IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i12p9570-d1171002.html
   My bibliography  Save this article

Influence of Dockless Shared E-Scooters on Urban Mobility: WTP and Modal Shift

Author

Listed:
  • Draženko Glavić

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Beograd, Serbia)

  • Marina Milenković

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Beograd, Serbia)

  • Aleksandar Trifunović

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Beograd, Serbia)

  • Igor Jokanović

    (Faculty of Civil Engineering, University of Novi Sad, 24000 Subotica, Serbia)

  • Jelica Komarica

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Beograd, Serbia)

Abstract

Land use largely depends on the traffic policy of a city. The appearance of e-scooters can greatly affect the visual distribution of transportation, and thus the occupation of land, primarily in the central areas of cities. E-scooters as a shared micro-mobility service have become widespread worldwide since 2017. The advent of e-scooters has made changes in travel habits, especially in the central parts of big cities. However, many issues are focused on e-scooter shared mobility management policies. One of the important issues is the price of renting an e-scooter, on which the percentage of users who use e-scooters largely depend. In order to determine willingness to pay for e-scooter dockless shared mobility, a survey was conducted in the city of Belgrade (Serbia, Europe) on the willingness of participants to use this mode of transport for commuting and other travel purposes depending on the price of renting an e-scooter. The results showed that price plays an important role in the willingness of participants to use an e-scooter. The paper presents mathematical models, which include the cost of renting an e-scooter and the percentage of participants who would accept this type of transport. These mathematical models can help a decision maker to determine the pricing policy in order to maximize the profit from renting an e-scooter, as well as to influence modal shift in order to reduce car-dependent trips.

Suggested Citation

  • Draženko Glavić & Marina Milenković & Aleksandar Trifunović & Igor Jokanović & Jelica Komarica, 2023. "Influence of Dockless Shared E-Scooters on Urban Mobility: WTP and Modal Shift," Sustainability, MDPI, vol. 15(12), pages 1-17, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9570-:d:1171002
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/12/9570/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/12/9570/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Button, Kenneth & Frye, Hailey & Reaves, David, 2020. "Economic regulation and E-scooter networks in the USA," Research in Transportation Economics, Elsevier, vol. 84(C).
    3. Nikiforiadis, Andreas & Paschalidis, Evangelos & Stamatiadis, Nikiforos & Paloka, Ntonata & Tsekoura, Eleni & Basbas, Socrates, 2023. "E-scooters and other mode trip chaining: Preferences and attitudes of university students," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    4. 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.
    5. Mina Lee & Joseph Y. J. Chow & Gyugeun Yoon & Brian Yueshuai He, 2019. "Forecasting e-scooter substitution of direct and access trips by mode and distance," Papers 1908.08127, arXiv.org, revised Apr 2021.
    6. Cláudia A. Soares Machado & Nicolas Patrick Marie De Salles Hue & Fernando Tobal Berssaneti & José Alberto Quintanilha, 2018. "An Overview of Shared Mobility," Sustainability, MDPI, vol. 10(12), pages 1-21, November.
    7. Martina Fazio & Nadia Giuffrida & Michela Le Pira & Giuseppe Inturri & Matteo Ignaccolo, 2021. "Planning Suitable Transport Networks for E-Scooters to Foster Micromobility Spreading," Sustainability, MDPI, vol. 13(20), pages 1-18, October.
    8. 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.
    9. 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.
    10. Sanders, Rebecca L. & Branion-Calles, Michael & Nelson, Trisalyn A., 2020. "To scoot or not to scoot: Findings from a recent survey about the benefits and barriers of using E-scooters for riders and non-riders," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 217-227.
    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. Kang, Seongmin & Chung, Yongjin & Yang, Byungsoo & Lee, Hyukseong & Lee, Jun & Kim, Jinhee, 2024. "User preference and willingness-to-pay for operation strategies that enhance safety and convenience of E-scooter sharing services," Transport Policy, Elsevier, vol. 146(C), pages 31-41.
    2. Chao Zeng & Xu Zhou & Li Yu & Changxi Ma, 2023. "Parking Generating Rate Prediction Method Based on Grey Correlation Analysis and SSA-GRNN," Sustainability, MDPI, vol. 15(17), pages 1-15, August.

    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. Krauss, Konstantin & Gnann, Till & Burgert, Tobias & Axhausen, Kay W., 2024. "Faster, greener, scooter? An assessment of shared e-scooter usage based on real-world driving data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    2. 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).
    3. Jin, Scarlett T. & Sui, Daniel Z., 2024. "A comparative analysis of the spatial determinants of e-bike and e-scooter sharing link flows," Journal of Transport Geography, Elsevier, vol. 119(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. Jin, Scarlett T. & Wang, Lei & Sui, Daniel, 2023. "How the built environment affects E-scooter sharing link flows: A machine learning approach," Journal of Transport Geography, Elsevier, vol. 112(C).
    6. Monika Hamerska & Monika Ziółko & Patryk Stawiarski, 2022. "A Sustainable Transport System—The MMQUAL Model of Shared Micromobility Service Quality Assessment," Sustainability, MDPI, vol. 14(7), pages 1-18, March.
    7. 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).
    8. Roig-Costa, Oriol & Miralles-Guasch, Carme & Marquet, Oriol, 2024. "Shared bikes vs. private e-scooters. Understanding patterns of use and demand in a policy-constrained micromobility environment," Transport Policy, Elsevier, vol. 146(C), pages 116-125.
    9. 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.
    10. Meng, Si'an & Brown, Anne, 2021. "Docked vs. dockless equity: Comparing three micromobility service geographies," Journal of Transport Geography, Elsevier, vol. 96(C).
    11. 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.
    12. Alberica Domitilla Bozzi & Anne Aguilera, 2021. "Shared E-Scooters: A Review of Uses, Health and Environmental Impacts, and Policy Implications of a New Micro-Mobility Service," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    13. 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.
    14. 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.
    15. Alexandra König & Laura Gebhardt & Kerstin Stark & Julia Schuppan, 2022. "A Multi-Perspective Assessment of the Introduction of E-Scooter Sharing in Germany," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    16. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    17. 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).
    18. Ouassim Manout & Azise Oumar Diallo & Thibault Gloriot, 2023. "Implications of pricing and fleet size strategies on shared bikes and e-scooters: a case study from Lyon, France," Working Papers hal-04017908, HAL.
    19. 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.
    20. 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).

    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:gam:jsusta:v:15:y:2023:i:12:p:9570-:d:1171002. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.