Applications of Complex Systems in Socio-Economic Inequality Research: A Preliminary Survey

  • Czesław MesjaszEmail author
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


The ideas drawn from broadly defined systems thinking, including complex systems studies, have already been used to describe and explain socio-economic inequality, both directly and indirectly. Most of these works are good examples of applications of middle-range theories of socio-economic inequality, but many issues still need to be studied. The aim of this paper is to survey the different applications of complexity studies in the extant research on socio-economic inequality. Although inequality is a common phenomenon worldwide, attention in this paper is paid to the developed world, where poverty is not such a significant issue and where the ‘information revolution’ has had a greater impact.


Complexity Socio-economic inequality Middle-range theories 


  1. 1.
    Andriani, P., McKelvey, B.: From Gaussian to Paretian thinking: causes and implications of power-laws in organizations. Organ. Sci. 20(6), 1053–1071 (2009)CrossRefGoogle Scholar
  2. 2.
    Ashby, W.R.: An Introduction to Cybernetics. Wiley, New York (1963)zbMATHGoogle Scholar
  3. 3.
    Barabási, A.-L.: Linked. How Everything is Connected to Everything else and What it Means for Business, Science, and Everyday Life. Penguin, New York (2003)Google Scholar
  4. 4.
    Barabási, A.-L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)ADSMathSciNetCrossRefGoogle Scholar
  5. 5.
    Bar-Yam, Y.: Dynamics of complex systems. Addison-Wesley, Reading (1997)zbMATHGoogle Scholar
  6. 6.
    von Bertalanffy, L.: General Systems Theory. Braziller, New York (1968)Google Scholar
  7. 7.
    Biggiero, L.: Sources of complexity. Hum. Syst. Nonlinear Dyn. Psychol. Life Sci. 5(1), 3–19 (2001)CrossRefGoogle Scholar
  8. 8.
    Broido A.D., Clauset, A.: Scale-free networks are rare. Accessed 16 Apr 2018
  9. 9.
    Brzeziński, M.: Do wealth distributions follow Power-Laws? Evidence from ‘rich lists’. Accessed 14 Jan 2017
  10. 10.
    Buchanan, M.: Nexus: Small Worlds and the Groundbreaking Science of Networks. W.W. Norton & Company, New York (2002)Google Scholar
  11. 11.
    Carter, P.L., Reardon, S.F.: Inequality matters. A William T. Grant Foundation Inequality Paper, Stanford University, Accessed 21 Jan 2017
  12. 12.
    Castellani, B.: Brian Castellani on the complexity sciences. Accessed 20 Feb 2018
  13. 13.
    Castells, M.: The Information Age: Economy, Society and Culture: End of Millennium. Blackwell, Malden (1998)Google Scholar
  14. 14.
    Chatterjee, A., Ghosh, A., Inoue, J.-C., Chakrabarti, B.K.: Social inequality: from data to statistical physics modeling. J. Phys: Conf. Ser. 638, 1–9 (2015)Google Scholar
  15. 15.
    Checkland, P.: Soft systems methodology: a thirty year retrospective. Syst. Res. Behav. Sci. 17, 11–58 (2000)CrossRefGoogle Scholar
  16. 16.
    Ciliers, P.: Complexity and Postmodernism. Routledge, London (1998)Google Scholar
  17. 17.
    Clauset, A., Shalizi, C.R., Newman, M.E.J.: Power-law distributions in empirical data. SIAM Rev. 51(4), 661–703 (2009)ADSMathSciNetCrossRefGoogle Scholar
  18. 18.
    Economist: Measuring inequality. A three-headed hydra. Accessed 02 Nov 2017
  19. 19.
    von Foerster, H.: Observing systems. A Collection of papers by Heinz von Foerster. Intersystems Publications, Seaside, CA (1982)Google Scholar
