e-scooter use, equity, and accessibility while improving the mobility of cities.

Suggested Citation

  • Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
  • Handle: RePEc:eee:jotrge:v:92:y:2021:i:c:s0966692321000697
    DOI: 10.1016/j.jtrangeo.2021.103016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692321000697
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.jtrangeo.2021.103016?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. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Cervero, R. & Duncan, M., 2003. "Walking, Bicycling, and Urban Landscapes: Evidence from the San Francisco Bay Area," American Journal of Public Health, American Public Health Association, vol. 93(9), pages 1478-1483.
    3. Lazarus, Jessica & Pourquier, Jean Carpentier & Feng, Frank & Hammel, Henry & Shaheen, Susan, 2020. "Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco," Journal of Transport Geography, Elsevier, vol. 84(C).
    4. Lazarus, Jessica & Pourquier, Jean Carpentier & Feng, Frank & Hammel, Henry & Shaheen, Susan, 2020. "Micromobility evolution and expansion: Understanding how docked and dockless bikesharing models complement and compete – A case study of San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt96g9c9nd, Institute of Transportation Studies, UC Berkeley.
    5. 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.
    6. Hosseinzadeh, Aryan & Baghbani, Asiye, 2020. "Walking Trip Generation and Built Environment: A Comparative Study on Trip Purposes," MPRA Paper 109025, University Library of Munich, Germany.
    7. Shaheen, Susan PhD & Cohen, Adam & Chan, Nelson & Bansal, Apaar, 2020. "Chapter 13 - Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0z9711dw, Institute of Transportation Studies, UC Berkeley.
    8. Cao, Xinyu, 2006. "The Causal Relationship between the Built Environment and Personal Travel Choice: Evidence from Northern California," University of California Transportation Center, Working Papers qt07q5p340, University of California Transportation Center.
    9. Yu, Haitao & Peng, Zhong-Ren, 2019. "Exploring the spatial variation of ridesourcing demand and its relationship to built environment and socioeconomic factors with the geographically weighted Poisson regression," Journal of Transport Geography, Elsevier, vol. 75(C), pages 147-163.
    10. Cervero, Robert & Duncan, Michael, 2003. "Walking, Bicycling, and Urban Landscapes: Evidence from the San Francisco Bay Area," University of California Transportation Center, Working Papers qt6zr1x95m, University of California Transportation Center.
    11. Chiou, Yu-Chiun & Jou, Rong-Chang & Yang, Cheng-Han, 2015. "Factors affecting public transportation usage rate: Geographically weighted regression," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 161-177.
    12. Younes, Hannah & Zou, Zhenpeng & Wu, Jiahui & Baiocchi, Giovanni, 2020. "Comparing the Temporal Determinants of Dockless Scooter-share and Station-based Bike-share in Washington, D.C," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 308-320.
    13. Gehrke, Steven R. & Wang, Liming, 2020. "Operationalizing the neighborhood effects of the built environment on travel behavior," Journal of Transport Geography, Elsevier, vol. 82(C).
    14. Itf, 2019. "New Directions for Data-Driven Transport Safety," International Transport Forum Policy Papers 83, OECD Publishing.
    15. Gutiérrez, Javier & Cardozo, Osvaldo Daniel & García-Palomares, Juan Carlos, 2011. "Transit ridership forecasting at station level: an approach based on distance-decay weighted regression," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1081-1092.
    16. Bree, Sarah & Fuller, Daniel & Diab, Ehab, 2020. "Access to transit? Validating local transit accessibility measures using transit ridership," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 430-442.
    17. Yang, Hongtai & Lu, Xiaozhao & Cherry, Christopher & Liu, Xiaohan & Li, Yanlai, 2017. "Spatial variations in active mode trip volume at intersections: a local analysis utilizing geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 64(C), pages 184-194.
    18. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    19. 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.
    20. Huang, Yuan & Wang, Xiaoguang & Patton, David, 2018. "Examining spatial relationships between crashes and the built environment: A geographically weighted regression approach," Journal of Transport Geography, Elsevier, vol. 69(C), pages 221-233.
    21. Jorge García Álvarez & Miguel Ángel González & Camino Rodríguez Vela & Ramiro Varela, 2018. "Electric Vehicle Charging Scheduling by an Enhanced Artificial Bee Colony Algorithm," Energies, MDPI, vol. 11(10), pages 1-19, October.
    22. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Teller, David, 2020. "Study design impacts on built environment and transit use research," Journal of Transport Geography, Elsevier, vol. 82(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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. 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).
    3. 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.
    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. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    6. Bretones, Alexandra & Marquet, Oriol, 2022. "Sociopsychological factors associated with the adoption and usage of electric micromobility. A literature review," Transport Policy, Elsevier, vol. 127(C), pages 230-249.
    7. Zhu, Rui & Kondor, Dániel & Cheng, Cheng & Zhang, Xiaohu & Santi, Paolo & Wong, Man Sing & Ratti, Carlo, 2022. "Solar photovoltaic generation for charging shared electric scooters," Applied Energy, Elsevier, vol. 313(C).
    8. Samadzad, Mahdi & Nosratzadeh, Hossein & Karami, Hossein & Karami, Ali, 2023. "What are the factors affecting the adoption and use of electric scooter sharing systems from the end user's perspective?," Transport Policy, Elsevier, vol. 136(C), pages 70-82.
    9. 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.
    10. Elena Carrara & Rebecca Ciavarella & Stefania Boglietti & Martina Carra & Giulio Maternini & Benedetto Barabino, 2021. "Identifying and Selecting Key Sustainable Parameters for the Monitoring of e-Powered Micro Personal Mobility Vehicles. Evidence from Italy," Sustainability, MDPI, vol. 13(16), pages 1-22, August.
    11. Hosseinzadeh, Aryan & Baghbani, Asiye, 2020. "Walking Trip Generation and Built Environment: A Comparative Study on Trip Purposes," MPRA Paper 109025, University Library of Munich, Germany.
    12. 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).
    13. 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.
    14. 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).

