A Complex Adaptive Systems Model of Organization Change

  • Kevin J. Dooley


The study of complex adaptive systems has yielded great insight into how complex, organic-like structures can evolve order and purpose over time. Business organizations, typified by semi-autonomous organizational members interacting at many levels of cognition and action, can be portrayed by the generic constructs and driving mechanisms of complex adaptive systems theory. The purpose of this paper is to forge a unified description of complex adaptive systems from several sources, and then investigate the issue of change in a business organization via the framework of complex adaptive systems. The theory of complex adaptive systems uses components from three paradigms of management thought: systems theory, population ecology, and information processing. Specific propositions regarding the nature of dynamical change will be developed, driven by the complex adaptive systems model. Supporting evidence for these propositions is then sought within the existing management theory literature. In doing so, the complex adaptive systems approach to understanding organization change will be better grounded in domain-specific theory, and new insights and research areas will come to light.

organization development management agents schema organization learning 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Abraham, F., Abraham, R., & Shaw, C. (1990). A visual introduction to dynamical systems theory for psychology. Santa Cruz, CA: Aerial Press.Google Scholar
  2. Ackoff, R. L. (1988). The second industrial revolution (speech transcript).Google Scholar
  3. Ackoff, R. K., & Emery, F. E. (1972). On purposeful systems. Chicago: Aldine.Google Scholar
  4. Allen, P., & Sanglier, M. (1981). Urban evolution, self-organization, and decision-making. Environment and Planning A, 13, 167–183.Google Scholar
  5. Anderson, J., Rungtusanatham, M., & Schroeder, R. (1994). A theory of quality management underlying the Deming management method. Academy of Management Review, 19, 472–509.Google Scholar
  6. Anderson, P., & Tushman, M. L. (1990). Technological discontinuities and dominant designs: A cyclical model of technological change. Administrative Science Quarterly, 35, 604–633.Google Scholar
  7. Argyris, C., & Schon, D. (1978). Organizational learning: A theory of action perspective. Reading, MA: Addison-Wesley.Google Scholar
  8. Arthur, W. B. (1994). On the evolution of complexity. In G. A. Cowen, D. Pines, & D. Meltzer (Eds.), Complexity: Metaphors, models, and reality. SFI Studies in the Sciences of Complexity, Proc. (Vol. XIX, pp. 65–82). New York: Addison-Wesley.Google Scholar
  9. Ashby, W. R. (1958). An introduction to cybernetics. New York: John Wiley and Sons.Google Scholar
  10. Baum, J., & Singh, J. (1994). Evolutionary dynamics of organizations. New York: Oxford University Press.Google Scholar
  11. Beaumariage, T., & Kempf, K. (November 1994). The Nature and Origin of Chaos in Manufacturing. IEEE Advanced Semiconductor Manufacturing Conference, Boston.Google Scholar
  12. Bohm, D. (1957). Causality and chance in modern physics. Philadelphia: University of Pennsylvania Press.Google Scholar
  13. Boyd, R., & Richerson, P. (1985). Culture and the evolutionary process. Chicago: University of Chicago Press.Google Scholar
  14. Burke, W., & Litwin, G. (1992). A causal model of organization performance and change. Journal of Management, 18, 523–545.Google Scholar
  15. Burns, T., & Stalker, G. M. (1961). The management of innovation. London: Tavistock.Google Scholar
  16. Camp, R. C. (1989). Benchmarking. Milwaukee, WI: Quality Press.Google Scholar
  17. Capra, F. (1982). The turning point. Toronto: Bantam.Google Scholar
  18. Cartwright, T. J. (1991). Planning and chaos theory. Journal of American Planning Association, 57, 44–56.Google Scholar
  19. Cavalli-Sforza, L., & Feldman, M. (1981). Cultural transmission and evolution: A quantitative approach. Princeton, NJ: Princeton Press.Google Scholar
  20. Chase, C., Serrano, J., & Ramadge, P. (1993). Periodicity and chaos from switched flow systems: Contrasting examples of discretely controlled continuous systems. IEEE Transactions on Automatic Control, 38, 70–83.Google Scholar
  21. Cheng, Y-T., & Van de Ven, A. (1994). Learning the innovation journey: Order out of chaos? Technical Report, Strategic Management Center, University of Minnesota.Google Scholar
  22. Csanyi, V. (1989). Evolutionary systems and society: A general theory. Durham, NC: Duke University Press.Google Scholar
  23. Cyert, R. M., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  24. Davies, S. (1979). The diffusion of process innovation. Cambridge: Cambridge University Press.Google Scholar
  25. Dawkins, R. (1976). The selfish gene. New York: Oxford Press.Google Scholar
  26. de Bono, E. (1969). The mechanism of mind. New York: Penguin Books.Google Scholar
  27. Deshmukh, A. (1993). Complexity and Chaos in Manufacturing Systems. Doctoral dissertation, School of Industrial Engineering, Purdue University.Google Scholar
  28. DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147–160.Google Scholar
  29. Donaldson, G., & Lorsch, J. (1980). Decision making at the top. New York: Basic Books.Google Scholar
  30. Dooley, K. (in press). Chaotic dynamics and autonomous agents in manufacturing. Chaos Network.Google Scholar
  31. Dooley, K., Bush, D., Anderson, J., & Rungtusanatham, M. (1990). The U.S. Baldrige award and Japan's Deming prize: Two guidelines for total quality control. Engineering Management Journal, 2(3), 9–16.Google Scholar
  32. Dooley, K., Johnson, T., & Bush, D. (1995). TQM, chaos, and complexity. Human Systems Management, 14, 297–302.Google Scholar
  33. Dutton, J., & Dukerich, J. (1991). Keeping an eye on the mirror: Image and identity in organizational adaptation. Academy of Management Journal, 34, 517–554.Google Scholar
  34. Eoyang, G. (October 1993). Patterns: an algorithm for complex interactions. Paper presented to the Annual Conference of the Chaos Network, Minneapolis.Google Scholar
  35. Eoyang, G., & Dooley, K. (1996). Boardrooms of the future: The fractal nature of organizations. In C. Pickover (Ed.), Fractals in the future (pp. 195–203). New York: St. Martin's Press.Google Scholar
  36. Erramilli, A., & Forys, L. (1991). Oscillations and chaos in a flow model of a switching system. IEEE Journal on Selected Areas in Communications, 9, 171–178.Google Scholar
  37. Fiol, M., & Huff, A. (1992). Maps for managers: where are we? Where do we go from here? Journal of Management Studies, 29, 267–285.Google Scholar
  38. Fiol, M., & Lyles, M. (1985). Organization learning. Academy of Management Review, 10, 803–813.Google Scholar
  39. Forrester, J. W. (1961). Industrial dynamics. Cambridge, MA: Productivity Press.Google Scholar
  40. Gailbraith, J. R. (1974). Organization design: An information processing view. Interfaces, 4, 28–36.Google Scholar
  41. Garvin, D. A. (1991). How the Baldrige award really works. Harvard Business Review, November–December, 80–93.Google Scholar
  42. Gell-Mann, M. (1994). The quark and the jaguar. New York: Freeman & Co.Google Scholar
  43. George, C. (1968). The history of management thought. Englewood Cliffs: Prentice Hall.Google Scholar
  44. Gersick, C. (1988). Time and transition in work teams: Toward a new model of group development. Academy of Management Journal, 31(1), 9–41.Google Scholar
  45. Gioia, D., & Chittipeddi, K. (1991). Sensemaking and sensegiving in strategic management initiation. Strategic Management Journal, 12, 433–448.Google Scholar
  46. Gleick, J. (1987). Chaos: Making of a new science. New York: Viking.Google Scholar
  47. Goldstein, J. (1990). A nonequilibrium, nonlinear approach to organizational change. In D. Andersen, G. Richardson, & J. Sterman (Eds.), System dynamics '90 (pp. 425–439). Cambridge, MA: MIT.Google Scholar
  48. Goldstein, J. (1994). The unshackled organization. Portland, OR: Productivity Press.Google Scholar
