Trust is Extensible: A Field Experiment on Airbnb’s User Population

Bruno Abrahao
Paolo Parigi
Alok Gupta
Proceedings of the National Academy of Sciences (PNAS)
We investigate the extent to which artificial features engineered by sharing-economy platforms, such as reputation systems, can be used to override people’s tendency to base judgments of trustworthiness on social biases, such as to trust others who are similar (i.e., homophily). To this end, we engaged 8,906 users of Airbnb as volunteers in an online experiment. We demonstrate that homophily based on several demographic characteristics is a relatively weak driver of trust. In fact, having high reputation is enough to counteract homophily. Using Airbnb data, we present evidence that the effects we found experimentally are at work in the actual platform. Lastly, we found an inverse relationship between risk aversion and trust in those with positive reputations.