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Airbnb’s Reputation System and Gender Differences Among Guests: Evidence from Large-Scale Data Analysis and a Controlled Experiment

  • Eunseo Choi
  • Emőke-Ágnes HorvátEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11864)

Abstract

Sharing economy platforms are rapidly scaling up by reaching increasingly diverse demographics. However, this expansion comes with great difficulties in adequately identifying and responding to everyone’s needs. In this paper, we study gender-related behaviors of guests on the currently most prominent home-sharing platform, Airbnb. While our results confirm the efficacy of Airbnb’s reputation system, we also find that the level of trust and participation on the platform varies by gender. In particular, female solo travelers are more likely to be conscious of review sentiment and choose more often female hosts than male solo travelers. Our findings are obtained by combining exploratory data analysis with large-scale experiments and call for further studies on the usage of sharing economy platforms among subpopulations, informing and improving both policy and practice in these growing online environments.

Keywords

Sharing economy Reputation systems Trust Gender bias 

Notes

Acknowledgements

The authors would like to thank Joshua Becker and Johannes Wachs for their feedback. We are also grateful to all the anonymous Mechanical Turk participants for their input to the presented experimental studies (IRB: STU00207726). This work was supported in part by a Northwestern Undergraduate Summer Research grant and the U.S. National Science Foundation (IIS-1755873).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Northwestern UniversityEvanstonUSA

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