No abstract

Transportation network companies (TNCs) offer two types of service: private-party ridehailing and shared ridehailing. Policymakers have an interest in encouraging shared over private ridehailing to promote more efficient use of the transportation network. While transportation researchers have analyzed ridehailing behavior before, there is limited literature describing the effect of price and time on a rider’s choice between private-party and shared ridehailing. This paper fills this gap by analyzing revealed preferences for private-party and shared ridehailing trips in 15 American cities coupled with a survey of 4,365 users of a large TNC that includes stated preference questions focused on various alternative options for their most recent trip choice. This study finds that an increase in the relative price difference of $1 per mile increases an individual’s probability of sharing by over 8%, while a decrease in the relative travel time difference of 1 min per mile increases the probability of sharing by over 33%. The survey results also show that that a sizable proportion of private-party TNC trips (approximately 35%) will be difficult or even impossible to convert to shared rides through a price-based incentive. Market segmentation analysis reveals user and trip types where price- and time-based incentives have a relatively greater effect on the choice between private and shared rides. Finally, heterogeneity in user time versus money trade-offs suggests new product possibilities that would increase TNC sharing.

Prior studies have provided evidence of discrimination between drivers and passengers in the context of ridehailing. This paper extends prior research by investigating passenger-topassenger discriminatory attitudes in the context of ridesharing. We conducted a survey of 1,110 Uber and Lyft users in the US using Mechanical Turk, 76.5% of whom have used uberPOOL or Lyft Shared rides, and estimated two structural equation models. The first model examines the influence of one's demographic, social and economic characteristics on discriminatory attitudes toward fellow passengers in ridesharing, and how such influence varies by the targets of discrimination (i.e., race and class). The second model examines the influence of one's generic social dominance orientation on discriminatory attitudes in the ridesharing context. We find that discriminatory attitudes toward fellow passengers of differing class and race in the shared ride are positively correlated with respondents that are male or are women with children. A respondent's race does not have a significant effect on discriminatory attitudes, but white respondents that live in majority white counties are more likely to hold discriminatory attitudes with regard to race (no effect is observed regarding class preferences). The same is true of respondents that live in counties in which a larger share of the electorate voted for the Republican candidate in the 2016 presidential election. Conversely, higher-income respondents appear more likely to hold discriminatory attitudes regarding class, but no effect is observed regarding racial preferences. We also find that one's generic social dominance orientation strongly influences his/her discriminatory attitudes in ridesharing, supporting the claim that behavior in shared mobility platforms reflects long-standing social dominance attitudes. Further research is required to identify policy interventions that mitigate such attitudes in the context of ridesharing.

Transportation investments determine the long-term success or failure of a transportation provider. It is therefore vital for decision makers to have an in-depth understanding of the alternatives available before they choose to invest. However, often, the process of evaluating alternatives is lengthy, costly, and contentious, particularly for transportation infrastructure investment decisions that are large, complex, and interconnected with other economic development and sustainability goals. Furthermore, transportation investments involve many decision makers, each with different priorities and expertise. Therefore, there is a need for transparent, accurate, flexible, and practicable decision-making aids that can handle the complex challenges facing the decision-making bodies of transportation providers and planning organizations. This paper introduces a new decision aid—the CLIOSjre Process—that combines insights from multicriteria decision analysis, multistakeholder negotiation theory, and uncertainty analysis. The CLIOSjre Process helps decision makers compare multiple alternatives across multiple objectives and seek an informed collective transportation investment decision. Unlike other multicriteria decision aids, the CLIOSjre Process accounts for differences of opinion among decision makers and is designed to facilitate constructive negotiation among them. Finally, the CLIOSjre Process formally accounts for sources of uncertainty inherent in these decisions. In this way, the CLIOSjre Process provides a unique and flexible framework for investment analysis that can adapt to changes in transportation alternatives, decision-maker priorities, and emerging real-world conditions. The usefulness of this new decision aid is illustrated for the East Japan Railway Company’s consideration of a transportation investment opportunity in high-speed rail development on the Northeast Corridor of the United States.