Adoption of voice assistants for airport procedures and services: an empirical study using the UTAUT2 model and SEM analysis

Purpose The study aims to examine the adoption of voice assistants (VAts) in developing countries for airport procedures and services, focusing on user behavior and technology readiness, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework to identify key predictors of intention and actual use. Design/methodology/approach A mixed-methods study was conducted in Vietnam, with a total of 330 responses collected. After screening for validity, 314 responses were retained for the quantitative survey and the remaining 14 participants were engaged in qualitative interviews. Quantitative data were analyzed using structural equation modeling to validate the conceptual framework, and qualitative insights were used to complement and contextualize the statistical findings. Findings The findings indicate that seven UTAUT2 factors significantly shaped users’ intention to use voice assistants, which in turn strongly predicted actual usage, highlighting the key mediating role of behavioral intention. Research limitations/implications The study explores the adoption of VAts in airport services in developing countries, extending the UTAUT2 framework. It provides insights for airport managers and developers to design and implement VAts that meet user expectations, improve service efficiency and enhance customer experience, ultimately promoting sustained adoption of technology in public service settings. Originality/value This is among the first studies applying UTAUT2 to VAts adoption in airports within a developing country. It contributes to theoretical expansion and offers practical insights for airport managers and developers to tailor VAts to enhance user experience and encourage sustained usage.

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Publication Details

Journal
Journal of Hospitality and Tourism Insights
Published
2025-10-31
DOI
https://doi.org/10.1108/jhti-06-2025-0682
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Adoption of voice assistants for airport procedures and services: an empirical study using the UTAUT2 model and SEM analysis

Thien Nhan Chau, Vi Loi Truong, Thuong Thi Nguyen
Journal of Hospitality and Tourism Insights
AI in Service Interactions
article

Adoption of voice assistants for airport procedures and services: an empirical study using the UTAUT2 model and SEM analysis

Thien Nhan Chau, Vi Loi Truong, Thuong Thi Nguyen
article en

Abstract

Purpose The study aims to examine the adoption of voice assistants (VAts) in developing countries for airport procedures and services, focusing on user behavior and technology readiness, using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework to identify key predictors of intention and actual use. Design/methodology/approach A mixed-methods study was conducted in Vietnam, with a total of 330 responses collected. After screening for validity, 314 responses were retained for the quantitative survey and the remaining 14 participants were engaged in qualitative interviews. Quantitative data were analyzed using structural equation modeling to validate the conceptual framework, and qualitative insights were used to complement and contextualize the statistical findings. Findings The findings indicate that seven UTAUT2 factors significantly shaped users’ intention to use voice assistants, which in turn strongly predicted actual usage, highlighting the key mediating role of behavioral intention. Research limitations/implications The study explores the adoption of VAts in airport services in developing countries, extending the UTAUT2 framework. It provides insights for airport managers and developers to design and implement VAts that meet user expectations, improve service efficiency and enhance customer experience, ultimately promoting sustained adoption of technology in public service settings. Originality/value This is among the first studies applying UTAUT2 to VAts adoption in airports within a developing country. It contributes to theoretical expansion and offers practical insights for airport managers and developers to tailor VAts to enhance user experience and encourage sustained usage.

Journal of Hospitality and Tourism InsightsVol. 9(3)
FPT University (VN), Artificial Intelligence in Medicine (Canada) (CA)
Openalex Percentile: Top 83%
AI in Service Interactions
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