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Complexity

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Complex System Governance

Abstract

Complexity is an essential and fundamental concept in complex systems. The most rudimentary perspective of complexity suggests a large number of entities/variables in rich interaction, not totally “knowable,” subject to emergence, and dynamically changing over time. However, for complex system governance (CSG), complexity has much more profound ramifications than the rudimentary perspective. Thus, the purpose of this chapter is to explore in-depth the nature, role, and implications of complexity for CSG. Three central themes of complexity are explored. First, the many different variations of complexity are synthesized into a set of cogent themes to provide a grounded perspective to inform CSG. Second, the role that complexity holds for the emerging CSG field is explored. Additionally, insights into the themes are provided in relation to CSG. Third, a set of implications of complexity for the design, deployment, and development aspects of CSG are examined. These implications are examined considering both field development as well as practice for CSG. The chapter closes with complexity-related challenges for CSG field development along with theoretical, methodological, and practice implications.

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References

  1. Ackoff R (1974) Redesigning the Future. Wiley, New York

    Google Scholar 

  2. Adami C (1998) Introduction to artificial life. Springer Science & Business Media

    Google Scholar 

  3. Addis L (1975) The logic of society: a philosophical study, vol 7. U of Minnesota Press

    Google Scholar 

  4. Allen P, McGlade J (1987) Modelling complex human systems: a fisheries example. Eur J Oper Res 30(2):147–167

    Google Scholar 

  5. Anderson PW (1972) More is different. Science 177(4047):393–396

    Google Scholar 

  6. Anzola D, Barbrook-Johnson P, Cano JI (2017) Self-organization and social science. Comput Math Organ Theory 23(2):221–257

    Article  Google Scholar 

  7. Ashby W (1947) Principles of the self-organizing dynamic system. J Gen Psychol 37:25–128

    Article  Google Scholar 

  8. Ashby WR (1947) The nervous system as physical machine: with special reference to the origin of adaptive behavior. Mind 56 (221) (January):44–59. http://tinyurl.com/aqcmdy

  9. Ashby WR (1960) Design for a brain: the origin of adaptive behaviour, 2nd ed. Chapman & Hall, London. https://doi.org/10.1037/11592-000

  10. Axelrod R (1984) The evolution of cooperation. Basic Books, New York

    MATH  Google Scholar 

  11. Batterman RW (2009) On the explanatory role of mathematics in empirical science. Br J Philos Sci 61(1):1–25

    Google Scholar 

  12. Beer S (1979) Heart of enterprise. Wiley

    Google Scholar 

  13. Beer S (1981) Brain of the Firm. Wiley

    Google Scholar 

  14. Beer S (1985) Diagnosing the system for organizations. Oxford University Press

    Google Scholar 

  15. Bertelsen S (2002) Bridging the gap–towards a comprehensive understanding of lean construction. In: IGLC-10, Gramado, Brazil

    Google Scholar 

  16. Boisot M, McKelvey B (2010) Integrating modernist and postmodernist perspectives on organizations: a complexity science bridge. Acad Manag Rev 35(3):415–433

    Google Scholar 

  17. Boisot M, McKelvey B (2011) Complexity and organisation—environment relations: revisiting Ashby’s law of requisite variety. In: Allen P, Maguire S, McKelvey B (eds) The SAGE book of complexity and management. London, pp 279–298

    Google Scholar 

  18. Bousquet A, Curtis S (2011) Beyond models and metaphors: complexity theory, systems thinking and international relations. Camb Rev Int Aff 24(1):43–62

    Google Scholar 

  19. Carley KM, Hill V (2001) Structural change and learning within organizations. In: Lomi A, Larsen ER (eds) Dynamics of organizational societies: computational modelling and organization theories. Cambridge, MA: MIT Press, pp 63–92

    Google Scholar 

  20. Crutchfield JP, Young K (1993) Computation at the edge of chaos. In: Complexity, entropy and the physics of information: SFI studies in the sciences of complexity, pp 223–269

    Google Scholar 

  21. Crutchfield JP, Young K (1994) What lies between order and chaos. In: The sciences. New York Academy of Sciences

    Google Scholar 

  22. Deutsch KW (1963) The nerves of government: models of political communication and control. The Free Press, New York

    Google Scholar 

  23. Eigen M, Schuster P (1977) A principle of natural self-organization. Naturwissenschaften 64(11):541–565

    Google Scholar 

  24. Eigen S, Schuster P (1979) The hypercycle [electronic resource] a principle of natural self-organization

    Google Scholar 

  25. Epstein JM, Axtell R (1996) Growing artificial societies: social science from the bottom up. MIT Press, Cambridge, MA

    Book  Google Scholar 

  26. Fernández N, Gershenson C (2013) Measuring complexity in an aquatic ecosystem. arXiv preprint arXiv:1305.5413

    Google Scholar 

  27. Fernández A, Gómez C, Hornero R, López-Ibor JJ (2013) Complexity and schizophrenia. Prog Neuro-Psychopharmacol Biol Psychiatry 45:267–276

