Fostering Library Agility with Big Data

Authors

  • Muhamad Khairulnizam Zaini Faculty of Information Management, UiTM
  • Wan Nor Haliza Wan Mokhtar Faculty of Information Management, UiTM
  • Nora'ayu Ahmad Uzir Faculty of Information Management, UiTM
  • Irni Eliana Khairuddin Faculty of Information Management, UiTM

DOI:

https://doi.org/10.24191/aclim.v2i1.19

Keywords:

Library Agility, Big Data, Big Data Capability, Agile Libraries

Abstract

The increasing complexity of the information environment has spurred libraries to increase their relevance. Increasing the agility of libraries is worth considering. In the context for this study, Agile library is a user-centred library that permits flexibility, to take risks, and to make responsive changes that address its users’ needs, while Big Data is one of many emerging technologies available to foster agility in libraries. Big Data have offered libraries and librarians new ways and methods to collect and analyse data to justify their value and contributions, while at the same time being innovative, flexible, and responsive in giving superior services to its users. This signifies the importance of such technological integrations in the library environment. Against this background, this paper will focus on the perspectives and future agenda of how library agility could be fostered in the Big Data era. This paper will discuss the concepts of Agile Libraries and how Big Data capabilities could become the determinants for library agility. The biggest limitation of this work is that it remains at the conceptual level and requires empirical research and testing to validate the model. Conceptualizing both concepts of library agility and Big Data capabilities are expected to provide the opportunities for future research directions in library with Big Data technology.

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Published

01-08-2022

How to Cite

Zaini, M. K., Wan Mokhtar, W. N. H., Ahmad Uzir, N., & Khairuddin, I. E. (2022). Fostering Library Agility with Big Data. Journal of Academic Library Management (AcLiM), 2(1), 33–45. https://doi.org/10.24191/aclim.v2i1.19

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Articles