This research demonstrates how big data analytics enhances user satisfaction and optimizes resource allocation in university libraries.
This research explores the application of Big Data-driven analytics to understand, optimize, and enhance book circulation trends at the Library of Kotelawala Defense University. By leveraging advanced technologies, machine learning, data mining, and predictive analytics, university libraries can enhance their services, optimize resource allocation, and better understand user behavior. Using big data analytics to comprehend circulation patterns poses opportunities for enhancing library services. It highlights how Big Data technology can improve resource utilization, user service, and library operations of user services. The findings suggest that a data-driven approach can improve user satisfaction, quality of services (QoS), efficient collection management, and strategic planning for the library's future development.
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Aruna Thilanka (2024) studied this question.
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