Race and Rating on Sharing Economy Platforms: The Effect of Race Similarity and Reputation on Trust and Booking Intention in Airbnb

Teng Ye, Rasha Alahmad, Casey Pierce, Lionel P. Robert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Stories about the “sharing economy” are increasingly making the headlines in the media and research. While the sharing economy is booming and attractive, research has found evidence of racial discrimination on these sharing economy platforms. To begin to address this issue, this research in-progress paper proposes a theoretical model to examine the effects of racial similarity and ratings on an accommodation-sharing platform, Airbnb. We also propose a 2 (the racial origins of the guest and host are the same vs. different) × 2 (high vs. low reputation) between-subjects experiment to test the model. Then, we discuss the implementation of the experiment followed by a brief discussion of the study’s potential theoretical contributions.

Original languageEnglish (US)
Title of host publicationICIS 2017
Subtitle of host publicationTransforming Society with Digital Innovation
PublisherAssociation for Information Systems
ISBN (Print)9780996683159
StatePublished - 2018
Externally publishedYes
Event38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017 - Seoul, Korea, Republic of
Duration: Dec 10 2017Dec 13 2017

Publication series

NameICIS 2017: Transforming Society with Digital Innovation

Other

Other38th International Conference on Information Systems: Transforming Society with Digital Innovation, ICIS 2017
Country/TerritoryKorea, Republic of
CitySeoul
Period12/10/1712/13/17

Keywords

  • Airbnb
  • Racial bias
  • Racial Discrimination
  • Reputation systems
  • Sharing economy

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