An Empirical Analysis of Predictors of AI-Powered Design Tool Adoption
An Empirical Analysis of Predictors of AI-Powered Design Tool Adoption
Author(s): Nguyen Thi Hong Chuyen, Nguyen The VinhSubject(s): Information Architecture, Electronic information storage and retrieval
Published by: UIKTEN - Association for Information Communication Technology Education and Science
Keywords: SEM; AI-powered design tools; UTAUT; factor analysis; empirical analysis
Summary/Abstract: This study examined the relationships among the dimensions of Unified Theory of Acceptance and Use of Technology (UTAUT) and external variables in the context of using artificial intelligence (AI)-powered tools for lecture design. After four months of utilizing the tools, 208 participants took the survey via Google Form. The structural equation model was utilized to analyze the obtained responses. Findings showed that performance expectancy, effort expectancy, social influence, and availability/accessibility are reliable predictors of users' intentions to utilize AI-powered design tools. However, the effects of facilitating conditions and trust and confidence are insignificant. The proposed conceptual model accounted for 54.6% of the data variation. This study provides designers and developers of AI-powered design tools with theoretical and practical implications that can enhance the practical adoption and utilization of these tools.
Journal: TEM Journal
- Issue Year: 12/2023
- Issue No: 3
- Page Range: 1482-1489
- Page Count: 8
- Language: English