Spatial Welfare Effects of Shared Taxi Operating Policies for First Mile Airport Access

With increasing availability of alternative mobility options for first/last mile, it is necessary to better understand how shared taxis are impacting airport access demand and consumer surplus. However, no study has been conducted to evaluate the welfare effects of the range of shared taxi matching and fare allocation policies for airport access. Using several data sources primarily from Port Authority of NY and NJ and The Taxi and Limousine Commission, a mode choice model is estimated for access to John F. Kennedy International Airport in New York City. The baseline model and data show that passengers have a value of time of $101 per hour, consistent with Harvey’s study from 1986. Airport taxi travelers are also elastic to cost in a similar manner to public transit. The model is used to evaluate two policies: a first (we call this wait-share policy) where taxis can offer shared rides for two passengers from the same zip code, incorporating an endogenous expected wait time variable; and a second (we call this space-share policy) where taxis match randomly arriving passengers from any zip codes in the city. These two policies reflect extreme ends of a spectrum of policies between waiting and detouring. Findings suggest that having a shared taxi option benefit passengers in NYC going to JFK airport by at least 10% increase in consumer surplus. However, the increase in taxi ridership comes at a cost to transit ridership. Furthermore, the population in NYC that benefits most is highly dependent on the type of shared taxi policy. A wait-share policy benefits passengers from the dense parts of Manhattan most, while a space-share policy distributes the benefits more to other boroughs. These insights can help policymakers set regulations in providing first/last mile ride-sharing taxi options in different cities around the world.

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  • English

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  • Accession Number: 01652534
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Nov 30 2017 9:53AM