Complexity theory and organizations

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This article is about the application of complexity science to strategy. For its application to the problems of economics, see Complexity economics. For other uses, see Complexity theory (disambiguation).

Complexity theory and organizations, also called complexity strategy or complex adaptive organization, is the use of complexity theory in the field of strategic management and organizational studies.

Overview[edit]

Complexity theory has been used in the fields of strategic management and organizational studies. Application areas include understanding how organizations or firms adapt to their environments and how they cope with conditions of uncertainty. The theory treats organizations and firms as collections of strategies and structures. The structure is complex; in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive; in that the individual and collective behavior mutate and self-organize corresponding to a change-initiating micro-event or collection of events.[1][2]

Organizations can be treated as complex adaptive systems (CAS) as they exhibit fundamental CAS principles like self-organisation, complexity, emergence,[3] interdependence, space of possibilities, co-evolution, chaos, and self-similarity.[1][4] A typical example for an organisation behaving as CAS, is the wikipedia[5] - collaborated and managed by a loosely organised management structure,[5] composed of a complex mix of human–computer interactions.[6][7][8] By managing behaviour, and not only mere content, Wikipedia uses simple rules to produce a complex, evolving knowledge base which has largely replaced older sources in popular use. Other examples include - the complex global macroeconomic network within a country or group of countries; stock market and complex web of cross border holding companies; manufacturing businesses; and any human social group-based endeavour in a particular ideology and social system such as political parties, communities, geopolitical organisations, and terrorist networks of both hierarchical and leaderless nature.[9] This new macro level state may create difficulty for an observer in explaining and describing the collective behaviour in terms of its constituent parts; as a result of the complex dynamic networks of interactions, outlined earlier.[1]

CAS are contrasted with ordered and chaotic systems by the relationship that exists between the system and the agents which act within it. In an ordered system the level of constraint means that all agent behaviour is limited to the rules of the system. In a chaotic system the agents are unconstrained and susceptible to statistical and other analysis. In a CAS, the system and the agents co-evolve; the system lightly constrains agent behaviour, but the agents modify the system by their interaction with it. This self-organizing nature is an important characteristic of CAS; and its ability to learn to adapt, differentiate it from other self organizing systems.[1]

CAS approaches to strategy seek to understand the nature of system constraints and agent interaction and generally takes an evolutionary or naturalistic approach to strategy. More recently work by organizational scholars and their colleagues have added greatly to our understanding of how concepts from the complexity sciences can be used to understand strategy and organizations. Much of this later research integrates computer simulation and organizational studies.

See also[edit]

References[edit]

  1. ^ a b c d "Insights from Complexity Theory: Understanding Organisations better". by Assoc. Prof. Amit Gupta, Student contributor - S. Anish , IIM Bangalore. Retrieved 1 June 2012. 
  2. ^ "Ten Principles of Complexity & Enabling Infrastructures". by Professor Eve Mitleton-Kelly, Director Complexity Research Programme, London School of Economics. Retrieved 1 June 2012. 
  3. ^ "Complex Adaptive Systems as a Model for Evaluating Organisational : Change Caused by the Introduction of Health Information Systems". Kieren Diment, Ping Yu, Karin Garrety, Health Informatics Research Lab, Faculty of Informatics, University of Wollongong, School of Management, University of Wollongong, NSW. uow.edu.au. Retrieved 25 August 2012. 
  4. ^ "Page 3, Similar fundamental between CAS and organisations, from paper "Ten Principles of Complexity & Enabling Infrastructures"". by Professor Eve Mitleton-Kelly, Director Complexity Research Programme, London School of Economics. Retrieved 1 June 2012. 
  5. ^ a b "A Complex Adaptive Organization Under the Lens of the LIFE Model:The Case of Wikipedia". Retrieved 25 August 2012. 
  6. ^ "The Internet Analyzed as a Complex Adaptive System". Retrieved 25 August 2012. 
  7. ^ "Cyberspace: The Ultimate Complex Adaptive System". The International C2 Journal. Retrieved 25 August 2012.  by Paul W. Phister Jr
  8. ^ "Complex Adaptive Systems". mit.edu. 2001. Retrieved 25 August 2012.  by Serena Chan, Research Seminar in Engineering Systems
  9. ^ "Toward a Complex Adaptive Intelligence Community The Wiki and the Blog". D. Calvin Andrus. cia.gov. Retrieved 25 August 2012. 