  49. Gould, S. J. (1989). Punctuated equilibria in fact and theory. Journal of Social and Biological Structures, 12, 117–136.Google Scholar
  50. Gresov, C., Haveman, H., & Oliva, T. (1993). Organization design, inertia, and the dynamics of competitive response. Organization Science, 4(2), 181–208.Google Scholar
  51. Gribbin, J. (1984). In search of Schroedinger's cat: Quantum physics and reality. New York: Bantam Books.Google Scholar
  52. Guastello, S. (1995). Chaos, catastrophe, and human affairs. Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
  53. Guastello, S., Dooley, K., & Goldstein, J. (1995). Chaos, organizational theory, and organizational development. In A. Gilgen & F. Abraham (Eds.), Chaos theory in psychology (pp. 267–278). Westport, CT: Praeger.Google Scholar
  54. Hannan, M. T., & Freeman, F. (1989). Organizational ecology. Cambridge, MA: Harvard University Press.Google Scholar
  55. Hayles, N. K. (1991). Introduction: Complex dynamics in science and literature. In N. K. Hayles (Ed.), Chaos and order: Complex dynamics in literature and science (pp. 1–36). Chicago: University of Chicago Press.Google Scholar
  56. Heyerbrand, W. (1977). Organizational contradictions in public bureaucracies: Toward a Marxian theory of organizations. Sociological Quarterly, 18, 83–107.Google Scholar
  57. Hock, D. W. (1995). The chaordic organization. World Business Academy Perspectives, 9(1), 5–18.Google Scholar
  58. Holland, J. H. (1995). Hidden order. Reading, MA: Addison-Wesley.Google Scholar
  59. Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88–115.Google Scholar
  60. Huberman, B., & Hogg, T. (1988). The behavior of computational ecologies. In B. Huberman (Ed.), The ecology of computation (pp. 77–115). Amsterdam: North Holland Publishers.Google Scholar
  61. Jantsch, E. (1980). The self-organizing universe. Oxford: Pergamon Press.Google Scholar
  62. Jayanthi, S., & Sinha, K. K. (June 1994). A Chaotic Process of Innovation: The Case of High Technology Manufacturing. TECMAN Conference, Carnegie-Mellon University, Pittsburgh, PA.Google Scholar
  63. Jelinek, M., & Schoonhoven, C. (1990). The innovation marathon. Cambridge: Basil Blackwell.Google Scholar
  64. Kanter, R. M., Stein, B. A., & Jick, T. D. (1992). The challenge of organizational change: How companies experience it and leaders guide it. New York: Free Press.Google Scholar
  65. Karakatsios, K. Z. (1990). Casim's user's guide. Nicosia, CA: Algorithmic Arts.Google Scholar
  66. Kauffman, S. (1995). At home in the universe. Oxford: Oxford Press.Google Scholar
  67. Kellert, S. (1993). In the wake of chaos. Chicago: University of Chicago Press.Google Scholar
  68. Kelly, K. (1994). Out of control: The rise of the neo-biological society. Reading, MA: Addison-Wesley.Google Scholar
  69. Kiel, L. D. (1994). Managing chaos and complexity in government. San Francisco: Jossey-Bass.Google Scholar
  70. Kiesler, S., & Sproull, L. (1982). Management response to changing environments: Perspective on problem solving from social cognition. Administrative Science Quarterly, 27(4), 548–570.Google Scholar
  71. Kodama, F. (1995). Emerging patterns of innovation: Sources of Japan's technological edge. Boston: Harvard Business School Press.Google Scholar
  72. Koput, K. W. (1992). Dynamics of Innovative Idea Generation in Organizations. Unpublished doctoral dissertation, University of California, Berkeley.Google Scholar
  73. Kuhn, T. (1970). The structure of scientific revolutions. Chicago: University of Chicago Press.Google Scholar
  74. Lamprecht, J. L. (1992). ISO 9000. Milwaukee, WI: Quality Press.Google Scholar
  75. Lant, T., & Mezias, S. (1992). An organization learning model of convergence and reorientation. Organization Science, 3, 47–71.Google Scholar
  76. Lawrence, P., & Dwyer, D. (1983). Renewing American industry. New York: Free Press.Google Scholar
  77. Lawrence, P., & Lorsch, J. (1967). Organization and environment. Cambridge: Harvard University Press.Google Scholar
