The Effect of Review Summary: Evidence from a Natural Experiment

Abstract

By leveraging a unique policy of an online review platform that introduces generative AI reviews summary (GAIRS), this study examines how GAIRS affect the characteristics of user-generated content in the online reviews context. Constructing a unique dataset of online reviews for a matched set of hotels across TripAdvisor and Expedia, we apply a cross-platform difference-in-differences approach to assess the impact of GAIRS. Our findings elucidate the adverse effects of GAIRS on users' subsequent contributions, manifested in diminished quantity and length of subsequent reviews. Nonetheless, GAIRS also correlates with an increase in the average ratings of reviews. We identify the substitution and learning effects as two plausible explanations for these effects. Further analyses reveal that the substitution effect mainly reduces strongly negative reviews, particularly in lower-status hotels, while the learning effect primarily causes inexperienced users to emulate GAIRS. This research contributes to the expanding discourse on how GAI impacts user-generated content.