4.7 Article

Optimal prices for ridesourcing in the presence of taxi, public transport and car competition

Journal

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.trc.2022.103591

Keywords

Multimodal pricing; Optimal fares; Ridesourcing; Congestion; Uber

Funding

  1. ANID Chile (Grant PIA/BASAL) [AFB180003]

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Ridesourcing platforms have become an important alternative travel mode in major cities worldwide. While these platforms offer benefits over traditional taxi and public transport options, there is increasing evidence that they contribute to traffic congestion. This paper presents a social welfare maximization model to derive optimal fares considering the congestion externality generated by each travel mode. The results suggest that ridesourcing fares should be higher to account for the congestion they contribute to, compared to current levels.
Ridesourcing platforms have acquired an important role as an alternative travel mode in almost all major cities in the world. These new mobility applications offer benefits for users over traditional taxi and public transport alternatives. However, there is mounting evidence that ridesourcing worsens traffic congestion. Given this potential negative impact and the complicated relationship between travel modes, it is unclear how policymakers should respond to the appearance of this new transport option. In this paper, we present a social welfare maximization model with four modes (automobile, taxi, buses and ridesourcing services) to derive the optimal first-best and second-best fares, considering the congestion externality generated by each mode. We apply this model to Santiago, Chile, using available parameter estimates to derive optimal fares with a novel inverse demand system (Inverse Product Differentiation Logit model). The results indicate that ridesourcing fares should be 29% higher per ride in the first-best scenario and 59% higher in the second-best scenario compared to current levels. However, our second-best scenario (in which buses and taxis have fares given by current levels and there is no conges-tion pricing for cars) reaches only 18% of the welfare gains from a first-best scenario. Sensitivity analysis shows that these results are not sensitive to several key assumptions, however they are sensitive to the parametrization of the flow-delay function in the second-best scenario. Our simulations also show that the optimal surcharge should be slightly higher if the average occu-pancy rate for ridesourcing services increases. This result is due to the higher overall use of this service, as the average fare per passenger decreases when more passengers ride together.

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