Big data text analytics: an enabler of knowledge management

Zaheer Khan*, Tim Vorley

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

78 Citations (Scopus)

Abstract

Purpose: The purpose of this paper is to examine the role of big data text analytics as an enabler of knowledge management (KM). The paper argues that big data text analytics represents an important means to visualise and analyse data, especially unstructured data, which have the potential to improve KM within organisations. Design/methodology/approach: The study uses text analytics to review 196 articles published in two of the leading KM journals – Journal of Knowledge Management and Journal of Knowledge Management Research & Practice – in 2013 and 2014. The text analytics approach is used to process, extract and analyse the 196 papers to identify trends in terms of keywords, topics and keyword/topic clusters to show the utility of big data text analytics. Findings: The findings show how big data text analytics can have a key enabler role in KM. Drawing on the 196 articles analysed, the paper shows the power of big data-oriented text analytics tools in supporting KM through the visualisation of data. In this way, the authors highlight the nature and quality of the knowledge generated through this method for efficient KM in developing a competitive advantage. Research limitations/implications: The research has important implications concerning the role of big data text analytics in KM, and specifically the nature and quality of knowledge produced using text analytics. The authors use text analytics to exemplify the value of big data in the context of KM and highlight how future studies could develop and extend these findings in different contexts. Practical implications: Results contribute to understanding the role of big data text analytics as a means to enhance the effectiveness of KM. The paper provides important insights that can be applied to different business functions, from supply chain management to marketing management to support KM, through the use of big data text analytics. Originality/value: The study demonstrates the practical application of the big data tools for data visualisation, and, with it, improving KM.

Original languageEnglish
Pages (from-to)18-34
Number of pages17
JournalJournal of Knowledge Management
Volume21
Issue number1
Early online date13 Feb 2017
DOIs
Publication statusPublished - 13 Feb 2017

Keywords

  • Big data
  • Knowledge management
  • Methodology
  • Text analytics

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