Examining the nonlinear effects of neighborhood housing + transportation affordability on shared dockless e-scooter trips using machine learning approach-Reference-Cited by-同舟云学术

Examining the nonlinear effects of neighborhood housing + transportation affordability on shared dockless e-scooter trips using machine learning approach

Published:2023-11-22 Issue: Volume: Page:
ISSN:0049-4488
Container-title:Transportation
language:en
Short-container-title:Transportation

Author:

Yang Wookjae^ORCID,Ewing Reid^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Transportation,Development,Civil and Structural Engineering

Link

https://link.springer.com/content/pdf/10.1007/s11116-023-10448-3.pdf

Reference45 articles.

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2. Abouelela, M., Haddad, A.C., Antoniou, C.: Are young users willing to shift from carsharing to scooter-sharing? Transp. Res. PART D-TRANSPORT Environ. 95 (2021). https://doi.org/10.1016/j.trd.2021.102821

3. Acevedo-Garcia, D., McArdle, N., Hardy, E., Dillman, K.-N.N., Reece, J., Crisan, U.I., Norris, D., Osypuk, T.L.: Neighborhood opportunity and location affordability for low-income renter families. Hous. Policy Debate. 26(4–5), 607–645 (2016). https://doi.org/10.1080/10511482.2016.1198410

4. Badia, H., Jenelius, E.: Shared e-scooter micromobility: Review of use patterns, perceptions and environmental impacts. Transp. Reviews. (2023). https://doi.org/10.1080/01441647.2023.2171500

5. Bai, S., Jiao, J.: Dockless e-scooter usage patterns and urban built environments: A comparison study of Austin, TX, and Minneapolis, M.N. Travel Behav. Soc. 20, 264–272 (2020). https://doi.org/10.1016/j.tbs.2020.04.005