UTAUT as a Model for Understanding Intention to Adopt AI and Related Technologies among Librarians

Document Type

Article

Publication Date

2021

Keywords

UTAUT, Artificial intelligence, Internet of things, Robots, Big data, Cloud computing, AR./VR, LIS education, Public library, Academic library

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.acalib.2021.102437

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.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

The Journal of Academic Librarianship, v. 47, issue 6, art. 102437

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