Abstract
The co-evolution of information systems (IS) and the processes that underpin the construction and development of IT systems are explained from a complex systems perspective. Evolution operates at the microscopic level; in organizations, this is the individual or agent. Each agent has an idiosyncratic view of the organization, using to some extent personal constructs in dealing with the reality of organizational life. These objects or constructs can be described and measured by most agents; they are well defined. Many of these objects are represented in electronic, IT systems. Each agent also has their own view as to how they know what they know, that is, their epistemology, which we argue is their IS, and is wider than the IT systems they use. The IS of each agent co-evolves, by interaction with other agents, based on the agent's view of reality. The interaction of all agents constitutes the organization. Even more importantly, different values and interests motivate each agent. This is their axiology and it is what motivates them to learn and to develop their IS. An agent-based axiological framework is essential to understanding the evolution of organizations. It is the interaction of agents that builds consensus as to the shared reality of the organization, and this affects each agent's ability and motivation to evolve IS further. In addition, we propose that it is time that IT systems included modelling capabilities, based on multi-agent representations of the organization and its context, to explore and support strategic thinking and decision making.
Similar content being viewed by others
References
Allen, P.M. (1976). Evolution, Population Dynamics and Stability, Proc Natl Acad Sci USA 73 (3): 665–668.
Allen, P.M. (2004). The Complexity of Structure, Strategy and Decision Making, in J. Foster and J.S. Metcalfe (eds.) Evolution and Economic Complexity, Cheltenham: Edward Elgar, pp. 85–107.
Allen, P.M. and McGlade, J.M. (1987). Evolutionary Drive: The effect of microscopic diversity, error making & noise, Foundation of Physics 17 (7): 723–728.
Allen, P.M. and Strathern, M. (2004). Evolution, Emergence and Learning in Complex Systems, Emergence 5 (4): 8–33.
Allen, P.M., Strathern, M. and Baldwin, J.S. (2006). Evolutionary Drive: New understanding of change in socio-economic systems, Emergence Complexity & Organization 8 (2): 2–19.
Allen, P.M. (1994). Coherence, Chaos and Evolution in the Social Context, Futures 26 (6): 583–597.
Allen, P.M. (2001a). A Complex Systems Approach to Learning, Adaptive Networks, International Journal of Innovation Management 5 (2): 149–180.
Allen, P.M. (2001b). What Is Complexity Science? Knowledge of the Limits to Knowledge, Emergence 3 (1): 24–42.
Argyris, C. and Schon, D.A. (1978). Organizational Learning: A Theory of Action Perspective, Reading, MA: Addison-Wesley.
Baldwin, J.S., Allen, P.M., Winder, B. and Ridgway, K. (2003). Simulating the Cladistic Evolution of Manufacturing, Journal of Innovation Management, Policy and Practice 5 (3): 144–156.
Bruderer, E. and Singh, J.V. (1996). Organization Evolution, Learning and Selection: A Genetic-Algorithm Based Model, Academy Management Journal 39 (5): 1322–1349.
Brynjolfsson, E. and Hitt, L. (1996). Paradox Lost? Firm-level evidence on the returns to information systems spending, Management Science 42 (4): 541–558.
Burgelman, R.A. (1983). Corporate Entrepreneurship and Strategic Management: Insights from a process study, Management Science 29 (12): 1349–1364.
Burrell, G. and Morgan, G. (1979). Sociological Paradigms and Organizational Analysis, Ashgate Publishing, Aldershot: UK.
Bygrave, W.D. (1989). The Entrepreneurship Paradigm (II): Chaos and catastrophes among quantum jumps, Entrepreneurship: Theory and Practice 14 (2): 7–30.
Capra, F. (1996). The Web of Life: A New Scientific Understanding of Living Systems, New York: Anchor Books.
Carley, K.M. (2002). Intra-Organizational Complexity and Computation, in J.A.C. Baum (ed.) The Blackwell Companion to Organizations, Oxford: Blackwell, pp. 208–232.