    Google Scholar 

  28. Gershenson C (2013) The implications of interactions for science and philosophy. Foundations of Science Early View. http://arxiv.org/abs/1105.2827

  29. Gershenson C (2014) Harnessing the complexity of education with information technology. arXiv preprint arXiv:1402.2827

    Google Scholar 

  30. Gershenson C (2015) Requisite variety, autopoiesis, and self-organization. Kybernetes

    Google Scholar 

  31. Gilbert N (2008) Agent-based models. Sage, London

    Book  Google Scholar 

  32. Gilbert N, Anzola D, Johnson P, Elsenbroich C, Balke T, Dilaver O (2015) Self-organizing dynamical systems. In: Wright JD (ed) International encyclopedia of the social & behavioral sciences. Elsevier, London

    Google Scholar 

  33. Goldstein J (1999) Emergence as a construct: History and issues. Emergence 1(1):49–72

    Article  Google Scholar 

  34. Griffeath D, Moore C (eds) (2003) New constructions in cellular automata. Oxford University Press on Demand

    Google Scholar 

  35. Guastello SJ (2002) Managing emergent phenomena: nonlinear dynamics in work organizations. Lawrence Erlbaum Associates

    Google Scholar 

  36. Haken W (1973) Connections between topological and group theoretical decision problems. In: Studies in logic and the foundations of mathematics, vol 71. Elsevier, pp 427–441

    Google Scholar 

  37. Haken H (1981) Chaos and order in nature. In: Chaos and order in nature. Springer, Berlin, Heidelberg, pp 2–11

    Google Scholar 

  38. Haken H (2008) Self-organization of brain function. Scholarpedia 3:2555. https://doi.org/10.4249/Scholarpedia.2555

  39. Harrison JR, Carroll GR (1991) Keeping the faith: a model of cultural transmission in formal organizations. Adm Sci Q 36(4):552–582. https://doi.org/10.2307/2393274

  40. Hayek FA (1967) The theory of complex phenomena. In: Hayek FA (ed) Studies in philosophy, politics and economics. Routledge, London

    Google Scholar 

  41. Hayek FA (1978) The pretence of knowledge. In: Hayek FA (ed) New studies in philosophy, politics, economics and the history of ideas. Routledge, London

    Google Scholar 

  42. Holland JH (1988) The global economy as an adaptive system. In: Anderson PW, Arrow KJ, Pines D (eds) The economy as an evolving complex system. Addison-Wesley, Reading, MA, pp 117–124

    Google Scholar 

  43. Holland JH (1994) Echoing emergence: objectives, rough definitions, and speculations for ECHO-class models. In: Cowan GA, Pines D, Meltzer D (eds) Complexity: metaphors, models, and reality. Addison-Wesley

    Google Scholar 

  44. Homer-Dixon T (2015) Synchronous Failure. Ecol Soc 20(3)

    Google Scholar 

  45. Ireland V, Gorod A (2016) Contribution of complex systems to entrepreneurship. Entrep Res J 6(1):1–41

    Article  Google Scholar 

  46. Jervis R (1997) System Effects. Princeton University Press. Kaski, T, Princeton

    Google Scholar 

  47. Johnson S (2002) Emergence: the connected lives of ants, brains, cities, and software. Simon and Schuster

    Google Scholar 

  48. Katina PF (2015) Emerging systems theory–based pathologies for governance of complex systems. Int J Syst Syst Eng 6(1–2):144–159

    Google Scholar 

  49. Katina PF (2016) Systems theory as a foundation for discovery of pathologies for complex system problem formulation. In: Applications of systems thinking and soft operations research in managing complexity. Springer, Cham, pp 227–267

    Google Scholar 

  50. Kauffman S (1995) At home at the universe. Oxford University Press, Oxford

    Google Scholar 

  51. Keating CB, Katina PF, Bradley JM (2015) Challenges for developing complex system governance. Paper presented at the Proceedings of the 2015 industrial and systems engineering research conference

    Google Scholar 

  52. Keating CB, Katina PF (2019) Complex system governance: concept, utility, and challenges. Syst Res Behav Sci 36(5):687–705

    Article  Google Scholar 

  53. Keating CB, Morin M (2001) An approach for systems analysis of patient care operations. J Nurs Adm 31(7/8):355–363. https://doi.org/10.1097/00005110-200107000-00007

    Article  Google Scholar 

  54. Koskinen KU (2013) Processual autopoietic knowledge production in organizations. In: Knowledge production in organization. Springer, Heidelberg, pp 1–5

    Google Scholar 

  55. Langton CG (1986) Studying artificial life with cellular automata. Physica D: Nonlinear Phenom 22(1–3):120–149

    Google Scholar 

  56. Langton CG (1996) SFI studies in the sciences of complexity, vol XVII. Addison-Wesley

    Google Scholar 

  57. Laughlin RB (2005) A different universe: reinventing physics from the bottom down. Basic Books (AZ)

    Google Scholar 

  58. LeBaron B (2000) Empirical regularities from interacting long- and short-memory investors in an agent-based stock market. IEEE Trans Evol Comput 5(5):442–455. https://doi.org/10.1109/4235.956709

