Cool or poor: Assessing the effectiveness of GenAI-powered review summary feature on the OTA platform
研究了在线旅游平台（OTA）上生成式AI（GenAI）评论摘要如何通过缓解信息过载和减少感知处理努力，增强游客的互惠动机，从而提升其撰写评论的意愿。
Despite the growing adoption of generative artificial intelligence (GenAI) in online travel agencies (OTAs), its impact on tourists' review behavior remains poorly understood. Within the information overload framework, this study offers a novel dual-path theoretical framework that integrates both generalized reciprocity and suppressed social loafing mechanisms. Using a multi-method design comprising a natural experiment with regression discontinuity design and controlled online experiments across three studies, we investigated how GenAI-powered review summaries shape tourists' review intention. Our findings reveal that exposure to GenAI summaries enhances review intention through generalized reciprocity. By alleviating information overload and reducing perceived processing effort, these summaries motivate tourists to reciprocate by composing their own reviews, thereby ''paying forward'' the benefits received, rather than triggering free-riding that would diminish review intention. These findings advance theoretical knowledge of information processing, GenAI's influence on tourists' decision-making, and tourists' review behavior, while providing actionable insights for OTAs and hospitality management.