摘要
AbstractAlthough artificial intelligence (AI) is currently a prominent technology that has received increasing attention, the factors affecting users’ AI device adoption for healthcare were less discussed. Drawing on affordance-actualization theory and literature on AI, uniqueness theory, and healthcare, we developed a research model to explain users’ adoption intention of AI devices in the healthcare context. Data collected from 307 potential users in China were used to test the proposed model. Our findings indicated that data capture, classification, and social affordances impacted self-monitoring significantly, while data capture and social affordances were the predators of uniqueness enhancement. The self-monitoring, on the other hand, had a positive influence on uniqueness enhancement. Finally, our results revealed that self-monitoring and uniqueness enhancement have significant effects on AI adoption. From the findings, theoretical and practical implications are discussed.Keywords: AI adoptionaffordance-actualization theoryAI affordanceself-monitoringuniqueness enhancement Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsShi-Zhu LiangShi-Zhu Liang is currently an associate professor at the Department of Marketing, Yang-En University, China. Her current research interests include electronic commerce, information management and data management and application. She has published articles in Sustainability, Journal of Computer Information Systems, and others.Chun-Ming ChangChun-Ming Chang is currently a professor at the Department of International Business, Ming Chuan University, Taiwan. His current research interests include electronic commerce and knowledge management. He has published articles in Decision Support Systems, Information Systems Journal, International Journal of Human–Computer Studies, Behaviour and Information Technology and People, and others.Chiung-Hui HuangChiung-Hui Huang, a PhD student at the Department of Information Management, National Sun Yat-sen University. Her research interests include blockchain technology and marketing management.