Further reading[edit]

  • Anderson, P. 1999. Complexity Theory and Organization Science Organization Science. 10(3): 216–232.
  • Axelrod, R. A., & Cohen, M. D., 2000. Harnessing Complexity: Organizational Implications of a Scientific Frontier. New York: The Free Press
  • Yaneer Bar-Yam (2005). Making Things Work: Solving Complex Problems in a Complex World. Cambridge, MA: Knowledge Press
  • Beautement, P. & Broenner, C. 2010. Complexity Demystified: A Guide for Practitioners. Axminster: Triarchy Press
  • Brown, S. L., & Eisenhardt, K. M. 1997. The Art of Continuous Change: Linking Complexity Theory and Time-paced Evolution in Relentlessly Shifting Organizations. Administrative Science Quarterly, 42: 1–34
  • Burns, S., & Stalker, G. M. 1961. The Management of Innovation. London: Tavistock Publications
  • Davis, J. P., Eisenhardt, K. M., & Bingham, C. B. 2009. Optimal Structure, Market Dynamism, and the Strategy of Simple Rules. Administrative Science Quarterly, 54: 413–452
  • De Toni, A.F., Comello, L., 2010. Journey into Complexity. Udine: Lulu Publisher
  • Gell-Mann, M. 1994. The Quark and the Jaguar: Adventures in the Simple and the Complex. New York: WH Freeman
  • Kauffman, S. 1993. The Origins of Order. New York, NY: Oxford University Press.
  • Levinthal, D. 1997. Adaptation on Rugged Landscapes. Management Science, 43: 934–950
  • March, J. G. 1991. Exploration and Exploitation in Organizational Learning. Organization Science, 2(1): 71–87
  • McKelvey, B. 1999. Avoiding Complexity Catastrophe in Coevolutionary Pockets: Strategies for Rugged Landscapes. Organization Science, 10(3): 249–321
  • McMillan, E. 2004 Complexity, Organizations and Change. Routledge.ISBN 041531447X Hardback. ISBN 0-415-39502-X Paperback
  • Moffat, James. 2003. Complexity Theory and Network Centric Warfare.
  • Perrow, C. Complex Organizations: A Critical Essay Scott, Forseman & Co., Glenville, Illinois
  • Rivkin, J., W. 2000. Imitation of Complex Strategies. Management Science, 46(6): 824–844
  • Rivkin, J. and Siggelkow, N. 2003. Balancing Search and Stability: Interdependencies Among Elements of Organizational Design. Management Science, 49, pp. 290–311
  • Rudolph, J., & Repenning, N. 2002. Disaster Dynamics: Understanding the Role of Quantity in Organizational Collapse. Administrative Science Quarterly, 47: 1–30
  • Schilling, M. A. 2000. Toward a General Modular Systems Theory and its Applicability to Interfirm Product Modularity. Academy of Management Review, 25(2): 312–334
  • Siggelkow, S. 2002. Evolution toward Fit. Administrative Science Quarterly, 47, pp. 125–159
  • Simon, H. 1996 (1969; 1981) The Sciences of the Artificial (3rd Edition) MIT Press
  • Smith, Edward. 2006. Complexity, Networking, and Effects Based Approaches to Operations] by Edward
  • Snowden, D.J. Boone, M. 2007. "A Leader's Framework for Decision Making". Harvard Business Review, November 2007, pp. 69–76.
  • Weick, K. E. 1976. Educational Organizations as loosely coupled systems. Administrative Science Quarterly, 21(1): 1–19

External links[edit]