How Unbecoming of You: Gender Biases in Perceptions of Ridesharing Performance
Files
Date
2019-01-08
Contributor
Advisor
Department
Instructor
Depositor
Speaker
Researcher
Consultant
Interviewer
Narrator
Transcriber
Annotator
Journal Title
Journal ISSN
Volume Title
Publisher
Volume
Number/Issue
Starting Page
Ending Page
Alternative Title
Abstract
It has been suggested that the gig-economy’s elimination of traditional arm’s-length transactions may introduce bias into perceptions of quality. In this work, we build upon research that has identified biases based on ascriptive characteristics in rating systems, and examine gender biases in ridesharing platforms. In doing so, we extend research to consider not simply willingness to transact, but post transaction perceptions of quality. We also examine which types of tasks may yield more biased ratings for female drivers. We find no differences in ratings across gender in the presence of a high quality experience. However, when there is a lower quality experience, penalties for women accrue faster, notably when poorly performed tasks are perceived to be highly gendered.
Description
Keywords
Strategy, Information, Technology, Economics, and Strategy (SITES), Organizational Systems and Technology, Gender Bias, Sharing Economy, Ride Sharing
Citation
Extent
11 pages
Format
Geographic Location
Time Period
Related To
Proceedings of the 52nd Hawaii International Conference on System Sciences
Related To (URI)
Table of Contents
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International
Rights Holder
Local Contexts
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.