What drives the adoption of data analytics at Australian university libraries in the perspective of UTAUT2?

This study investigates the adoption of data analytics in Australian university libraries from the UTAUT2 perspective, focusing on the factors that influence library professionals' acceptance of analytics. As technology advances, data has become a valuable resource, and the emergence of analytics is often considered a recent development driven by accessible computing power. However, there is a lack of comprehensive research on adopting analytics in Australian university libraries, highlighting the need for a deeper understanding of the factors that influence university library professionals"perceptions of adopting analytics. This research addresses the main question: What factors drive the adoption of data analytics in Australian university libraries? This qualitative study employs a single case study approach with multiple sites involving 16 university libraries and 25 participants. Data collection methods included document analysis and semi-structured interviews with university librarians and analytics experts. The results show that all UTAUT2 constructs - performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit - influence librarians' attitudes and motivations towards adopting analytics applications. Additionally, this study reveals additional factors beyond the original UTAUT2 model, including the absence of data analytics in LIS education curriculums, algorithm training, and data privacy concerns. The study identifies various benefits of analytics adoption in university libraries, such as enhanced collection development planning, insights into user behaviour, improved financial management, and demonstrating library value. However, challenges like skill shortages, complex IT configurations, and privacy legislation must be addressed to effectively implement data analytics. The findings contribute to our understanding of user acceptance of analytics in university libraries, providing valuable insights for library administrators and analytics vendors. By applying the UTAUT2 model, this research enriches our knowledge of technology adoption in the context of university libraries' analytics.