Rethinking information disclosure to GenAI in hotels: An extended parallel process model

Abstract

A critical, yet understudied aspect of generative AI functionality in hotels is consumers’ disclosure of personal information, which carries significant risks. By expanding the Extended Parallel Process Model, this research investigates the role of trust in hotels in impacting consumers’ perceptions of threat and coping efficacy. These perceptions, in turn, influence consumers’ fear perceptions and drive both adaptive behaviors (e.g., protective action and seeking help) and maladaptive behaviors (e.g., avoidance). Ultimately, the disclosure of personal information is strongly influenced by avoidance and, to some extent, by seeking help behaviors, but not by protective action behaviors. As the first study to examine consumers’ disclosure of personal information to generative AI, it extends the literature on processing arguments related to opaque systems like generative AI. Additionally, it provides insightful managerial implications, especially at a time when the hotel industry lacks clear guidance regarding the use of consumers’ personal information within generative AI.