Author
Listed:
- Yen-Ling Chou
(Department of Information Management, I-Shou University, No.1, Sec. 1, Syuecheng Rd., Dashu District, 84001 Kaohsiung City, Taiwan)
- Yu-Lung Wu
(Department of Information Management, I-Shou University, No.1, Sec. 1, Syuecheng Rd., Dashu District, 84001 Kaohsiung City, Taiwan)
- Ren-Fang Chao
(Department of Leisure Management, I-Shou University)
Abstract
Against the backdrop of rapid advancements in generative artificial intelligence (GenAI), ChatGPT has emerged as a representative application, drawing significant research interest in user behavior patterns. This study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) Model to investigate the key factors influencing the adoption of ChatGPT among users in Taiwan. Using a cross-sectional survey approach, we recruited a sample of 454 Taiwanese ChatGPT users through social media and online forums. The study analyzed the impact of four key constructs—performance expectancy, effort expectancy, social influence, and facilitating conditions—on behavioral intention and actual usage behavior. The results indicated that performance expectancy and effort expectancy play pivotal roles in shaping behavioral intention, while facilitating conditions significantly affect actual usage behavior. Furthermore, cultural background exerts a critical moderating effect on the influence of social factors. These findings highlight the unique characteristics of user behavior in Taiwan, provide practical insights for optimizing the design and promotion of GenAI tools, and offer valuable implications for technology adoption policies. Key Words:ChatGPT, UTAUT Model, behavioral intention, artificial intelligence applications, technology adoption
Suggested Citation
Yen-Ling Chou & Yu-Lung Wu & Ren-Fang Chao, 2025.
"Applying the UTAUT model to explore user behavior in ChatGPT usage,"
International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 14(2), pages 332-341, March.
Handle:
RePEc:rbs:ijbrss:v:14:y:2025:i:2:p:332-341
DOI: 10.20525/ijrbs.v14i2.4047
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