Advertisement

Journal of Information Technology

, Volume 30, Issue 1, pp 44–57 | Cite as

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

  • Ioanna D Constantiou
  • Jannis Kallinikos
Research Article

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.

Keywords

big data business environment data practices management social data strategy making 

References

  1. Aaltonen, A. and Tempini, N. (2014). Everything Counts in Large Amounts: A critical realist case study on data-based production, Journal of Information Technology 29 (1): 97–110.CrossRefGoogle Scholar
  2. Alaimo, C. (2014). Computational Consumption: Social media and the construction of digital consumers, PhD Thesis. Department of Management, London School of Economics.Google Scholar
  3. Anderson, C. (2008). The End of Theory: The Data Deluge Makes the Scientific Method Obsolete, Wired Magazine, July, [www document] http://www.wired.com/science/discoveries/magazine/16-07/pb_theory (accessed 11 May 2014).
  4. Ayres, I. (2007). Super Crunches: How anything can be predicted, London: John Murray.Google Scholar
  5. Barney, J. (1986). Strategic Factor Markets: Expectations, luck and business strategy, Management Science 17 (1): 99–120.Google Scholar
  6. Beniger, J.R. (1986). The Control Revolution: Technological and economic origins of the information society, Cambridge, MA: Harvard University Press.Google Scholar
  7. Bhimani, A. and Willcocks, L. (2014). Digitisation, ‘Big Data’ and the Transformation of Accounting Information, Accounting and Business Research 44 (4): 1–22.CrossRefGoogle Scholar
  8. Bollier, D. (2010). The Promise and Perils of Big Data, The Aspen Institute, [www document] http://www.aspeninstitute.org/publications/promise-peril-big-data (accessed 11 May 2014).
  9. Borgmann, A. (1999). Holding on to Reality: The nature of information at the turn of the millennium, Chicago: The University of Chicago Press.CrossRefGoogle Scholar
  10. Bowker, G.C. (2005). Memory Practices in Sciences, Cambridge, MA: The MIT Press.Google Scholar
  11. Bowker, G.C. and Star, S.L. (1999). Sorting Things Out: Classification and its consequences, inside technology, Cambridge, MA: The MIT Press.Google Scholar
  12. Boyd, d. and Crawford, K. (2012). Critical Questions for Big Data, Information, Communication & Society 15 (5): 662–679.CrossRefGoogle Scholar
  13. Brynjolfsson, E. and McAfee, A. (2014). The Second Machine Age: Work, progress, and prosperity in a time of brilliant technologies, New York: WW Norton & Company.Google Scholar
  14. Carter, C., Clegg, S.R. and Kornberger, M. (2008). A Very Short, Fairly Interesting and Reasonably Cheap Book about Studying Strategy, London: SAGE Publications.Google Scholar
  15. Castells, M. (2001). The Internet Galaxy: Reflections on the internet, business, and society, New York: Oxford University Press.CrossRefGoogle Scholar
  16. Caves, R.E. (1964). American Industry: Structure, conduct, performance, New Jersey: Prentice-Hall.Google Scholar
  17. Chen, H., Chiang, R.H. and Storey, V.C. (2012). Business Intelligence and Analytics: From big data to big impact, MIS Quarterly 36 (4): 1165–1188.Google Scholar
  18. Choi, H. and Varian, H. (2012). Predicting the Present with Google Trends, Economic Record 88 (s1): 2–9.CrossRefGoogle Scholar
  19. Clemons, E.K. (2009). Business Models for Monetizing Internet Applications and Web Sites: Experience, theory, and predictions, Journal of Management Information Systems 26 (2): 15–41.CrossRefGoogle Scholar
  20. Clemons, E.K., Reddi, S.P. and Row, M.C. (1993). The Impact of Information Technology on the Organization of Economic Activity: The ‘move to the middle’ hypothesis, Journal of Management Information Systems 10 (2): 9–35.CrossRefGoogle Scholar
  21. Ciborra, C.U. (1993). Teams, Markets and Systems, Oxford: Oxford University Press.Google Scholar
  22. Connors, B.L., Rende, R. and Colton, T.J. (2014). Inter-Rater Reliability for Movement Pattern Analysis (MPA): Measuring patterning of behaviors versus discrete behavior counts as indicators of decision-making style, Personality and Social Psychology 5: 605.Google Scholar
  23. Cordella, A. (2006). Transaction Costs and Information Systems: Does IT add up? Journal of Information Technology 21 (3): 195–202.CrossRefGoogle Scholar
