When Transparency Fails: Bias and Financial Incentives in Ridesharing Platforms

31 Pages Posted: 27 Jul 2018 Last revised: 23 Sep 2019

See all articles by Jorge Mejia

Jorge Mejia

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies

Chris Parker

American University - Kogod School of Business

Date Written: September 20, 2019

Abstract

Providing transparency into operational processes can change consumer and worker behavior. However, it is unclear whether operational transparency is beneficial with potentially biased service providers. We explore this in the context of ridesharing platforms where early evidence documents bias similar to what has been observed in traditional transportation systems. Platforms responded by reducing operational transparency through removing information about riders' gender and race from the ride request presented to drivers. However, following this change, bias may still manifest through driver cancelation after a request is accepted, at which point the rider's picture is displayed. Our primary research question is to what extent a rider's gender, race, and perception of support for lesbian, gay, bisexual, and transgender (LGBT) rights impact cancelation rates. We investigate this through a large field experiment on a major ridesharing platform in Washington, DC. By manipulating rider names and profile pictures, we observe drivers' behavior patterns in accepting and canceling rides. Our results confirm that bias at the ride request stage has been eliminated. However, after acceptance, racial and LGBT biases are persistent, while we find no evidence of gender biases. We also explore whether peak times moderate (through increased pay to drivers) or exacerbate (by signaling that there are many riders, allowing drivers to be more selective) these biases. We find a moderating effect of peak timing, with lower cancelation rates for non-caucasian riders. We do not find a similar moderating effect for riders that signal support for the LGBT community.

Keywords: Economics Behavior and Behavioral Decision Making, Sharing Economy, Field Experiment, Operational Transparency, Gender and Racial Biases

Suggested Citation

Mejia, Jorge and Parker, Chris, When Transparency Fails: Bias and Financial Incentives in Ridesharing Platforms (September 20, 2019). Kelley School of Business Research Paper No. 18-59. Available at SSRN: https://ssrn.com/abstract=3209274 or http://dx.doi.org/10.2139/ssrn.3209274

Jorge Mejia

Indiana University - Kelley School of Business - Department of Operation & Decision Technologies ( email )

Business 670
1309 E. Tenth Street
Bloomington, IN 47401
United States

Chris Parker (Contact Author)

American University - Kogod School of Business ( email )

4400 Massachusetts Avenue NW
Washington, DC 20816-8044
United States

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