Casti, J.L. (1997). Would-Be Worlds: How Simulation Is Changing the Frontiers of Science, New York: John Wiley and Sons.
Cohen, M. (1999). Commentary on the Organizational Science Special Issue on Complexity, Organization Science 10 (3): 373–376.
Coveney, P. and Highfield, R. (1995). Frontiers of Complexity: The Search for Order in a Chaotic World, New York, NY: Fawcett Columbine.
Curd, M. and Cover, J.A. (1998). Philosophy of Science: The Central Issues, New York: Norton.
Daft, R.L. and Weick, K.E. (1984). Toward a Model of Organizations as Interpretation Systems, Academy of Management Review 9 (2): 284–295.
Datta, P., Christopher, M. and Allen, P.M. (2006). Proceedings of the EIASM Conference, Oxford: June.
Galbraith, J.R. (1977). Organizational Design, Reading, MA: Addison-Wesley.
Giaglis, G.M., Hlupic, V., de Vreede, G.-J. and Verbraeck, A. (2005). Synchronous Design of Business Processes and Information Systems Using Dynamic Process Modelling, Business Process Management Journal 11 (5): 488–500.
Greenwood, R. and Hinings, C.R. (1988). Organizational Design Types, Tracks and the Dynamics of Strategic Change, Organization Studies 9 (3): 293–316.
Hammerstein, P. (2001). Evolutionary Adaptation and the Economic Concept of Bounded Rationality – A dialogue, in G. Gigerenzer and R. Selten (eds.) Bounded Rationality: The Adaptive Toolbox, Cambridge, MA: The MIT Press, pp. 71–82.
Hannan, M.T. and Freeman, J. (1977). The Population Ecology of Organizations, American Journal of Sociology 82: 929–964.
Hinings, C.R., Thibault, L., Slack, T. and Kikulis, L.M. (1996). Values and Organizational Structure, Human Relations 49 (7): 885–916.
Holland, J. (1995). Hidden Order: How Adaptation Builds Complexity, Cambridge, MA: Perseus Books.
Holland, J. (1998). Emergence: From Chaos to Order, Cambridge, MA: Perseus Books.
Jantsch, E. (1975). Design for Evolution: Self-Organization and Planning in the Life of Human Systems, New York: Braziller.
Jantsch, E. (1983). The Self-Organizing Universe, 1st edn Oxford, UK: Pergamon Press.
Johnson, J.L. and Burton, B.K. (1994). Chaos and Complexity Theory for Management; Caveat Emptor, Journal of Management Inquiry 3 (4): 320–328.
Kauffman, S.A. (1995a). At Home in the Universe, Oxford: Oxford University Press.
Kauffman, S.A. (1995b). Escaping the Red Queen Effect, The McKinsey Quarterly 1: 119–129.
Kauffman, S.A. and Macready, W. (1995). Technological Evolution and Adaptive Organizations, Complexity 1 (2): 26–43.
King, S.F. and Burgess, T.F. (2006). Beyond Critical Success Factors: A dynamic model of enterprise system innovation, International Journal of Information Management 26: 59–69.
Lind, A. and Lind, B. (2005). Systems Research and Behaviour Science, Systems Research and Behavioural Science 22: 453–464.
Liu, K., Sun, L. and Bennett, K. (2002). Co-Design of Business and IT Systems – Introduction by Guest Editors, Information Systems Frontiers 4 (3): 251–256.
Lorenz, E.N. (1963). Deterministic Nonperiodic Flow, Journal of the Atmospheric Sciences 20 (1): 30–141.
March, J.G. (1991). Exploration and Exploitation in Organizational Learning, Organization Science 2 (1): 71–87.
McCarthy, I.P., Tsinopoulos, C., Allen, P.M. and Rose-Anderssen, C. (2006). New Product Development as a Complex Adaptive System of Decisions, Journal of Product Innovation Management 23: 437–456.
