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Uncovering Disparities in Rideshare Drivers Earning and Work Patterns: A Case Study of Chicago

Hy Dang, Yuwen Lu, Jason Spicer, Tamara Kay, Di Yang, Yang Yang, Jay Brockman, Meng Jiang, Toby Jia-Jun Li

TL;DR

Uncovering Disparities in Rideshare Drivers Earning and Work Patterns uses Chicago's public Trip Network Provider data (2018–2023) to analyze temporal and spatial inequities in earnings. It introduces a trip-based driver assignment algorithm to infer plausible driver work patterns from anonymized trips and applies clustering to reveal distinct driver groups. The study finds a nominal earnings surge in early 2021 followed by fluctuations and a decline in real earnings, with Central and Airport regions commanding higher trip costs than peripheral areas and new low-income groups emerging in 2023. These results highlight the need for transparent pricing and algorithmic accountability to promote equitable outcomes in urban ridesourcing.

Abstract

Ride-sharing services are revolutionizing urban mobility while simultaneously raising significant concerns regarding fairness and driver equity. This study employs Chicago Trip Network Provider dataset to investigate disparities in ride-sharing earnings between 2018 and 2023. Our analysis reveals marked temporal shifts, including an earnings surge in early 2021 followed by fluctuations and a decline in inflation-adjusted income, as well as pronounced spatial disparities, with drivers in Central and airport regions earning substantially more than those in peripheral areas. Recognizing the limitations of trip-level data, we introduce a novel trip-driver assignment algorithm to reconstruct plausible daily work patterns, uncovering distinct driver clusters with varied earning profiles. Notably, drivers operating during late-evening and overnight hours secure higher per-trip and hourly rates, while emerging groups in low-demand regions face significant earnings deficits. Our findings call for more transparent pricing models and a re-examination of platform design to promote equitable driver outcomes.

Uncovering Disparities in Rideshare Drivers Earning and Work Patterns: A Case Study of Chicago

TL;DR

Uncovering Disparities in Rideshare Drivers Earning and Work Patterns uses Chicago's public Trip Network Provider data (2018–2023) to analyze temporal and spatial inequities in earnings. It introduces a trip-based driver assignment algorithm to infer plausible driver work patterns from anonymized trips and applies clustering to reveal distinct driver groups. The study finds a nominal earnings surge in early 2021 followed by fluctuations and a decline in real earnings, with Central and Airport regions commanding higher trip costs than peripheral areas and new low-income groups emerging in 2023. These results highlight the need for transparent pricing and algorithmic accountability to promote equitable outcomes in urban ridesourcing.

Abstract

Ride-sharing services are revolutionizing urban mobility while simultaneously raising significant concerns regarding fairness and driver equity. This study employs Chicago Trip Network Provider dataset to investigate disparities in ride-sharing earnings between 2018 and 2023. Our analysis reveals marked temporal shifts, including an earnings surge in early 2021 followed by fluctuations and a decline in inflation-adjusted income, as well as pronounced spatial disparities, with drivers in Central and airport regions earning substantially more than those in peripheral areas. Recognizing the limitations of trip-level data, we introduce a novel trip-driver assignment algorithm to reconstruct plausible daily work patterns, uncovering distinct driver clusters with varied earning profiles. Notably, drivers operating during late-evening and overnight hours secure higher per-trip and hourly rates, while emerging groups in low-demand regions face significant earnings deficits. Our findings call for more transparent pricing models and a re-examination of platform design to promote equitable driver outcomes.

Paper Structure

This paper contains 36 sections, 21 figures, 1 table, 1 algorithm.

Figures (21)

  • Figure 1: Cost per driving hour trends from November 2018 to November 2023. A significant increase in earnings per trip and projected total earnings per driving hour begins in January 2021, peaking in August 2021. After this peak, all metrics fluctuate and gradually decline throughout 2023, with no major increases observed since late 2021.
  • Figure 2: Heat maps of pickup and dropoff trip distributions across Chicago in 2019. The highest concentration of activity was in the Central region, accounting for 30.50% of pickups and 30.88% of dropoffs, followed by the West Side. Other regions, such as the South Side and Far Southeast Side, shows lower levels of ride-hailing activity, with the Far Southwest Side being the least active area, contributing only 1.31% of pickups and 1.29% of dropoffs.
  • Figure 3: Heat maps of pickup and dropoff trip distributions across Chicago in 2023. The Central region remains the most active, with 27.42% of pickups and 27.75% of dropoffs, followed by the West Side. The South Side and Far Southeast Side show increased activity compared to 2019, the Far Southwest Side continues to account for the lowest share, with 1.98% of pickups and 1.91% of dropoffs.
  • Figure 4: Projected hourly driving costs in 2019. The highest cost area is in the Airport region, with $66.21/hour for pickups and $65.97/hour for dropoffs. The Central and Southwest Side regions with the top earnings regions. In contrast, the Northwest Side recorded the lowest earnings, with $56/hour and $54.13/hour for pickup and dropoff, respectively.
  • Figure 5: Average hourly trip costs in 2023. The highest cost remains in the Airport region, with $97.17/hour for pickups and $87.52/hour for dropoffs. The Central and Southwest Side regions are among the top earning areas. In contrast, the Far Southeast Side and Far Southwest Side recorded the lowest earnings, with $30.06/hour and $31.14/hour for pickup and dropoff, respectively.
  • ...and 16 more figures