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Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon

Author

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  • Rana Tarabay

    (American University of Beirut
    General Technologies and Solutions)

  • Maya Abou-Zeid

    (American University of Beirut)

Abstract

This study investigates the current and potential uptake of ridesourcing services, such as Uber and Careem, by the students of the American University of Beirut, Lebanon. A hybrid choice model is developed to predict the switching choice from traditional modes of transport to ridesourcing services for social/recreational trips made by these students in Lebanon. Data are provided by a web-based survey that includes revealed and stated preferences, besides demographics. It is found that the switching choice is determined by several observed factors, such as door-to-door travel time, waiting time for pick-up, and one-way fares, in addition to a latent variable that captures individual differences in perceptions and attitudes towards ridesourcing services. A base switching probability from traditional modes to ridesourcing services (calculated under a base scenario representing realistic values of the attributes of ridesourcing services if the latter were used to make the most recent social/recreational trip) is estimated to be 0.22. This probability is expected to reach 0.31 under a forecasted policy scenario consisting of 40% reduction in ridesourcing fares. Car users will be more sensitive to switch to ridesourcing services for their social/recreational trips if the ridesourcing fare reduction (40%) is associated with restricted parking conditions consisting of (a) 100% increase of parking fees from actual prices, and (b) 20-minute increase of parking search time and parking time from the actual car travel time. In this case, the resulting switching probability is expected to reach 0.38. By using the estimated choice model to forecast policy scenarios as such, this study can guide planners, policymakers, and service operators to prioritize effective policies in response to the behavioral change caused by the diffusion of innovative transport services and technologies. The study also contributes to a better understanding of the uptake of ridesourcing services in developing country contexts where public transport services are often inadequate.

Suggested Citation

  • Rana Tarabay & Maya Abou-Zeid, 2020. "Modeling the choice to switch from traditional modes to ridesourcing services for social/recreational trips in Lebanon," Transportation, Springer, vol. 47(4), pages 1733-1763, August.
    • Handle: RePEc:kap:transp:v:47:y:2020:i:4:d:10.1007_s11116-019-09973-x
    DOI: 10.1007/s11116-019-09973-x
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    References listed on IDEAS

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    Cited by:

    1. Tri Basuki Joewono & Ariel Matthew & Muhamad Rizki, 2021. "Loyalty of Paratransit Users in the Era of Competition with Ride Sourcing," Sustainability, MDPI, vol. 13(22), pages 1-20, November.
    2. Gustavo García-Melero & Rubén Sainz-González & Pablo Coto-Millán & Alejandra Valencia-Vásquez, 2021. "Sustainable Mobility Policy Analysis Using Hybrid Choice Models: Is It the Right Choice?," Sustainability, MDPI, vol. 13(5), pages 1-16, March.
    3. Hossain, Sanjana & Loa, Patrick & Ong, Felita & Habib, Khandker Nurul, 2022. "The determinants of commute mode usage frequency of post-secondary students in the Greater Toronto and Hamilton Area," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 164-185.
    4. Muhamad Rizki & Tri Basuki Joewono & Dimas Bayu Endrayana Dharmowijoyo & Dwi Prasetyanto, 2021. "The Effects of On- and Before- Journey Advantages Using Ride-Sourcing in Indonesia," Sustainability, MDPI, vol. 13(19), pages 1-20, October.
    5. Li, Wu & Zhao, Shengchuan & Ma, Jingwen & Nielsen, Otto Anker & Jiang, Yu, 2023. "Book-ahead ride-hailing trip and its determinants: Findings from large-scale trip records in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 178(C).
    6. Moeinaddini, Amin & Habibian, Meeghat, 2023. "Transportation demand management policy efficiency: An attempt to address the effectiveness and acceptability of policy packages," Transport Policy, Elsevier, vol. 141(C), pages 317-330.

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