UTAUT as a Model for Understanding Intention to Adopt AI and Related Technologies among Librarians |
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| Institution: | 1. School of Information, University of South Florida, Tampa, FL 33620, USA;2. Department of Library and Information Science, Jeonbuk National University Jeonju-si, South Korea;1. Department of Computer Science & Engineering, Indian Institute of Technology, Kharagpur, West Bengal, India;2. School of Management, University of Bradford, Richmond Road, Bradford, BD7 1DP, UK;3. School of Management, Swansea University Bay Campus, Swansea, SA1 8EN, UK;4. Department of Management Information Systems, Faculty of Economics and Administration, King Abdulaziz University, Jeddah, Saudi Arabia;1. Strategy and Innovation, EDC Paris Business School, Department of Entrepreneurship and Digital Transformation, CRE - Observatory and Research Center on Entrepreneurship, France;2. Master of Science in, Digital Marketing and Collaborative Strategies, La Rochelle Business School, Excelia Group, France;3. Marketing, EDC Paris Business School, Department of Digital Marketing, CRE - Observatory and Research Center on Entrepreneurship, France;4. Management, IPAG Business School, France |
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| Abstract: | This study explored the intention to adopt various AI and related technologies by academic and public librarians. A survey was disseminated through various library organization lists to collect input on issues surrounding AI attitude and intentions among librarians in North America. We utilized the Unified Theory of Acceptance and Use of Technology (UTAUT) as a framework and performed structural equation modeling (SEM) and related statistical analyses (using SPSS and AMOS). Our findings confirm that the UTAUT can partially predict the likelihood of AI and related technologies adoption intentions among librarians. The model showed that performance expectancy (PE) and attitude toward use (ATU) of AI and related technologies had significant effects on librarians' intention to adopt AI and related technologies, while social influence (SI) and effort expectancy (EE) did not. We conclude that UTAUT is a viable integrated theoretical framework that, when properly designed and executed within a study, and lends itself to robust statistical analyses such as SEM. UTAUT is helpful as a framework for future approaches to designing and promoting adoption and use of emerging technologies by librarians. |
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