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Literature Review on Big Data: What Do We Know So Far?
University of Skövde, School of Business. University of Skövde, Enterprises for the Future. (Knowledge and Innovation Management (KIM))ORCID iD: 0000-0001-8469-2427
Universidade Federal de Santa Catarina, Brazil. (Knowledge and Innovation Management (KIM))
(Knowledge and Innovation Management (KIM))
2018 (English)In: Big Data in the Arts and Humanities: Theory and Practice / [ed] Giovanni Schiuma, Daniela Carlucci, CRC Press, 2018, p. 3-14Chapter in book (Refereed)
Abstract [en]

The term “big data” has been discussed often in recent years so it is high time for us to determine the current state of knowledge on big data and the benefits and challenges that its applications may bring to individuals, companies, or the society at large. We argue that such work will allow for greater dissemination of results across both academic research and practitioners. The determination of the body of knowledge will help to systematize research, whereas practitioners will get insights into the pros and cons of using big data, which in turn can provide the basis for the improved use of big data or its first-time application, respectively. Based on a systematic review consisting of 87 papers, this chapter proposes a number of future research avenues that can be used to organize the study of big data. The future avenues and the determination of the current body of knowledge about big data are considered the main contributions of this chapter. Next, we briefly discuss the term “big data.” Then the insights into the methodology are provided. After that, the results are presented. This is followed by a discussion about the possible future research opportunities. The chapter terminates with final remarks and conclusions.

Place, publisher, year, edition, pages
CRC Press, 2018. p. 3-14
Keywords [en]
big data, application possibilities, challenges of big data, implications of big data, systematic literature review
National Category
Business Administration
Research subject
Knowledge and Innovation Management (KIM)
Identifiers
URN: urn:nbn:se:his:diva-15110ISBN: 978-1-4987-6585-5 (print)OAI: oai:DiVA.org:his-15110DiVA, id: diva2:1202810
Available from: 2018-05-01 Created: 2018-05-01 Last updated: 2018-07-27Bibliographically approved

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Durst, Susanne

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf