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Omran, W., Casais, B. & Ramos, R. F. (2025). Attributes of virtual and augmented reality tourism mobile applications predicting tourist behavioral engagement. International Journal of Human–Computer Interaction. 41 (21), 13335-13348
W. Omran et al., "Attributes of virtual and augmented reality tourism mobile applications predicting tourist behavioral engagement", in Int. Journal of Human–Computer Interaction, vol. 41, no. 21, pp. 13335-13348, 2025
@article{omran2025_1765462021491,
author = "Omran, W. and Casais, B. and Ramos, R. F.",
title = "Attributes of virtual and augmented reality tourism mobile applications predicting tourist behavioral engagement",
journal = "International Journal of Human–Computer Interaction",
year = "2025",
volume = "41",
number = "21",
doi = "10.1080/10447318.2025.2470293",
pages = "13335-13348",
url = "https://www.tandfonline.com/journals/hihc20"
}
TY - JOUR TI - Attributes of virtual and augmented reality tourism mobile applications predicting tourist behavioral engagement T2 - International Journal of Human–Computer Interaction VL - 41 IS - 21 AU - Omran, W. AU - Casais, B. AU - Ramos, R. F. PY - 2025 SP - 13335-13348 SN - 1044-7318 DO - 10.1080/10447318.2025.2470293 UR - https://www.tandfonline.com/journals/hihc20 AB - 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. ER -
English