Exploring the intention–behavior gap in food delivery applications: a digital transformation perspective in smart tourism

PurposeIntegrating modern food technologies within the tourism sector improves the pleasures, convenience and involvement of travelers. Central to this advancement is AI-powered food applications (AI-PFDA), which are vital in driving this shift. However, the adoption of AI-PFDA is impeded by the gap between travelers’ usage intention (UI) and their actual usage behavior (UB), a phenomenon that has received limited scholarly attention in recent years.Design/methodology/approachTo address the identified disparity, this study introduces a theoretical model based on self-determination theory, cognitive dissonance theory and mere exposure theory. The proposed model was tested using data collected from a questionnaire administered to 305 tourists in China, employing partial least squares structural equation modeling and necessary conditions analysis techniques.FindingsOur findings demonstrate a significant partial mediating effect of perceived autonomy, competence and relatedness, a positive moderating effect of mere exposure and a negative moderating effect of reference price on the relationship between UI and UB.Originality/valueThis research enriches the current literature and assists policymakers in developing measures to mitigate the intention–behavior gap in adopting AI-PFDA within the framework of smart tourism.