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Complexity and Information Systems: The Emergent Domain

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Enacting Research Methods in Information Systems

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Abstract

This paper is concerned with the emergence of the information systems (IS) domain as a central feature of the management research landscape in the networked world. It shows that the emergence of the network economy and network society (Castells, 1996) necessitates a paradigm shift in the IS discipline, and that complexity science offers the apposite concepts and tools for effecting such a shift.

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References

  • Abu-Mostafa, Y.S., LeBaron, B., Lo, A.W. and Weigend, A.S. (eds.) (1999). Computational Finance, Cambridge, MA: MIT Press.

    Google Scholar 

  • Albert, R. and Barabassi, A. (2000). Statistical Mechanics of Complex Networks, Review of Modern Physics 74: 47–97.

    Article  Google Scholar 

  • Albert, R., Joeng, H. and Barabassi, A. (2000). Attack and Error Tolerance of Complex Networks, Nature 406: 378–382.

    Article  Google Scholar 

  • Anderson, P. (1999). Complexity Theory and Organization Science, Organization Studies 10(3): 216–232.

    Google Scholar 

  • Anderson, P., Meyer, A., Eisenhardt, K., Carley, K. and Pettigrew, A. 1999. Introduction to the Special Issue: Applications of complexity theory to organization science, Organization Science 10: 233–236.

    Article  Google Scholar 

  • Arthur, W., Lane, D. and Durlaff, S. (eds.) (1997). The Economy as an Evolving Complex System II, Reading, MA: Addison-Wesley.

    Google Scholar 

  • Axelrod, R. (1984). The Evolution of Cooperation, New York: Basic Books.

    Google Scholar 

  • Axelrod, R. and Cohen, M. (1999). Harnessing Complexity: Organizational Implications of a Scientific Frontier, New York: Free Press.

    Google Scholar 

  • Axtell, R. (2000). Why Agents? On the Varied Motivations for Agent Computing in the Social Sciences, Center on Social and Economic Dynamics Working Paper No. 17, November 2000, Washington: The Brookings Institution.

    Google Scholar 

  • Barabasi, A. (2002). Linked: The New Science of Networks, Massachusetts: Perseus Publishing.

    Google Scholar 

  • Bar-Yam, Y. (2000). About Complex Systems, http://necsi.net/guide/

  • Berlekamp, J., Conway, J. and Guy, R. (1982). Winning Ways for Your Mathematical Plays, New York: Academic Press.

    Google Scholar 

  • Bonabeau, E. (2002). Predicting the Unpredictable, Harvard Business Review 80(3): 109–116.

    Google Scholar 

  • Bonabeau, E and Meyer, C (2001). Swarm Intelligence, Harvard Business Review 79(5): 106–114.

    Google Scholar 

  • Brown, S.L. and Eisenhardt, K.M. (1997). The Art of Continuous Change: Linking complexity theory and time-based evolution in relentlessly shifting organizations, Administrative Science Quarterly 42: 1–34.

    Article  Google Scholar 

  • Buchanan, M. (2002). Nexus, New York, NY: Norton.

    Google Scholar 

  • Burt, R.S. (1992). Structural Holes: The Social Structure of Competition, Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Burt, R.S. (1997). The Contingent Value of Social Capital, Administrative Science Quaterly 42(2): 339–365.

    Article  Google Scholar 

  • Capra, F. (1996). The Web of Life, London: HarperCollins.

    Google Scholar 

  • Castells, M. (1996). The Rise of the Network Society, Oxford: Blackwell Publishers.

    Google Scholar 

  • Casti, J. (1997). Would-Be Worlds: How Simulation is Changing, Wiley: New York.

    Google Scholar 

  • Chaitin, G. (1990). Information, Randomness, and Incompleteness, Singapore: World Scientific Co.

    Book  Google Scholar 

  • Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly 13(3): 319–340.

    Article  Google Scholar 

  • Eisenhardt, K. and Galunic, C. (1999). Coevolving: At last, a way to make synergies work, Harvard Business Review 78(1): 91–99.

    Google Scholar 

  • Epstein, J.M. and Axtell, R. (1996). Growing Artificial Societies: Social Science from the Bottom Up, Washington, DC and Cambridge, MA: Brookings Press and MIT Press.

    Google Scholar 

  • Evans, P. and Wurster, T. (2000). Blown to Bits: How The New Economics of Information Transforms Strategy, Cambridge, MA: Harvard Business School Press.

