An Examination of the Relationships between AI-Generated Content (AIGC) Transparency, Perceived Trust, Content Authenticity, and Behavioral Intentions: A SEM Approach Toward Digital Tourism in China

HRMARS - This study examines the relationships between AI-generated content (AIGC) transparency, perceived trust, content authenticity, and behavioral intentions in China's digital tourism context. With the increasing integration of AIGC in tourism marketing, transparency, and authenticity have become crucial factors influencing consumer trust and decision-making. Data were collected through an online survey targeting users of AI-powered tourism platforms and an experimental study comparing disclosed and undisclosed AIGC. Structural Equation Modeling (SEM) was employed to analyze the proposed relationships. The key findings indicate that greater transparency in AIGC significantly enhances perceived trust, strengthening perceptions of content authenticity and positively influencing tourists' behavioral intentions. Furthermore, prior exposure to AIGC moderates the impact of transparency on trust, while perceived risk weakens this relationship. These results suggest that digital tourism platforms should prioritize transparent AI disclosure and enhance authenticity perceptions to foster consumer engagement. Therefore, improving transparency and managing perceived risk in AIGC can contribute to more positive consumer trust and behavioral responses in digital tourism experiences.