  24. Cyert, R. and March, J.G. (1963). The Behavioral Theory of the Firm, Englewood Cliffs: Prentice Hall.Google Scholar
  25. D’aveni, R.A. and Gunther, R.E. (1994). Hypercompetition: Managing the dynamics of strategic maneuvering, New York: The Free Press, Simon and Schuster.Google Scholar
  26. Davenport, T. (2014). Big Data at Work: Dispelling the myths, uncovering the opportunities, Boston, MA: Harvard Business Review Press.CrossRefGoogle Scholar
  27. Davenport, T.H., Barth, P. and Bean, R. (2012). How ‘Big Data’ is Different, MIT Sloan Management Review 54 (1): 22–24.Google Scholar
  28. Davenport, T.H., Cohen, D. and Jakobson, A. (2005). Competing on Analytics, Babson Park, MA: Babson Executive Education.Google Scholar
  29. Desrosières, A. (1998). The Politics of Large Number: A history of statistical reasoning, Cambridge, MA: Harvard University Press.Google Scholar
  30. Drnevich, P. and Croson, D. (2013). Information Technology and Business-Level Strategy: Toward an integrated theoretical perspective, MIS Quarterly 37 (2): 483–509.Google Scholar
  31. Dosi, G., Nelson, R.R. and Winter, S.G. (2001). The Nature and Dynamics of Organizational Capabilities, New York: Oxford University Press.CrossRefGoogle Scholar
  32. Eco, U. (2000). Kant and the Platypus: On language and cognition, London: Vintage.Google Scholar
  33. Eggers, J.P. and Kaplan, S. (2013). Cognition and Capabilities: A multi-level perspective, The Academy of Management Annals 7 (1): 293–338.CrossRefGoogle Scholar
  34. Ekbia, H. and Evans, T. (2009). Regimes of Information: Land use, management, and policy, The Information Society 25 (5): 328–343.CrossRefGoogle Scholar
  35. Ekbia, H., Mattioli, M., Kouper, I., Arave, G., Ghazinejad, A., Bowman, T., Suri, V.R., Tsou, A., Weingart, S. and Sugimoto, C.R. (2014). Big Data, Bigger Dilemmas: A critical review, Journal of the American Society for Information Science and Technology, forthcoming.Google Scholar
  36. Ferrier, W.J., Smith, K.G. and Grimm, C.M. (1999). The Role of Competitive Action in Market Share Erosion and Industry Dethronement: A study of industry leaders and challengers, Academy of Management Journal 42 (4): 372–388.CrossRefGoogle Scholar
  37. Floridi, L. (2012). Big Data and their Epistemological Challenge, Philosophy and Technology 48 (2): 103–121.Google Scholar
  38. Gavetti, G. (2012). PERSPECTIVE – Toward a behavioral theory of strategy, Organization Science 23 (1): 267–285.CrossRefGoogle Scholar
  39. Gavetti, G. and Levinthal, D. (2000). Looking Forward and Looking Backward: Cognitive and experiential search, Administrative Science Quarterly 45 (1): 113–137.CrossRefGoogle Scholar
  40. Gavetti, G. and Rivkin, J.W. (2007). On the Origin of Strategy: Action and cognition over time, Organization Science 18 (3): 420–439.CrossRefGoogle Scholar
  41. George, G., Haas, M.R. and Pentland, A. (2014). Big Data and Management, Academy of Management Journal 57 (2): 321–326.CrossRefGoogle Scholar
  42. Gillespie, T. (2014). The Relevance of Algorithms, in T. Gillespie, P. Boczkowski and K. Foot (eds.) Media Technologies, Cambridge, MA: MIT Press, pp 167–193.Google Scholar
  43. Iansiti, M. and Levien, R. (2004). The Keystone Advantage: What the new dynamics of business ecosystems mean for strategy, innovation, and sustainability, Boston, MA: Harvard Business School Press.Google Scholar
  44. IDC (2011). Digital Universe Study: Extracting Value from Chaos [www document] http://www.emc.com/collateral/analyst-reports/idc-extracting-value-from-chaos-ar.pdf (accessed 11 May 2014).
  45. Jarzabkowski, P., Balogun, J. and Seidl, D. (2007). Strategizing: The challenges of a practice perspective, Human Relations 60 (1): 5–27.CrossRefGoogle Scholar
  46. Kallinikos, J. (2006). The Consequences of Information: Institutional implications of technological change, Cheltenham: Elgar.CrossRefGoogle Scholar
  47. Kallinikos, J. (2009). The Making of Ephemeria: On the shortening life spans of information, The International Journal of Interdisciplinary Social Sciences 4 (3): 227–236.CrossRefGoogle Scholar
  48. Kallinikos, J. (2013). The Allure of Big Data, Mercury Magazine 2 (3): 40–43.Google Scholar
  49. Kallinikos, J., Aaltonen, A. and Marton, A. (2013). The Ambivalent Ontology of Digital Artifacts, MIS Quarterly 37 (2): 357–370.Google Scholar
