Discriminatory attitudes between ridesharing passengers

Abstract

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.

Effect of Price and Time on Private and Shared Transportation Network Company Trips

“…Despite the strength of the stated preference methodology, we note several limitations to this work and suggest possible avenues for future research. First, our data is only a snapshot in time of a TNC user base that was growing rapidly before the COVID-19 pandemic, with a 37% increase in passengers transported from 2016 to 2017 (19). As the national economy undergoes a major transition, TNCs' user base changes, and TNCs alter their services, our descriptive analysis will need to be updated to reflect the point-in-time reality of travel behavior.…”

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

“…Most research on ride-hailing has focused on millennials, generation Xers, and regular travelers. Methodologically, online surveys (Alemi, Circella, Mokhtarian, & Handy, 2019;Middleton & Zhao, 2019), spatio-temporal data on use of ride-hailing (Brown, 2019a;Erhardt et al, 2019), and intercept surveys (Gehrke, Felix, & Reardon, 2019;Henao & Marshall, 2018) have been utilized to unearth dimensions of ride-hailing usage in cities. Tirachini (2019) provides an in-depth literature review of ride-hailing scholarship from developed and developing countries.…”

“…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. Conway et al (2018), using the National Household Travel Survey, find that there are differences across users and by location.…”

“…We collected data from the respondents through an online survey (for complete methodological details, see Agrawal, Shirgaokar, Misra, Wachs, & Dobbs, 2020). Online surveys are a method increasingly used by researchers (Alemi et al, 2019;Middleton & Zhao, 2019). Our calculations based on American Community Survey (ACS) 5-year housing and person Public Use Microdata Sample (PUMS) data show that 86% percent of California's population over the age of 55 has access to the internet and 73% has access to a smartphone.…”

“I trust Norway” – investigating acceptance of shared autonomous shuttles using open and closed questions in short-form street interviews

“…The social situation within such small shared vehicles is not well understood nor integrated into the MAVA (Nordhoff et al, 2019;Sanguinetti et al, 2019). However, rider-to-rider discrimination could be a crucial issue for the implementation and acceptance of SASs, particularly because of their intimacy and planned stewardless operation (Middleton & Zhao, 2019). Research remains to be conducted that gives insight into the distinction between AVs in general and SASs in public transport.…”