Optimizing AI user experience: Analyzing the impact of trust, engagement, and emotional satisfaction using multiple linear regression

https://doi.org/10.55214/2576-8484.v10i4.12546

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This study examines the effects of trust in AI, happiness from AI interactions, user engagement, AI-influenced purchase intention, and reliance on AI on overall AI user experience. Using a multiple linear regression model and survey data from 200 AI users in Vietnam, the results show that all five factors significantly influence AI user experience (p < 0.001). Among them, happiness from AI interactions emerges as the strongest predictor (β = 0.336), highlighting the critical role of positive emotional responses. Engagement (β = 0.266) and reliance on AI (β = 0.253) also show substantial effects, indicating that frequent interaction and reliance on AI enhance the user experience. Trust in AI (β = 0.230) contributes significantly, emphasizing the importance of transparency and reliability in AI systems. In contrast, AI-driven purchase intention (β = 0.189) shows a weaker influence. The findings underscore the importance of human-centered and ethical AI design. Future research should explore cross-cultural variations and the ethical implications of AI reliance.

How to Cite

Binh, P. T., & Thanh, N. N. (2026). Optimizing AI user experience: Analyzing the impact of trust, engagement, and emotional satisfaction using multiple linear regression. Edelweiss Applied Science and Technology, 10(4), 1–15. https://doi.org/10.55214/2576-8484.v10i4.12546

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Published

2026-03-27