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<p>This study explores the application of Voice Assistants (VAts) in providing information and guiding passengers at airports, highlighting their potential as a transformative solution to enhance passenger experience. The study examines the major determinants of Voice Assistant (VAts) adoption and use in the airport setting using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model in conjunction with the Information Acceptance Model (IAM). Data were collected from 314 participants in Vietnam, representing various professions and age groups, with the majority being 18 years and older. In addition, many interviews were conducted with people who frequently work in or use airport services to provide qualitative insights. The Structural Equation Model (SEM) using AMOS was applied to analyze the direct and indirect impacts of the factors in the model to identify the accepted factors (Sig &lt; 0.05) aimed at extracting the core content. The findings indicate important predictive factors for the acceptance of VAts in the Vietnamese context, emphasizing that theoretical insights must be thoroughly examined before practical implementation. These insights provide actionable recommendations for airport authorities and technology developers to design user-centered Voice Assistant (VAts) solutions, enhancing service efficiency and passenger satisfaction at airports.</p>

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Applying voice assistants in providing information and guiding passengers at airports: an empirical investigation using the combined IAM and UTAUT2 models

  • 期刊论文

  • 发表日期：

    2025年7月31日

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  • Vi Loi Truong,
  • Thuong Hong Thi Nguyen,
  • Ngan Tran Huynh Chau

摘要

This study explores the application of Voice Assistants (VAts) in providing information and guiding passengers at airports, highlighting their potential as a transformative solution to enhance passenger experience. The study examines the major determinants of Voice Assistant (VAts) adoption and use in the airport setting using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model in conjunction with the Information Acceptance Model (IAM). Data were collected from 314 participants in Vietnam, representing various professions and age groups, with the majority being 18 years and older. In addition, many interviews were conducted with people who frequently work in or use airport services to provide qualitative insights. The Structural Equation Model (SEM) using AMOS was applied to analyze the direct and indirect impacts of the factors in the model to identify the accepted factors (Sig < 0.05) aimed at extracting the core content. The findings indicate important predictive factors for the acceptance of VAts in the Vietnamese context, emphasizing that theoretical insights must be thoroughly examined before practical implementation. These insights provide actionable recommendations for airport authorities and technology developers to design user-centered Voice Assistant (VAts) solutions, enhancing service efficiency and passenger satisfaction at airports.