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Cited by 526Big Data Technologies and ApplicationsCompetitive and Knowledge IntelligenceBig Data and Business Intelligence

New games, new rules: big data and the changing context of strategy

Open access
Constantiou, Ioanna D, Kallinikos, Jannis·2015·Journal of Information Technology
DOI 10.1057/jit.2014.17
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Abstract

Big data and the mechanisms by which it is produced and disseminated introduce important changes in the ways information is generated and made relevant for organizations. Big data often represents miscellaneous records of the whereabouts of large and shifting online crowds. It is frequently agnostic, in the sense of being produced for generic purposes or purposes different from those sought by big data crunching. It is based on varying formats and modes of communication (e.g., texts, image and sound), raising severe problems of semiotic translation and meaning compatibility. Crucially, the usefulness of big data rests on their steady updatability, a condition that reduces the time span within which this data is useful or relevant. Jointly, these attributes challenge established rules of strategy making as these are manifested in the canons of procuring structured information of lasting value that addresses specific and long-term organizational objectives. The developments underlying big data thus seem to carry important implications for strategy making, and the data and information practices with which strategy has been associated. We conclude by placing the understanding of these changes within the wider social and institutional context of longstanding data practices and the significance they carry for management and organizations.

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  1. [3]3. Arthur, B. W. (2011). The Second Economy, McKinsey Quarterly, October, http://www.mckinsey.com/insights/strategy/the_second_economy (accessed 11 May 2014).
  2. [12]12. boyd, d. and Crawford, K. (2012). Critical Questions for Big Data, Information, Communication & Society 15(5): 662-679.
  3. [17]17. Chen, D. Q., Mocker, M., Preston, D. S. and Teubner, A. (2010). Information Systems Strategy: Reconcep- tualization, Measurement, and Implications, MIS Quarterly 34(2): 233-259.
  4. [22]22. Ciborra, C. U. (1993). Teams, Markets and Systems, Oxford: Oxford University Press.
  5. [28]28. Davenport, T. H., Barth, P. and Bean, R. (2012). How 'Big Data' is Different, MIT Sloan Management Re- view 54(1): 22-24.
  6. [30]30. Desrosières, A. (1998). The Politics of Large Number: A History of Statistical Reasoning, Cambridge, MA: Harvard University Press.
  7. [53]53. LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S. and Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review 52(2): 21-31.
  8. [61]61. March, J.G. (1999). The Pursuit of Organizational Intelligence: Decisions and Learning, Cambridge, MA: Blackwell.
  9. [70]70. Morville, P. (2005). Ambient Findability, O'Reilly Media Inc.
  10. [75]75. O'Reilly (2012). Big Data Now: 2012 Edition, O'Reilly Media Inc.
  11. [94]94. Thompson, J. D. (1967). Organizations in Action, New York: McGraw & Hill.
  12. [95]95. Yates, J. (1989). Control through Communication: The Rising of System in American Management, Baltimore: John Hopkins University Press.
  13. [98]98. Yoo, Y., Henfridsson, O. and Lyytinen, K. (2010). The New Organizing Logic of Digital Innovation: An Ag- enda for Information Systems Research, Information Systems Research 21(4): 724-735.

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Authors
Constantiou, I. D., & Kallinikos, J.
Affiliations
  • Copenhagen Business School (DK)
  • London School of Economics and Political Science (GB)
Corresponding author
Kallinikos, Jannis
ORCID
Venue
Journal of Information Technology
Publisher
SAGE Publications
Published
2015-03
Volume
30
Issue
1
Pages
44-57
ISSN
  • 0268-3962 (ISSN-L)
  • 1466-4437
DOI
10.1057/jit.2014.17
OpenAlex
W2095422038
Cited by
526
References
116
Citations by year
2026: 36 · 2025: 33 · 2024: 50 · 2023: 58 · 2022: 71 · 2021: 77 · 2020: 65 · 2019: 44 · 2018: 42 · 2017: 24 · 2016: 20 · 2015: 6
FWCI
31.22
Type
journal article
Language
en
Open access
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Journal of Information Technology (publishedVersion)
  • CBS Research Portal (Copenhagen Business School) (publishedVersion)
  • London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
  • Journal of the Association for Information Systems (submittedVersion)
  • IRIS - Institutional Research Information System (Libera Università Internazionale degli Studi Sociali Guido Carli) (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
  • Social Sciences › Business, Management and Accounting › Strategy and Management › Competitive and Knowledge Intelligence
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
Keywords
big data, strategy making, data practices, information practices, semiotic translation, data relevance, organizational goals, data dissemination

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