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Modeling the demand for a shared-ride taxi service: An application to an organization-based context

Author

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  • Al-Ayyash, Zahwa
  • Abou-Zeid, Maya
  • Kaysi, Isam

Abstract

Traffic congestion has become a worldwide concern. One way to address this problem is to enhance the performance of the transport system by means of sound public transportation that is capable of appropriately addressing the demand of travelers, especially in highly urbanized areas of the world. The implementation of shared-ride transportation has been a viable transportation solution in many areas. The purpose of this study is to evaluate the market demand potential of a Shared-Ride Taxi (SRT) service in an organization-based context. It presents an integrated choice and latent variable modeling framework for modeling the number of times per week a Shared-Ride Taxi would be used if it were implemented at an organization. The study involves extensive analysis of practical policy scenarios through which the impact of cost incentives (subsidies) and multiple SRT attributes on travelers’ behavior is examined.

Suggested Citation

  • Al-Ayyash, Zahwa & Abou-Zeid, Maya & Kaysi, Isam, 2016. "Modeling the demand for a shared-ride taxi service: An application to an organization-based context," Transport Policy, Elsevier, vol. 48(C), pages 169-182.
    • Handle: RePEc:eee:trapol:v:48:y:2016:i:c:p:169-182
    DOI: 10.1016/j.tranpol.2016.02.013
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Saxena, Aditya & Gupta, Vallary, 2023. "Carpooling: Who is closest to adopting it? An investigation into the potential car-poolers among private vehicle users: A case of a developing country, India," Transport Policy, Elsevier, vol. 135(C), pages 11-20.
    2. Kucharski, Rafał & Cats, Oded, 2020. "Exact matching of attractive shared rides (ExMAS) for system-wide strategic evaluations," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 285-310.
    3. Ulak, Mehmet Baran & Yazici, Anil & Aljarrah, Mohammad, 2020. "Value of convenience for taxi trips in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 85-100.
    4. Jason Soria & Shelly Etzioni & Yoram Shiftan & Amanda Stathopoulos & Eran Ben-Elia, 2022. "Microtransit adoption in the wake of the COVID-19 pandemic: evidence from a choice experiment with transit and car commuters," Papers 2204.01974, arXiv.org.
    5. Georges Sfeir & Filipe Rodrigues & Maya Abou-Zeid, 2021. "Gaussian Process Latent Class Choice Models," Papers 2101.12252, arXiv.org.
    6. María J. Alonso-González & Oded Cats & Niels van Oort & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 0. "What are the determinants of the willingness to share rides in pooled on-demand services?," Transportation, Springer, vol. 0, pages 1-33.
    7. 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.
    8. Sanjay Gupta & Kushagra Sinha, 2022. "Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    9. Alonso-González, María J. & Hoogendoorn-Lanser, Sascha & van Oort, Niels & Cats, Oded & Hoogendoorn, Serge, 2020. "Drivers and barriers in adopting Mobility as a Service (MaaS) – A latent class cluster analysis of attitudes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 378-401.
    10. 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.
    11. Shafiq Alam & Muhammad Sohaib Ayub & Hao Cui & Muhammad Asad Khan, 2025. "A comparative study of machine learning models for taxi-demand prediction using a big data framework," Public Transport, Springer, vol. 17(3), pages 803-833, October.
    12. Nyga, Andreas & Minnich, Aljoscha & Schlüter, Jan, 2020. "The effects of susceptibility, eco-friendliness and dependence on the Consumers’ Willingness to Pay for a door-to-door DRT system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 540-558.
    13. Wang, Sicheng & Noland, Robert B., 2021. "What is the elasticity of sharing a ridesourcing trip?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 284-305.
    14. Sfeir, Georges & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Multivariate count data models for adoption of new transport modes in an organization-based context," Transport Policy, Elsevier, vol. 91(C), pages 59-75.
    15. María J. Alonso-González & Oded Cats & Niels van Oort & Sascha Hoogendoorn-Lanser & Serge Hoogendoorn, 2021. "What are the determinants of the willingness to share rides in pooled on-demand services?," Transportation, Springer, vol. 48(4), pages 1733-1765, August.

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