Multimodal AIGC and Digital Exhibition Experience Intention in Museums: The Roles of Immersion, Content Creativity, and Interaction Quality

Multimodal artificial intelligence-generated content (AIGC) is reshaping museum digital exhibitions through dynamic content generation, contextual storytelling, and interactive feedback. Despite its growing adoption, the impact of AIGC’s experiential attributes on visitors’ digital exhibition experience intention remains underexplored. Drawing on the Technology Acceptance Model (TAM), this study develops an integrative framework incorporating AIGC technology acceptance, perceived immersion, content creativity, interaction quality, cognitive evaluations, and affective responses. Data were collected from 481 visitors with prior digital exhibition experience and analyzed using PLS-SEM. The results indicate that AIGC technology acceptance significantly influences perceived ease of use, perceived usefulness, and digital exhibition experience intention; interaction quality enhances usability and exerts a direct effect on intention; and immersion and content creativity primarily shape intention through perceived enjoyment while also exhibiting direct effects. These findings extend TAM to multimodal AIGC-enabled museum contexts and provide empirical evidence to guide the design of culturally meaningful, interactive, and engaging digital exhibition experiences.