  78. Leifer, R. (1989). Understanding organizational transformation using a dissipative structure model. Human Relations, 42(10), 899–916.Google Scholar
  79. Leland, W., Taqqu, M., Willinger, W., & Wilson, D. (1993). On the self-similar nature of ethernet traffic. Sigcom, 93, 183–193.Google Scholar
  80. Leonard-Barton, D. (1988). Implementation as mutual adaptation of technology and organization. Research Policy, 17, 251–267.Google Scholar
  81. Levin, G., Hirsch, G., & Roberts, E. (1972). Narcotics and the community: A system simulation. American Journal of Public Health, 62(6), 861–873.Google Scholar
  82. Levitt, B., & March, J. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.Google Scholar
  83. Levy, D. (1994). Chaos theory and strategy: Theory, application, and managerial implications. Strategic Management Journal, 15, 167–178.Google Scholar
  84. Lewin, R. (1992). Complexity: Life at the edge of chaos. New York: MacMillan.Google Scholar
  85. Lin, G. Y., & Solberg, J. J. (1992). Integrated shop floor control using autonomous agents. IIE Transactions, 24, 57–71.Google Scholar
  86. Lumdsen, C., & Wilson, E. (1981). Genes, mind, and culture. Cambridge: Harvard University Press.Google Scholar
  87. Mandelbrot, B. (1983). The fractal geometry of nature. New York: W.H. Freeman.Google Scholar
  88. March, J. G., & Simon, H. A. (1958). Organizations. New York: John Wiley and Sons.Google Scholar
  89. Maturana, H., & Varela, F. (1992). The tree of knowledge. Boston: Shambhala.Google Scholar
  90. McKelvey, B. (1982). Organizational systematics: Taxonomy, classification, evolution. Berkeley, CA: University of California Press.Google Scholar
  91. McKelvey, B., & Aldrich, H. (1983). Populations, natural selection, and applied organization science. Administrative Science Quarterly, 28, 101–128.Google Scholar
  92. Miles, R., & Snow, C. (1978). Organizational strategy, structure, and process. New York: McGraw-Hill.Google Scholar
  93. Miller, D., & Friesen, P. H. (1978). Archetypes of strategy formulation. Management Science, 24, 921–933.Google Scholar
  94. Mintzberg, H. (1979). The structuring of organizations. Englewood Cliffs, NJ: Prentice-Hall.Google Scholar
  95. Mintzberg, H. (1994). The rise and fall of strategic planning. New York: Free Press.Google Scholar
  96. Morgan, G. (1986). Images of organizations. Newbury Park, CA: Sage.Google Scholar
  97. Nonaka, I. (1988). Creating organizational order out of chaos: Self-renewal in Japanese firms. California Management Review, 57–73.Google Scholar
  98. Palazzoli, M. S., Boscolo, L., Cecchin, G., & Prata, G. (1980). Hypothesizing-circularity-neutrality. Family Process, 19(1), 73–85.Google Scholar
  99. Peitgen, H.-O., Jurgens, H., & Saupe, D. (1992). Chaos and fractals: New frontiers of science. New York: Springer-Verlag.Google Scholar
  100. Peters, E. E. (1991). Chaos and order in the capital markets. New York: Wiley.Google Scholar
  101. Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations: A resource dependence perspective. New York: Harper and Row.Google Scholar
  102. Prahalad, C. K., & Hamel, G. (1990). The core competence of the organization. Harvard Business Review, May–June, 79–91.Google Scholar
  103. Priesmeyer, H. R. (1992). Organizations and chaos. Westport, CT: Quorum Books.Google Scholar
  104. Prigogine, I., & Stengers, I. (1984). Order out of chaos. New York: Bantam Books.Google Scholar
  105. Reger, R., Gustafson, L., Demarie, S., & Mullane, J. (1994). Reframing the organization: Why implementing total quality is easier said than done. Academy of Management Review, 19, 565–584.Google Scholar
  106. Roberts, E. (1963). The design of management control systems. Management Technology, 3(2), 100–108.Google Scholar
  107. Rosenkopf, L., & Tushman, M. (1994). The coevolution of technology and organization. In J. Baum and J. Singh (Eds.), Evolutionary dynamics of organizations (pp. 403–424). New York: Oxford University Press.Google Scholar
  108. Saraph, J., Benson, P., & Schroeder, R. (1989). An instrument for measuring the critical factors of quality management. Decision Sciences, 20, 810–829.Google Scholar