  50. Kallinikos, J. and Mariategui, J.-C. (2011). Video as Digital Object: Production and distribution of video content in the internet media ecosystem, The Information Society 27 (5): 281–294.CrossRefGoogle Scholar
  51. Lajili, K. and Mahoney, J.T. (2006). Revisiting Agency and Transaction Costs Theory Predictions on Vertical Financial Ownership and Contracting: Electronic integrations as an organizational form choice, Managerial and Decision Economics 27 (7): 573–586.CrossRefGoogle Scholar
  52. 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.Google Scholar
  53. Learned, E.P., Christensen, C.R., Andrews, K.E. and Guth, W.D. (1965). Business Policy: Text and cases, Homewood, IL: RD Irwin.Google Scholar
  54. Lee, Y., Madnick, S., Wang, R., Wang, F. and Zhang, H. (2014). A Cubic Framework for the Chief Data Officer: Succeeding in a world of big data, MIS Quarterly Executive 13 (1): 1–13.Google Scholar
  55. Lim, J.H., Stratopoulos, T.C. and Wirjanto, T.S. (2011). Path Dependence of Dynamic Information Technology Capability: An empirical investigation, Journal of Management Information Systems 28 (3): 45–84.CrossRefGoogle Scholar
  56. Luhmann, N. (1982). The Differentiation of Society, New York: Columbia University Press.Google Scholar
  57. Luhmann, N. (1993). Risk: A Sociological Theory, New York: A. de Gruyter.Google Scholar
  58. Malone, T.W., Yates, J. and Benjamin, R.I. (1987). Electronic Markets and Electronic Hierarchies, Communications of the ACM 30 (6): 484–497.CrossRefGoogle Scholar
  59. Manovich, L. (2001). The Language of New Media, Cambridge, MA: The MIT Press.Google Scholar
  60. March, J.G. (1999). The Pursuit of Organizational Intelligence: Decisions and learning, Cambridge, MA: Blackwell.Google Scholar
  61. Mayer-Schönberger, V. and Cukier, K. (2013). Big Data: A revolution that will transform how we live, work, and think, London: John Murray.Google Scholar
  62. McAfee, A. and Brynjolfsson, E. (2012). Big Data: The management revolution, Harvard Business Review (October): 1–9.Google Scholar
  63. McGee, J. and Thomas, H. (1986). Strategic Groups: Theory, research and taxonomy, Strategic Management Journal 7 (2): 141–160.CrossRefGoogle Scholar
  64. Melville, N., Kraemer, K. and Gurbaxani, V. (2004). Review: Information technology and organizational performance: An integrative model of IT business value, MIS Quarterly 28 (2): 283–322.Google Scholar
  65. Merali, Y., Papadopoulos, T. and Nadkarni, T. (2012). Information Systems Strategy: Past, present, future? Journal of Strategic Information Systems 21 (2): 125–153.CrossRefGoogle Scholar
  66. Mingers, J. and Willcocks, L. (2014). An Integrative Semiotic Framework for Information Systems: The social, personal and material worlds, Information and Organization 24 (1): 48–70.CrossRefGoogle Scholar
  67. Mintzberg, H. (1991). The Five Ps for Strategy, in H. Mintzberg and J.B. Quinn (eds.) The Strategy Process: Concepts, contexts, cases, Englewood Cliffs, NJ: Prentice-Hall, pp 12–19.Google Scholar
  68. Moretti, F. (2005). Graphs, Maps, Trees: Abstract models of literary history, London: Verso.Google Scholar
  69. Morville, P. (2005). Ambient Findability, Sebastopol, CA: O’Reilly Media.Google Scholar
  70. Nelson, R.R. and Winter, S.G. (1982). An Evolutionary Theory of Economic Change, Cambridge MA: Belknap.Google Scholar
  71. Nelson, R.R. and Winter, S.G. (2002). Evolutionary Theorizing in Economics, Journal of Economic Perspectives 16 (2): 23–46.CrossRefGoogle Scholar
  72. Newman, H.H. (1978). Strategic Groups and the Structure-Performance Relationship, The Review of Economics and Statistics 60 (3): 417–427.CrossRefGoogle Scholar
  73. Oestreicher-Singer, G. and Zalmanson, L. (2013). Content or Community? A digital business strategy for content providers in the social age, MIS Quarterly 37 (2): 591–616.Google Scholar
  74. O’Reilly (2012). Big Data Now: 2012 edition, Sebastopol, CA: O’Reilly Media.Google Scholar
  75. Penrose, E.T. (1966). The Theory of the Growth of the Firm, Oxford: Basil Blackwell.Google Scholar
  76. Peteraf, M.A. (1993). The Cornerstones of Competitive Advantage: A resource based view, Strategic Management Journal 14 (3): 479–488.CrossRefGoogle Scholar
  77. Pfeffer, J. and Sutton, R.I. (2006). Hard Facts, Dangerous Halftruths, and Total Nonsense: Profiting from evidence-based management, Cambridge, MA: Harvard Business School Press.Google Scholar
