Uber Economics: Evaluating the Monetary and Travel Time Trade-Offs of Transportation Network Companies and Transit Service in Chicago, Illinois

Abstract

The potential diversion of passengers from public transit to transportation network companies (TNCs) is attracting considerable attention in metropolitan regions. Despite this, relatively little microeconomic analysis has been made available to explore how service attributes affect choices between the services offered by TNCs and public transit. To fill this shortfall, this study evaluates prices and service levels for Lyft, Lyft Line, UberX, UberPool, and Chicago Transit Authority (CTA) services in Chicago. Analysis of 3,075 fares and estimated travel times for 620 trips in the 4- to 11-mile range shows TNCs tend to be relatively costly when expressed in relation to the additional amount spent per unit of time saved. The average traveler using these four TNC services, across the entire sample, spends the equivalent of $42–$108 per hour saved—well above the $14.95/hr. the U.S. Department of Transportation (U.S. DOT) recommends assigning to the average transit passenger when conducting analyses about the value of time. However, for travelers on business and those between locations poorly served by transit, including trips between neighborhoods with less transit service than the downtown district, the analysis shows a significant share of passengers will likely find TNCs cost-effective options based on the U.S. DOT standard. The approach taken illustrates how the mobility benefits and competitive issues associated with TNCs can be systematically evaluated by reviewing the price and travel time characteristics of each trip.

Incentive-driven transition to high ride-sharing adoption

“…Strong correlations between the adoption of ride-sharing and (in)direct measures of the three incentives (see Supplementary Notes 1 and 2 , including Supplementary Figs. 5 and 7 ) confirm the importance of these incentives found in detailed empirical studies of ride-sharing user experiences as well as focus group interviews 21 , 23 – 25 , 27 , 28 , 34 – 38 . Together, discounts, detours and inconvenience affect the ride-sharing adoption as follows (Fig.…”

Regulating TNCs: Should Uber and Lyft set their own rules?

“…Empirical study suggests that value of travel time (VOT) in the range $20 to $100 per hour [32] and value of waiting time at 2 to 3 times that of in-vehicle travel time [33]. Our estimate of α = $3.2 per min corresponds to a VOT between $64 and $96 per hour.…”

Spontaneous symmetry breaking in ride-sharing adoption dynamics

“…We have studied the dynamics of ride-sharing adoption in a highly simplified setting. While the qualitative, fundamental interactions are likely persistent also in real-world ride-sharing applications, additional influences from alternative mode choice options, matching strategies, or quickly evolving regulatory boundary conditions add to the dynamics [31,[33][34][35][36]. In particular, adoption patterns in real ride-sharing applications seem to be dominated by socio-economic heterogeneities and the interaction with other (public) transport modes [30,36].…”

“…The decision of a ride-hailing user to request a single or a shared ride depends on the possible benefits of the two options [30,31,[33][34][35][36] (see Fig. 1).…”