    Google Scholar 

  • Gilbert, N. and Troitzsch, K.G. (1999). Simulation for the Social Scientist, Philadelphia, PA: Open University Press.

    Google Scholar 

  • Gleick, J. (1987). Chaos: Making a New Science, New York: Viking-Penguin.

    Google Scholar 

  • Granovetter, M. (1973). The Strength of Weak Ties, The American Journal of Sociology 78/6: 1360–1380.

    Article  Google Scholar 

  • Granovetter, M. (1985). Economic Action and Social Structure: The problem of embeddedness, American Journal of Sociology 91: 481–510.

    Article  Google Scholar 

  • Granovetter, M (1995). Coase Revisited: Business groups in modern society, Ind. Corp Change 4: 93–131.

    Article  Google Scholar 

  • Guastello, S.J. (1995). Chaos, Catastrophe and Human Affairs: Applications of Nonlinear Dynamics to Work, Organizations, and Social Evolution, Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Hamel, G. and Prahalad, C. (1994). Competing for the Future, Boston, MA: Harvard Business School Press.

    Google Scholar 

  • Hiltz, S.R. and Johnson, K. (1990). User Satisfaction with Computer-Mediated Systems, Management Science 36(6): 739–764.

    Article  Google Scholar 

  • Holland, J.H. (1995). Hidden Order, Reading, MA: Addison-Wesley.

    Google Scholar 

  • Holland, J.H. (1998). Emergence: From Chaos to Order, Oxford: Oxford University Press.

    Google Scholar 

  • Ilgen, D.R. and Hulin, C.L. (2000). Computational Modeling of Behavior in Organizations: The Third Scientific Discipline, Washington, DC: American Psychological Association.

    Book  Google Scholar 

  • Jarvanpaa, S. (1989). Effects of Task Demand and Graphical Format on Information Processing Strategies, Management Science 35(3): 285–303.

    Article  Google Scholar 

  • Kant, I. (1790). Critique of Judgement (translated by J. Meredith). New York: Oxford University Press, 1973.

    Google Scholar 

  • Kauffman, S. (1993). The Origins of Order: Self-Organization and Selection in Evolution, New York, NY: Oxford University Press.

    Google Scholar 

  • Kauffman, S. (1995). At Home in the Universe: The Search for Laws of Self-Organisation and Complexity, New York, NY: Oxford University Press.

    Google Scholar 

  • Kuhnb, T. (1962). The Structure of Scientific Revolutions, Chicago: Chicago University Press.

    Google Scholar 

  • Langton, C.G. (1991). Computation at the Edge of Chaos: Phase-Transitions and Emergent Computation, Ph.D. dissertation, University of Michigan.

    Google Scholar 

  • Leavitt, H. and Whistler, T. (1958). Management in the 1980s, Harvard Business Review 36: 41–48.

    Google Scholar 

  • Lichtenstein, B.B. and McKelvey, B. (2006). Toward a Theory of Emergence by Stages: Complexity dynamics, self-organization, and power laws in firms. Working paper, Boston, MA: Management/Marketing Department, University of Massachusetts.

    Google Scholar 

  • Lorenz, E. 1963. Deterministic Nonperiodic Flow, Journal of the Atmospheric Sciences 20: 130–141.

    Article  Google Scholar 

  • Maguire, S., Mckelvey, B., Mirabeau, L. and Öztas, N. (2006). Complexity Science and Organization Studies, in S.R. Clegg, C. Hardy and T. Lawrence (eds.) The Sage Handbook of Organization Studies, (2nd edn), Thousand Oaks, CA: Sage.

    Google Scholar 

  • Marcus, L.M. (1983). Power, Politics and MIS Implementation, Communication of the ACM 26: 430–440.

    Article  Google Scholar 

  • Maturana, H. and Varela, F.J. (1973). Autopoiesis: The Organization of the living, in H.R. Maturana and F.J. Varela (eds.) Autopoiesis and Cognition: The Realization of the Living, Vol. 42, Boston Studies in the Philosophy of Science, Dordrecht, Holland: D. Reidel Publishing Company.

    Google Scholar 

  • McKelvey, B. (1997). Quasi-Natural Organization Science, Organization Science 8: 351–381.