  59. Lewes GH (1875) On actors and the art of acting, vol 1533. B. Tauchnitz

    Google Scholar 

  60. Marinaro M, Tagliaferri R (2002) Neural nets. Springer-Verlag

    Google Scholar 

  61. Martelli M (1999) Introduction to discrete dynamical systems and chaos. Wiley

    Google Scholar 

  62. Maturana V, Varela FJ (1980) Autopoiesis and cognition the realization of the living. In: Boston studies in the philosophy of science, vol 42. D. Reidel Pub, Dordrecht, Holland; Boston

    Google Scholar 

  63. Maturana HR, Varela FJ (2012) Autopoiesis and cognition: the realization of the living, vol 42. Springer Science & Business Media

    Google Scholar 

  64. May RM, Oster GF (1976) Bifurcations and dynamic complexity in simple ecological models. Am Nat 110(974):573–599

    Google Scholar 

  65. McShea DW (2000) Functional complexity in organisms: parts as proxies. Biol Philos 15(5):641–668

    Google Scholar 

  66. Merali Y, Allen P (2011) Complexity and systems thinking. In: The SAGE handbook of complexity and management, 31–52

    Google Scholar 

  67. Miller J, Page S (2007) Complex adaptive systems. Princeton University Press, New Jersey

    MATH  Google Scholar 

  68. Morin E (2007) Introduction to complex thinking. Barcelona: Gedisa: Barcelona. PMI (Project Management Institute). (2014). Navigating complexity: a practice guide. pp. 1–113

    Google Scholar 

  69. Moroni S (2015) Complexity and the inherent limits of explanation and prediction: urban codes for self-organising cities. Plan Theory 14(3):248–267

    Article  Google Scholar 

  70. Nicolis P, Prigogine I (1989) Exploring complexity: an introduction. W.H. Freeman, New York

    Google Scholar 

  71. Orsini A, Le Prestre P, Haas PM, Brosig M, Pattberg P, Widerberg O, Gomez-Mera L, Morin J-F, Harrison NE, Geyer R, Chandler D (2019) Forum: complex systems and international governance. Int Stud Rev, 1–31

    Google Scholar 

  72. Prigogine I, Stengers I (1984) Order out of chaos: man’s new dialogue with nature. Boulder, CO: New Science Library

    Google Scholar 

  73. Prigogine I, Stengers I (2018) Order out of chaos: man’s new dialogue with nature. Verso Books

    Google Scholar 

  74. Prokopenko M, Boschetti F, Ryan AJ (2009) An information-theoretic primer on complexity, self-organization, and emergence. Complexity 15(1):11–28

    Article  ADS  MathSciNet  Google Scholar 

  75. Reid G (2007) The foundations of small business enterprise. Taylor and Francis

    Google Scholar 

  76. Rotmans J, Loorbach D (2009) Complexity and transition management. J Ind Ecol 13(2):184–196

    Article  Google Scholar 

  77. Sawyer RK (2005) Social emergence: societies as complex systems. Cambridge University Press, Cambridge, UK

    Book  Google Scholar 

  78. Skar J (2003) Introduction: self-organization as an actual theme. Philos Trans Ser A Math Phys Eng Sci 361(1807):1049–1056

    Google Scholar 

  79. Schelling T (1971) Dynamic models of segregation. J Math Sociol 1(2):143–186

    Article  Google Scholar 

  80. Simon H (1962) The architecture of complexity. Proc Am Philos Soc 106(6):467–482

    Google Scholar 

  81. Simon H (1981) The Sciences of the Artificial, 2nd edn. MIT Press, Cambridge

    Google Scholar 

  82. Solé R, Goodwin B (2000) How complexity pervades biology. Basic Books

    Google Scholar 

  83. Stewart I, Cohen J (1994) Why are there simple rules in a complicated universe? Futures 26(6):648–664

    Google Scholar 

  84. Teisman G, Gerrits L (2014) The emergence of complexity in the art and science of governance. Complex, Gov Netw 1(1):17–28

    Google Scholar 

  85. Varela F, Maturana H (1972) Mechanism and biological explanation. Philos Sci 39(3):378–382

    Google Scholar 

  86. Varela FG, Maturana HR, Uribe R (1974) Autopoiesis: the organization of living systems, its characterization and a model. Biosystems 5(4):187–196. https://doi.org/10.1016/0303-2647(74)90031-8

    Article  Google Scholar 

  87. Urry J (2003) Global complexity. Blackwell, London

    Google Scholar 

  88. Weaver W (1948) Science and Complexity. Am Sci 36:536

    Google Scholar 

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Correspondence to Charles W. Chesterman Jr. .

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Chesterman, C.W., Keating, C.B., Ireland, V. (2022). Complexity. In: Keating, C.B., Katina, P.F., Chesterman Jr., C.W., Pyne, J.C. (eds) Complex System Governance. Topics in Safety, Risk, Reliability and Quality, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-030-93852-9_2

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  • DOI: https://doi.org/10.1007/978-3-030-93852-9_2

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