This research investigates how value transparency and profile image realism jointly shape consumers' perceptions and trade behavior in Consumer-to-Consumer (C2C) swapping platforms. Across three studies, we examine whether realistic profile images enhance perceived warmth and competence, thereby fostering trade intentions under different levels of transparency. Study 1 analyzes behavioral data from an active swapping platform and finds that image realism positively predicts trade activity, particularly when value transparency is low. Study 2 uses an experiment to uncover underlying mechanisms; the results show that the effect of value transparency on perceived warmth and competence depends on image realism, which in turn influences trade intent. Study 3 contrasts realistic and AI-generated images to test the boundaries of artificial realism and reveals that AI imagery evokes weaker persuasion in high-transparency conditions. Together, these findings demonstrate that consumers rely on social cues from visual realism when informational cues are limited. This research extends models of authenticity signaling and the stereotype content framework to the context of C2C exchange, highlighting how visual and informational cues interact to influence fairness, trust, and persuasion in digital marketplaces that are increasingly shaped by AI-generated content.
This is the default collection for all research and scholarship developed by faculty, staff, or students at the University of Illinois at Urbana-Champaign
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
