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Knowledge identity (KI): a determining factor in the effective use of analytics

Author

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  • Ali Intezari
  • Morteza Namvar
  • Ramin Taghinejad

Abstract

Enterprise systems can play a fundamental role in the management of business analytics by facilitating knowledge management. Nonetheless, and despite extensive studies about enterprise systems and knowledge management over the past four decades, the information systems discipline still lacks a clear and practical understanding of what types of knowledge should be managed by enterprise systems, and how to facilitate the adoption and effective use of business analytics through knowledge management. To a high degree, the issue is rooted in the ambiguity about the nature and sources of knowledge. Motivated by this need, we conducted an exploratory study to address the research question, what knowledge is critical for data analysts to be able to use business analytics effectively? We interviewed 41 data analysts. Using thematic analysis, we propose the theory of knowledge identity, which explains the role of data analysts’ knowledge in the adoption and effective use of analytics in organisations. This study offers significant theoretical and practical implications.

Suggested Citation

  • Ali Intezari & Morteza Namvar & Ramin Taghinejad, 2022. "Knowledge identity (KI): a determining factor in the effective use of analytics," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 20(1), pages 14-33, January.
    • Handle: RePEc:taf:tkmrxx:v:20:y:2022:i:1:p:14-33
    DOI: 10.1080/14778238.2021.1967213
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