  109. Schein, E. (1992). Organizational culture and leadership. San Francisco: Jossey-Bass.Google Scholar
  110. Schon, D. (1975). Deutero-learning in organizations: Learning for increased effectiveness. Organizational Dynamics, 4(1), 2–16.Google Scholar
  111. Senge, P. (1990). The fifth discipline. New York: Doubleday.Google Scholar
  112. Simon, H. A. (1947). Administrative behavior. New York: MacMillan.Google Scholar
  113. Simon, H. A. (1952). On the application of servomechanism theory in the study of production control. Econometrica, 20(2), 247–268.Google Scholar
  114. Sitkin, S., Sutcliffe, K., & Schroeder, R. (1994). Distinguishing control from learning in total quality management: A contigency perspective. Academy of Management Review, 19(3), 537–564.Google Scholar
  115. Spencer, B. (1994). Models of organizational and total quality management: A comparison and critical evaluation. Academy of Management Review, 19, 446–471.Google Scholar
  116. Stacey, R. (1992). Managing the unknowable. San Francisco: Jossey-Bass.Google Scholar
  117. Stoneman, P. (1983). The economic analysis of technological change. Oxford: Oxford University Press.Google Scholar
  118. Thietart, R. A., & Forgues, B. (1995). Chaos theory and organization. Organization Science, 6, 19–31.Google Scholar
  119. Taylor, F. (1911). Principles of scientific management. New York: Harper & Bros.Google Scholar
  120. Tichy, N., & Ulrich, D. (1984). The leadership challenge—a call for transformational leader. Sloan Management Review, Fall, 59–63.Google Scholar
  121. Treacy, M., & Wiersema, F. (1995). The discipline of market leaders. Reading, MA: Addison-Wesley.Google Scholar
  122. Tushman, M. L., & Romanelli, E. (1985). Organizational evolution: A metamorphis model of convergence and reorientation. Research in Organizational Behavior, 7, 171–222.Google Scholar
  123. Tushman, M. L., Newman, W., & Romanelli, E. (1986). Convergence and upheaval: Managing the unsteady pace of organizational evolution. California Management Review, 29(1), 29–44.Google Scholar
  124. Tyre, M., & Orlikowski, W. (1994). Windows of opportunity: Temporal patterns of technological adaptation. Organization Science, 5, 98–118.Google Scholar
  125. Van de Ven, A., & Garud, R. (1994). The coevolution of technical and institutional events in the development of an innovation. In J. Baum and J. Singh (Eds.), Evolutionary dynamics of organizations (pp. 425–443). New York: Oxford University Press.Google Scholar
  126. Van de Ven, A. H., & Poole, M. S. (1995). Explaining development and change in organizations. Academy of Management Review, 20, 510–540.Google Scholar
  127. Virany, B., Tushman, T. L., & Romanelli, E. (1992). Executive succession and organization outcomes in turbulent environments: An organization learning approach. Organization Science, 3, 72–92.Google Scholar
  128. von Bertalanffy, L. (1968). General systems theory. New York: Braziller.Google Scholar
  129. Waldrop, M. M. (1992). Complexity: The emerging science at the edge of chaos. New York: Simon and Schuster.Google Scholar
  130. Weick, K. (1979). The social psychology of organization. New York: Random House.Google Scholar
  131. Wheatley, M. (1992). Leadership and the new science. San Francisco: Berrett-Koehler.Google Scholar
  132. Wiener, N. (1948). Cybernetics. New York: Wiley.Google Scholar
  133. Wiggins, E. T. (1987). Self-discrepancy: A theory relating self and affect. Psychological Review, 94, 319–340.Google Scholar
  134. Zimmerman, B. (1993). The inherent drive towards chaos. In P. Lorange, B. Chakravarthy, J. Roos, and A. Van de Ven (Eds.), Implementing strategic processes: Change, learning, and cooperation (pp. 373–393). Oxford: Basil Blackwell.Google Scholar

Copyright information

© Human Sciences Press, Inc. 1997

Authors and Affiliations

  • Kevin J. Dooley
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of MinnesotaMinneapolis

Personalised recommendations