Big data analytics in university libraries on today's librarianship decision-making: A disruptive innovation perspective

This study explores the transformative impact of big data analytics on university libraries, examining its potential to disrupt traditional systems and services through the lens of Clayton Christensen’s four-step framework. A qualitative case study approach was employed involving semi-structured interviews with 25 participants from five groups of Australian university libraries (independent universities and the mem bers of Innovative Research Universities, the Regional Universities Network, the Group of Eight and the Australian Technology Network). The data collection occurred between 2018 and 2022. The findings con f irm the disruptive potential of big data analytics in modern librarianship, enhancing decision-making and demonstrating libraries’ value. Its adoption is revolutionising librarians’ decision-making practices, signifying a major shift towards data-driven approaches. This study contributes to the field of library and information science, applying the theory of disruptive technologies to analyse the importance of big data analytics in librarianship decision-making. The study’s recommendations lay a foundation for future research and pro vide actionable strategies for implementing big data analytics in university libraries to enable informed deci sion-making and fully harness its potential. Additionally, this study makes a significant contribution to the existing literature on analytics adoption, particularly in the context of emerging and disruptive innovations. The findings have far-reaching practical implications for Australian libraries, emphasising the need to adopt big data analytics tools to elevate decision-making processes and enhance user experiences.