Reputation offsets trust judgments based on social biases among Airbnb users

Bruno Abrahao, Paolo Parigi, Alok Gupta, Karen S. Cook

    Research output: Contribution to journalArticlepeer-review


    To provide social exchange on a global level, sharing-economy companies leverage interpersonal trust between their members on a scale unimaginable even a few years ago. A challenge to this mission is the presence of social biases among a large heterogeneous and independent population of users, a factor that hinders the growth of these services. We investigate whether and to what extent a sharing-economy platform can design artificially engineered features, such as reputation systems, to override people’s natural tendency to base judgments of trustworthiness on social biases. We focus on the common tendency to trust others who are similar (i.e., homophily) as a source of bias. We test this argument through an online experiment with 8,906 users of Airbnb, a leading hospitality company in the sharing economy. The experiment is based on an interpersonal investment game, in which we vary the characteristics of recipients to study trust through the interplay between homophily and reputation. Our findings show that reputation systems can significantly increase the trust between dissimilar users and that risk aversion has an inverse relationship with trust given high reputation. We also present evidence that our experimental findings are confirmed by analyses of 1 million actual hospitality interactions among users of Airbnb.

    Original languageEnglish (US)
    Pages (from-to)9848-9853
    Number of pages6
    JournalProceedings of the National Academy of Sciences of the United States of America
    Issue number37
    StatePublished - Sep 12 2017


    • Online trust
    • Reputation systems
    • Risk
    • Sharing economy
    • Social biases

    ASJC Scopus subject areas

    • General


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