Attributes of Virtual and Augmented Reality Tourism Mobile Applications Predicting Tourist Behavioral Engagement

This is the authors' abstract. We don't add key points for this paper.

The study aims to explore the attributes of VR/AR tourism mobile applications (apps) and their impact on Tourist Behavioral Engagement (TBE), mediated by app satisfaction. The authors employed a text mining and Partial Least Squares-Structural Equation Modelling (PLS-SEM) approach to analyze 6,998 Google Play VR/AR tourism mobile apps online reviews. A word frequency matrix (WFM) was generated and used as an input for PLS-SEM to test the raised hypotheses. The findings revealed that utilitarian gratification, perceived usefulness, ease-of-use, and VR/AR immersion features (context awareness, presence, and telepresence) are key predictors of TBE, with app satisfaction playing a critical mediating role between these VR/AR attributions and TBE, emphasizing the vital role of Technology Acceptance Model (TAM) in driving sustained app engagement. The proposed framework advances theoretical literature on the TBE predictors and provides a guide for VR/AR tourism apps developers/designers to enable adoption, engagement, and proliferation among tourists.