Big Data Analytic Concepts in Libraries: A Systematic Literature Review

Abstract

A library has a lot of primary and secondary data with a wealth of information content. The diversity and improvement of the content can be attributed to the data that is freely available online. These include customer data, service data (loan and return), research data, citation data and other data. Therefore, libraries need to analyze these data as it provides many benefits and added value to the continuity of their services. This systematic review examines the determinants to adopt big data analytic (BDA) in organizations including libraries. The review analyses international literature on determinants to adopt BDA between January 2010 to December 2019 from databases including Emerald, ProQuest, Sage, Science Direct, Scopus, Springer, Web of Science (WOS) and Google Scholar. It uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Literary quality assessments were conducted on BDA concepts based on previous theories and articles. Twenty (20) papers from countries all over the world met the inclusion criteria. The review identified three-concept of BDA in library services; BDA readiness in libraries, model to measure BDA adoption and its implication in the library, and limitations of the existing model or concept of BDA for the library. Most studies reported those BDA concepts are new concepts; data science and libraries; fundamental building block of machine learning and the software instruction set for AI, hard characteristics of data, such as the big data V-characteristics; adoption readiness; and potential to exploit BDA. Future research should focus on a variety of rigorous large-scale methodological studies. Studies should use the quantitative approach to explore specific factors related to promoting BDA adoption. This review can help academics and practitioners understand the key factors for adopting BDA in a library so that BDA activities that enable a library to make practical and strategic preparation can be effectively implemented.