Travel Choices and Perceived Images Influenced by AI Interactive Approaches of Travel Apps: An Evidence From Chinese Mobile Travel Users

The main objective of this article is to investigate how the AI interactive approaches of travel apps affect tourists’ travel choices directly or indirectly through perceived images, in order to further understand whether tourists can have a favorable user experience in the face of this non-human service, and whether the interactive approaches should be adapted to satisfy the marketing intentions set by the travel app in response to the competitive strength in the marketplace. The research methodology uses quantitative analysis, hypotheses supported by a theoretical background and the formation of a research model, the collection of basic data through questionnaires, and data analysis using structural equation modeling with Amos 22.0. The major findings are associated with the essential role of the interactive approaches (including informativeness, playfulness, and personalization approaches) offered by the travel apps on both the users’ perceived images and travel choices. This not only emphasizes the role of AI interactive approaches in the experiential travel assistance provided to users, but also represents a stronger marketing element to the destination perceived image composition and travel decisions of tourists. The findings also support the development of approaches for human-android interaction and tourism marketing with AI as the main service. This research has the scientific value of an integrated disciplinary analysis that combines theories from computer technology, tourism management, and psychology.