Prevalence and Mechanisms of Discrimination: Evidence from the Ride-Hail and Taxi Industries

Abstract

Ride-hail services, including Uber and Lyft, have upended the taxi industry, but it remains unclear whether ride-hailing, like taxis, discriminates against riders based on race. To understand whether and when discrimination manifests in for-hire vehicle services, I conducted an audit of Uber, Lyft, and taxis in Los Angeles. Discrimination against black taxi riders resulted in far higher rates of trip cancellation and longer wait times compared with white riders. By contrast, ride-hailing dramatically reduced differences between riders. Findings suggest that discrimination occurs when people learn of rider characteristics and yield implications for how planners can use technology to deter discrimination.

Differences in ride-hailing adoption by older Californians among types of locations

“…Hughes and MacKenzie (2016) suggest, however, that supply efficiency of ride-hailing is correlated with density of population and time of day rather than the socio-economic characteristics of an area. Brown (2019b) finds that ride-hailing is more reliable and less discriminatory than taxi service for minorities and in low-income locations in Los Angeles, California. Middleton and Zhao (2019) examine shared trip preferences with respect to ride-hailing services and find that males, women traveling with children, and those living in areas with high average income and conservative political leanings are likely to hold negative attitudes toward fellow riders of a different race.…”

Urban Analytics: History, Trajectory, and Critique

“…Young (2017) found that response times to service requests in low-income communities of color were faster under 311 app reporting and algorithmic assignment than those handled by public management staff. Brown (2019) found that app-based Uber and Lyft drivers racially discriminate against their passengers less than drivers for traditional taxi services do-though they do still discriminate. Sometimes more data and better algorithms can produce better outcomes for vulnerable communities.…”

Does Ridesourcing Respond to Unplanned Rail Disruptions? A Natural Experiment Analysis of Mobility Resilience and Disparity

“…In New York City, ridesourcing pickup rates were lower in lower income areas (Correa et al, 2017;Jin et al, 2019). By contrast, other recent research instead argues that ridesourcing is closer than traditional taxis to eradicating racial and ethnic inequities in service quality (Brown, 2019a). In Atlanta, estimated wait times of UberX and UberBLACK were not significantly correlated with race or income (Wang & Mu, 2018).…”