The growing ecosystem of peer-to-peer enterprise – the Sharing Economy (SE) – has
brought with it a substantial change in how we access and provide goods and services.
Within the SE, individuals make decisions based mainly on user-generated trust and
reputation information (TRI). Recent research indicates that the use of such information
tends to produce a positivity bias in the perceived trustworthiness of fellow users.
Across two experimental studies performed on an artificial SE accommodation platform,
we test whether users’ judgments can be accurate when presented with diagnostic
information relating to the quality of the profiles they see or if these overly positive
perceptions persist. In study 1, we find that users are quite accurate overall (70%)
at determining the quality of a profile, both when presented with full profiles or with
profiles where they selected three TRI elements they considered useful for their decisionmaking. However, users tended to exhibit an “upward quality bias” when making errors.
In study 2, we leveraged patterns of frequently vs. infrequently selected TRI elements
to understand whether users have insights into which are more diagnostic and find
that presenting frequently selected TRI elements improved users’ accuracy. Overall, our
studies demonstrate that – positivity bias notwithstanding – users can be remarkably
accurate in their online SE judgments