McKelvey, B. (1999). Toward a Campbellian Realist Organization Science, in J.A.C. Baum and B. McKelvey (eds.) Variations in Organization Science: In Honor of Donald T, Thousand Oaks: Campbell, Sage Publications Inc, pp. 383–411.
McKelvey, B. (2002). Model-Centred Organization Science Epistemology, in J.A.C. Baum (ed.) The Blackwell Companion to Organizations, Oxford: Blackwell, pp. 752–780.
Mihata, K. (1997). The Persistence of Emergence, in Eve, R.A., Horsfall, S. and Lee, M.E. (eds.) Chaos, Complexity and Sociology: Myths, Models & Theories, Thousand Oaks, CA: Sage Publications Inc, pp. 30–38.
Morel, B. and Ramanujam, R. (1999). Through the Looking Glass of Complexity: The dynamics of organizations as adaptive and evolving systems, Organization Science 10 (3): 278–293.
Morgan, G. (1997). Images of Organization, Thousand Oaks, CA: Sage Publications Inc.
Nonaka, L. (1988). Creating Organizational Order Out of Chaos: Self-renewal in Japanese firms, California Management Review 30 (3): 57–73.
Paul, D.L., Butler, J.C., Pearlson, K.E. and Whinston, A.B. (1996). Computationally Modeling Organizational Learning and Adaptability As Resource Allocation: An artificial adaptive systems approach, Computational and Mathematical Organization Theory 2 (4): 301–324.
Ranson, S., Hinings, B. and Greenwood, R. (1980). The Structuring of Organizational Structures, Administrative Science Quarterly 25 (1): 1–17.
Schein, E.H. (1992). Organizational Culture and Leadership, 2nd edn. San Francisco: Jossey-Bass Publications.
Senge, P.M. (1990). The Fifth Discipline: The Art and Practice of the Learning Organization, 1st edn. New York: Doubleday.
Simon, H.A. (2001). Complex Systems: The interplay of organizations and markets in contemporary society, Computational and Mathematical Organization Theory 7 (2): 79.
Singh, K. (1997). The Impact of Technological Complexity and Interfirm Cooperation on Business Survival, Academy of Management Journal 40 (2): 339–365.
Thompson, J.D. (1967). Organizations in Action: Social Science Bases of Administrative Theory, New York: McGraw-Hill.
Tushman, M.L. and Nadler, D.A. (1978). Information Processing as an Integrating Concept in Organizational Design, Academy of Management Review 3: 613–624.
Van Dyck, W. and Allen, P.M. (2006). Pharmaceutical Discovery as a Complex System of Decisions: Front Loaded Experimentation, Emergence: Complexity & Organization 8 (3): 40–56.
Van Valen, L. (1983). How Pervasive Is Coevolution? in M. Nitecki (ed.) Coevolution, Chicago, IL: University of Chicago Press.
Waldrop, M.M. (1992). Complexity: The Emerging Science at the Edge of Order and Chaos, New York, NY: Simon & Schuster.
Walsh, J.P. (1995). Managerial and Organizational Cognition: Notes from a trip down memory lane, Organization Science 6 (3): 280–321.
Walsh, J.P. and Ungson, G.R. (1991). Organizational Memory, Academy of Management Review 16 (1): 57–91.
Acknowledgements
This work was supported by ESRC Grant No.: RES-000-23-0845, ‘Modelling the Evolution of the Aerospace Supply Chain’. We thank the reviewers, and particularly the editors for their helpful comments and suggestions.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Allen, P., Varga, L. A co-evolutionary complex systems perspective on information systems. J Inf Technol 21, 229–238 (2006). https://doi.org/10.1057/palgrave.jit.2000075
Published:
Issue Date:
DOI: https://doi.org/10.1057/palgrave.jit.2000075