    Article  Google Scholar 

  • Merali, Y. (1997). Information, Systems and Dasein, in F. Stowell, I. McRobb, R. Landor, R. Ison and J. Holloway (eds.) Systems for Sustainability: People Organisations and Environments, New York: Plenum Press. 595–600.

    Chapter  Google Scholar 

  • Merali, Y. (2000). The Organic Metaphor in Knowledge Management, Emergence, Special Issue on Organic Knowledge Management 2(4): 14–22.

    Google Scholar 

  • Merali, Y. (2004a). Ethics in an Inter-Connected World. Proceedings of International Conference on Corporate Social Responsibility, November 2004, Korea, pp. 45–65.

    Google Scholar 

  • Merali, Y. (2004b). Complexity and Information Systems, in J. Mingers and L. Willcocks (eds.) Social Theory and Philosophy of Information Systems, London: Wiley. pp. 407–446.

    Google Scholar 

  • Merali, Y. (2005). Complexity Science and Conceptualisation in the Internet Enabled World, 21st Colloquium of the European Group for Organisational Studies, July 2005, Berlin.

    Google Scholar 

  • Morgan, G. (1986). Images of Organization, California: Sage.

    Google Scholar 

  • Moser, I. and Law, J. (2006). Fluids or Flows? Information and Calculation in Medical Practice, Information Technology & People 19(1): 55–73.

    Article  Google Scholar 

  • Orlikowski, W. (1992). The Duality of Technology: Rethinking the concept of technology in organizations, Organisation Science 3(3): 398–427.

    Article  Google Scholar 

  • Orlikowski, W.J. (1996). Improvising Organizational Transformation Over Time: A situated change perspective, Information Systems Research 7(1): 63–92.

    Article  Google Scholar 

  • Potanin, A., Noble, J., Frean, M. and Biddle, R. (2005). Scale-Free Geometry in OO Programs, Communications of the ACM 48(5): 99–103.

    Article  Google Scholar 

  • Prietula, M.J., Carley, K.M. and Gasser, L. (eds.) (1998). Simulating Organizations: Computational Models of Institutions and Groups, Cambridge, MA: MIT Press.

    Google Scholar 

  • Prigogine, I. (1967). Dissipative Structures in Chemical Systems, in S. Claessons (ed.) Fast reactions and Primary Processes in Chemical Kinetics, New York: Interscience.

    Google Scholar 

  • Shapiro, C. and Varian, H. (1999). Information Rules: A Strategic Guide to the Network Economy, Cambridge, MA: Harvard Business School Press.

    Google Scholar 

  • Sigmund, K. (1993). Games of Life, New York: University Press.

    Google Scholar 

  • Stacey, R. (2001). Complex responsive Processes in Organisations: Learning and Knowledge Creation, London: Routledge.

    Google Scholar 

  • Stacey, R.D. (1992). Managing the Unknowable: Strategic Boundaries Between Order and Chaos in Organizations, San Francisco, CA: Jossey-Bass.

    Google Scholar 

  • Tesfatsion, L. and Judd, K. (2006). Handbook of Computational Economics (2nd edn.), Amsterdam: North-Holland/Elsevier Science.

    Google Scholar 

  • Wasserman, S. and Faust, K. (1994). Social Network Analysis: Methods and Applications, Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Watts, D.J. (1999). Small Worlds: The Dynamics of Networks between Order and Randomness, Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Watts, D. (2003). Six Degrees: Small Worlds and the Groundbreaking Science of Networks, New York: Norton.

    Google Scholar 

  • Watts, D.J. and Strogatz, S.H. (1998). Collective Dynamics of ‘Small World’ Networks, Nature 395: 440–442.

    Article  Google Scholar 

  • Zuboff, S. (1988). In the Age of the Smart Machine — The Future of Work and Power, New York: Basic Books Inc.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Warwick Business School, The University of Warwick, UK

    Yasmin Merali

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  1. Yasmin Merali
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Editors and Affiliations

  1. London School of Economics and Political Science, London, UK

    Leslie P. Willcocks

  2. Oxford University, Oxford, UK

    Chris Sauer

  3. University of Missouri-St Louis, St Louis, Missouri, USA

    Mary C. Lacity

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Merali, Y. (2016). Complexity and Information Systems: The Emergent Domain. In: Willcocks, L.P., Sauer, C., Lacity, M.C. (eds) Enacting Research Methods in Information Systems. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-29272-4_8

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