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Modeling demand for ridesourcing as feeder for high capacity mass transit systems with an application to the planned Beirut BRT

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  • Zgheib, Najib
  • Abou-Zeid, Maya
  • Kaysi, Isam

Abstract

Ridesourcing (Uber, Careem, Lyft, …) is emerging as a main player in the transportation industry. However, its relation to mass transit remains ambiguous, with divided opinions on its complementarity or substitutive effect towards high capacity public transportation systems. This study examines the integration of ridesourcing and transit, particularly focusing on modeling the demand for mass transit when ridesourcing is used as an access or egress mode to mass transit. It extends the existing literature on the integration of transit and new mobility concepts by providing a modeling framework that incorporates all stages of multi-modal trips such as those that involve using mass transit. A mixed logit with error component structure is presented to capture correlations in unobserved factors across multi-modal alternatives sharing similar modes at certain stages. The framework incorporates uni-modal and multi-modal travel alternatives and distinguishes between access, main mode, and egress stages without applying constraints on possible combinations. An application to Beirut’s planned Bus Rapid Transit (BRT) system, performed on a data set of 392 respondents, reveals that ridesourcing as a feeder mode is mostly popular with young commuters while also being perceived as more reliable than feeder buses and jitneys. Awareness and familiarity are major drivers for the service implying higher potential in the future. A complementarity effect with transit is found as the introduction of ridesourcing at the feeders’ level is expected to drive an additional 2% of commuters to use the BRT. Decreasing ridesourcing fare is effective for its integration with transit, as a fare decrease of 50% increases BRT market share from 33.53% to 36.89% of all motorized trips, implying possible synergies between the two modes. Forecasting results further reveal that additional taxes on parking used by car commuters and increasing park and ride capacity at BRT stations are effective policies to augment BRT ridership.

Suggested Citation

  • Zgheib, Najib & Abou-Zeid, Maya & Kaysi, Isam, 2020. "Modeling demand for ridesourcing as feeder for high capacity mass transit systems with an application to the planned Beirut BRT," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 70-91.
    • Handle: RePEc:eee:transa:v:138:y:2020:i:c:p:70-91
    DOI: 10.1016/j.tra.2020.05.019
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    2. Rick Grahn & Sean Qian & Chris Hendrickson, 2023. "Optimizing first- and last-mile public transit services leveraging transportation network companies (TNC)," Transportation, Springer, vol. 50(5), pages 2049-2076, October.
    3. Bi, Hui & Ye, Zhirui & Hu, Liyang & Zhu, He, 2021. "Why they don't choose bus service? Understanding special online car-hailing behavior near bus stops," Transport Policy, Elsevier, vol. 114(C), pages 280-297.
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