Nguyen Thi Hoi
Faculty of Economic Information System and E-commerce, Thuongmai University, Hanoi

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The Influence of Augmented Reality Technology on Young Consumers’ Online Purchasing Decisions Nguyen Thi Hoi
Journal of Information Systems Engineering and Business Intelligence Vol. 12 No. 2 (2026): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.12.2.520-533

Abstract

Background: Augmented reality (AR) has emerged as a transformative technology in e-commerce, enabling immersive, interactive, and personalized shopping experiences that help bridge the gap between online and offline retail environments. Although the adoption of AR has gained increasing attention in digital commerce, empirical evidence regarding the determinants of AR-enabled purchasing behavior remains limited, particularly among young consumers in emerging digital economies. Objective: This study aims to examine the factors that influence AR-enabled online purchasing decisions and identify the technological, psychological, social, and behavioral drivers that encourage consumers to adopt AR-supported shopping experiences. The proposed framework is illustrated through a survey conducted among young consumers in Hanoi, Vietnam, to provide empirical evidence. Methods: An integrated research framework was developed based on the TRA, TPB, UTAUT2, and social impact models. We employed a quantitative approach using data collected from 400 respondents who had prior experience using AR features in online shopping. SEM was applied to test the proposed hypotheses and evaluate the relationships among the constructs. Results: The findings indicate that Habit, Belief, Satisfaction, Social Influence, Facilitating Conditions, Perceived Number of Users, Subjective Norms, Effort Expectancy, and Attitude significantly influence consumers’ behavioral intention and purchase decision. In addition, BI serves as a significant mediating mechanism through which AR adoption factors are translated into actual purchasing behavior. Conclusion: By providing a comprehensive framework for understanding consumer adoption of AR technologies in online shopping environments, this study contributes to the growing literature on AR-enabled commerce. The findings offer practical implications for e-commerce platforms, digital retailers, and technology providers seeking to enhance customer engagement, trust, and purchase conversion through AR-enabled shopping experiences. The empirical evidence from Vietnam further enriches the understanding of AR adoption in emerging digital markets while supporting the proposed framework’s broader applicability across e-commerce contexts.   Keywords: Augmented Reality, online purchasing decisions, young consumers, behavioral intention, digital commerce
Generative AI and Youth Creativity: An Extended TAM2 Perspective Nguyen Thi Hoi; Bui Quang Truong; Nguyen Quang Trung; Tran Thi Nhung
Journal of Information Systems Engineering and Business Intelligence Vol. 12 No. 3 (2026): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.12.3.659-672

Abstract

Background: Generative Artificial Intelligence is increasingly transforming learning, work, and creative activities among young people. However, limited evidence explains how technological, social, behavioral, and individual factors jointly influence creativity in Generative Artificial Intelligence-assisted environments.  Objective: This study examines the determinants of Generative Artificial Intelligence usage and their effects on youth creativity by integrating the Technology Acceptance Model 2 and the Componential Theory of Creativity.  Methods: A quantitative survey was conducted with 400 young users who had prior experience with Generative Artificial Intelligence. Data were analyzed using Cronbach’s Alpha, Exploratory Factor Analysis, Confirmatory Factor Analysis, and Structural Equation Modeling.  Results: The proposed model demonstrated excellent fit, with a chi-square to degrees-of-freedom ratio of 1.373, Comparative Fit Index of 0.981, Tucker-Lewis Index of 0.978, and Root Mean Square Error of Approximation of 0.031. Social influence and perceived usefulness significantly promoted habitual use, while technology trendiness and innate creativity positively influenced usage purpose. Usage purpose was the strongest predictor of creativity enhancement, followed by habitual use and innate creativity. The model explained 62% of the variance in creativity enhancement.  Conclusion: Generative Artificial Intelligence serves not only as a productivity tool but also as a catalyst for youth creativity. The integration of the Technology Acceptance Model 2 and the Componential Theory of Creativity highlights how technological, social, behavioral, and individual factors jointly contribute to creativity enhancement, with practical implications for education, policy, and technology development.  Keywords: GenAI, Creativity, TAM2, Componential Theory of Creativity, SEM