  78. Pitelis, C.N. and Teece, D.J. (2009). The (New) Nature and Essence of the Firm, European Management Review 6 (1): 5–15.CrossRefGoogle Scholar
  79. Porter, M.E. (1980). Competitive Strategy: Techniques for analyzing industries and competitors, New York: The Free Press.Google Scholar
  80. Porter, M.E. (1985). Competitive Advantage: Creating and sustaining superior performance, New York: The Free Press.Google Scholar
  81. Porter, M.E. (1996). What is Strategy? Harvard Business Review 74 (6): 61–78.Google Scholar
  82. Porter, T.M. (1995). Trust in Numbers: The pursuit of objectivity in science and public life, New Jersey: Princeton University Press.Google Scholar
  83. Priem, R.L., Butler, J.E. and Li, S. (2013). Toward Reimagining Strategy Research: Retrospection and prospection on the 2011 AMR decade award article, Academy of Management Review 38 (4): 471–489.CrossRefGoogle Scholar
  84. Ray, G., Xue, L. and Barney, J.B. (2013). Impact of Information Technology Capital on Firm Scope and Performance: The role of asset characteristics, Academy of Management Journal 56 (4): 1125–1147.CrossRefGoogle Scholar
  85. Rosenfeld, l. and Morville, P. (2002). Information Architecture for the World Wide Web, Sebastopol, CA: O’Reilly Media.Google Scholar
  86. Rousseau, D.M. (2006). Is There Such a Thing as Evidence Based Management? Academy of Management Review 31 (2): 256–269.CrossRefGoogle Scholar
  87. Schmarzo, B. (2013). Big Data: Understanding how data powers big business, Indianapolis, IN: John Wiley & Sons.Google Scholar
  88. Schumpeter, J.A. (1934). The Theory of Economic Development, Cambridge, MA: Harvard University Press.Google Scholar
  89. Shollo, A. and Constantiou, I. (2013). Self-Reinforcing Mechanisms and Organizational Decision Making: The case of project prioritization in a financial institution, in J. Sydow and G. Schreyögg (eds.) Self-Reinforcing Processes in and among Organizations, London: Palgrave Macmillan, pp. 104–124.CrossRefGoogle Scholar
  90. Teece, D.J. (2007). Explicating Dynamic Capabilities: The nature and microfoundations of (sustainable) enterprise performance, Strategic Management Journal 28 (13): 1319–1350.CrossRefGoogle Scholar
  91. Teece, D.J. and Pisano, G. (1994). The Dynamic Capabilities of Enterprises: An introduction, Industrial and Corporate Change 3 (3): 537–556.CrossRefGoogle Scholar
  92. Teece, D.J., Pisano, G. and Shuen, A. (1997). Dynamic Capabilities and Strategic Management, Strategic Management Journal 18 (7): 509–533.CrossRefGoogle Scholar
  93. Thompson, J.D. (1967). Organizations in Action, New York: McGraw & Hill.Google Scholar
  94. Van Dijck, J. (2013). The Culture of Connectivity: A critical history of social media, Oxford: Oxford University Press.CrossRefGoogle Scholar
  95. Varian, H.R. (2010). Computer Mediated Transactions, American Economic Review 100 (2): 1–10.CrossRefGoogle Scholar
  96. Weinberger, D. (2007). Everything is Miscellaneous: The power of the new digital disorder, New York: Times Books.Google Scholar
  97. Wernerfelt, B. (1984). A Resource-Based View of the Firm, Strategic Management Journal 5 (2): 272–280.CrossRefGoogle Scholar
  98. Yates, J. (1989). Control through Communication: The rising of system in American management, Baltimore: John Hopkins University Press.Google Scholar
  99. Yoo, Y. (2010). Computing in Everyday Life: A call for research on experiential computing, MIS Quarterly 34 (2): 213–231.Google Scholar
  100. Yoo, Y. (2013). The Tables Have Turned: How can the information systems field contribute to technology and innovation management research, Journal of the Association of Information Systems 14 (5): 227–236.Google Scholar
  101. Zuboff, S. (1988). In the Age of the Smart Machine: The future of work and power, Oxford: Heinemann Professional.Google Scholar
  102. Zuboff, S. and Maxmin, J. (2003). The Support Economy: How corporations fail individuals and the next episode of capitalism, London: Allen Lane.Google Scholar

Copyright information

© Association for Information Technology Trust 2014

Authors and Affiliations

  1. 1.Department of IT ManagementCopenhagen Business SchoolCopenhagenDenmark
  2. 2.Department of ManagementInformation Systems and Innovation Group, The London School of Economics and Political ScienceLondonUK

Personalised recommendations