    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. Meng, Si'an & Brown, Anne, 2021. "Docked vs. dockless equity: Comparing three micromobility service geographies," Journal of Transport Geography, Elsevier, vol. 96(C).
    2. 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).
    3. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    4. Cheng, Long & Huang, Jie & Jin, Tanhua & Chen, Wendong & Li, Aoyong & Witlox, Frank, 2023. "Comparison of station-based and free-floating bikeshare systems as feeder modes to the metro," Journal of Transport Geography, Elsevier, vol. 107(C).
    5. Samadzad, Mahdi & Nosratzadeh, Hossein & Karami, Hossein & Karami, Ali, 2023. "What are the factors affecting the adoption and use of electric scooter sharing systems from the end user's perspective?," Transport Policy, Elsevier, vol. 136(C), pages 70-82.
    6. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    7. Nigro, Marialisa & Castiglione, Marisdea & Maria Colasanti, Fabio & De Vincentis, Rosita & Valenti, Gaetano & Liberto, Carlo & Comi, Antonio, 2022. "Exploiting floating car data to derive the shifting potential to electric micromobility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 78-93.
    8. 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.
    9. Marta Borowska-Stefańska & Michał Kowalski & Paulina Kurzyk & Alireza Sahebgharani & Szymon Wiśniewski, 2022. "Spatiotemporal Changeability of the Load of the Urban Road Transport System under Permanent and Short-Term Legal and Administrative Retail Restrictions," Sustainability, MDPI, vol. 14(9), pages 1-30, April.
    10. Du, Qiang & Zhou, Yuqing & Huang, Youdan & Wang, Yalei & Bai, Libiao, 2022. "Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership," Journal of Transport Geography, Elsevier, vol. 102(C).
    11. Zhao, Chunli & Nielsen, Thomas Alexander Sick & Olafsson, Anton Stahl & Carstensen, Trine Agervig & Meng, Xiaoying, 2018. "Urban form, demographic and socio-economic correlates of walking, cycling, and e-biking: Evidence from eight neighborhoods in Beijing," Transport Policy, Elsevier, vol. 64(C), pages 102-112.
    12. Fei-Hui Huang, 2021. "User Behavioral Intentions toward a Scooter-Sharing Service: An Empirical Study," Sustainability, MDPI, vol. 13(23), pages 1-21, November.
    13. Li, Shaoying & Lyu, Dijiang & Huang, Guanping & Zhang, Xiaohu & Gao, Feng & Chen, Yuting & Liu, Xiaoping, 2020. "Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 82(C).
    14. Bach, Xavier & Marquet, Oriol & Miralles-Guasch, Carme, 2023. "Assessing social and spatial access equity in regulatory frameworks for moped-style scooter sharing services," Transport Policy, Elsevier, vol. 132(C), pages 154-162.
    15. Ha Na Im & Chang Gyu Choi, 2020. "Measuring pedestrian volume by land use mix: Presenting a new entropy-based index by weighting walking generation units," Environment and Planning B, , vol. 47(7), pages 1219-1236, September.
    16. Emine Coruh & Faruk Urak & Abdulbaki Bilgic & Steven T. Yen, 2022. "The role of household demographic factors in shaping transportation spending in Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 3485-3517, March.
    17. 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.
    18. Steve O’Hern & Nora Estgfaeller, 2020. "A Scientometric Review of Powered Micromobility," Sustainability, MDPI, vol. 12(22), pages 1-21, November.
    19. 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.
    20. Regine Gerike & Caroline Koszowski & Bettina Schröter & Ralph Buehler & Paul Schepers & Johannes Weber & Rico Wittwer & Peter Jones, 2021. "Built Environment Determinants of Pedestrian Activities and Their Consideration in Urban Street Design," Sustainability, MDPI, vol. 13(16), pages 1-21, August.

    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:92:y:2021:i:c:s0966692321000697. 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.