This study explores how scene themes and interaction mechanisms influence tourist satisfaction through immersion and positive emotion in intelligent tourism. Grounded in the ABC model and BERTopic analysis of online reviews, it identifies key experiential drivers and their psychological pathways.
This study analyzes 33,297 Dianping online reviews using BERTopic and sentiment analysis to identify main themes and tourist sentiments. Based on the ABC model, combined with theme and sentiment analysis results, it proposes factors influencing intelligent tourism immersive experience satisfaction and constructs a model. Finally, questionnaire data is collected to test relationships between scene theme, interaction mechanism, immersion, positive emotion and tourist satisfaction.
Findings show tourists generally positively evaluate AI-driven immersive services in intelligent tourism, with particular interest in cultural, historical, tech-themed immersive spaces and traditional-style environments, though queue management issues were noted. The research identifies scene themes, interaction mechanisms, immersion and positive emotion as key factors influencing satisfaction in intelligent tourism scenes. These factors are interrelated: scene themes and interaction mechanisms indirectly boost satisfaction by deepening immersion and fostering positive emotion, while immersion itself promotes positive emotion.
This study contributes significantly to intelligent tourism immersive services literature by comprehensively understanding tourists’ feedback and perceptions. Integrating BERTopic, sentiment analysis and the ABC model, it highlights scene themes, interaction mechanisms, immersion and positive emotion as key to shaping satisfaction. These findings offer valuable theoretical and practical insights for optimizing such services and enhancing visitor experiences.
