How Unbecoming of You: Gender Biases in Perceptions of Ridesharing Performance

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dc.contributor.authorGreenwood, Brad
dc.contributor.authorAdjerid, Idris
dc.contributor.authorAngst, Corey
dc.date.accessioned2019-01-03T00:50:51Z
dc.date.available2019-01-03T00:50:51Z
dc.date.issued2019-01-08
dc.description.abstractIt 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.
dc.format.extent11 pages
dc.identifier.doi10.24251/HICSS.2019.789
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/60092
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectStrategy, Information, Technology, Economics, and Strategy (SITES)
dc.subjectOrganizational Systems and Technology
dc.subjectGender Bias, Sharing Economy, Ride Sharing
dc.titleHow Unbecoming of You: Gender Biases in Perceptions of Ridesharing Performance
dc.typeConference Paper
dc.type.dcmiText

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