  20. 20.
    Gell-Mann, M.: What is complexity? Complexity 1(1), 16–19 (1995)ADSMathSciNetCrossRefGoogle Scholar
  21. 21.
    von Glasersfeld, E.: Radical Constructivism: A New Way of Knowing and Learning. The Farmer Press, London (1995)Google Scholar
  22. 22.
    Holland, J.D.: Hidden Order. How Adaptation Builds Complexity. Basic Books, New York (1995)Google Scholar
  23. 23.
    Kauffman, S.A.: At home in the Universe. The search for laws of self-organization and complexity. Oxford University Press, New York/Oxford (1995)Google Scholar
  24. 24.
    Koestler, A.: The Ghost in the Machine. Penguin Group, London (1967)Google Scholar
  25. 25.
    Krauss, A.: The scientific limits of understanding the (potential) relationship between complex social phenomena: the case of democracy and inequality. J. Econ. Methodol. (2015). Scholar
  26. 26.
    Lakoff, G., Johnson, M.: Metaphors We Live By. University of Chicago Press, Chicago (1980/1995)Google Scholar
  27. 27.
    Lissack, M.R.: Complexity: The science, its vocabulary, and its relation to organizations. Emergence 1(1), 110–126 (1999)CrossRefGoogle Scholar
  28. 28.
    Lloyd, S.: Measures of complexity: a nonexhaustive List. IEEE Control Syst. Mag. 21(4), 7–8 (2001)CrossRefGoogle Scholar
  29. 29.
    Luhmann, N.: Social Systems. Stanford University Press, Palo Alto (1995)Google Scholar
  30. 30.
    Mantzavinos, C.: ‘Hermeneutics’. In: Zalta, E.N. (ed.) The Stanford Encyclopedia of Philosophy, Winter edn. Accessed 27 Dec 2016
  31. 31.
    McKay, A.: Defining and measuring inequality. Overseas Development Institute and University of Nottingham, Briefing Paper, 1, Accessed 13 Jan 2017
  32. 32.
    Mesjasz, C.: Complexity of social systems. Acta Phys. Polonica A 117(4), 706–715. Accessed 17 Apr 2018
  33. 33.
    Milanovic, B.: Global Inequality. A New Approach for the Age of Globalization. The Belknap Press of Harvard University Press, Cambridge, MA (2016)Google Scholar
  34. 34.
    Newman, M.E.J.: Power-Laws, Pareto distributions and Zipf’s law. Accessed 14 Mar 2015
  35. 35.
    Persky, J.: Retrospectives: Pareto’s Law. J. Econ. Perspect. 6(2), 181–192 (1992)CrossRefGoogle Scholar
  36. 36.
    Piketty, T.: Capital in the Twenty-First Century. Harvard University Press, Cambridge (2014)CrossRefGoogle Scholar
  37. 37.
    Prigogine, I., Stengers, I.: Order out of Chaos. Bantam, New York (1984)Google Scholar
  38. 38.
    Searle, J.R.: The Construction of Social Reality. The Free Press, New York (1995)Google Scholar
  39. 39.
    Sen, A.K.: Inequality Re-Examined. Oxford University Press, Oxford (1995)CrossRefGoogle Scholar
  40. 40.
    Simon, H.A.: The architecture of complexity. Proc. Am. Philos. Soc. 106(6), 467–482 (1962)Google Scholar
  41. 41.
    Simon, H.A.: Near decomponsability and complexity: How a mind resides in a brain. In: Morowitz, J.H., Singer, J.L. (eds.) The mind, the brain and complex adaptive systems (Santa Fe Institute Series) 25-43. Addisson-Wesley, Reading, MA (1995)Google Scholar
  42. 42.
    Stiglitz, J.: The Great Divide. Unequal Societies and What We Can Do About Them. W. W. Norton & Company, New York (2015)Google Scholar
  43. 43.
    Turchin, P., Gavrilets, S.: Evolution of complex hierarchical societies. Social Evolution & History (8)2, Accessed 26 Jan 2017
  44. 44.
    Waldrop, M.M.: Complexity: The Emerging Science at the Edge of Order and Chaos. Simon & Schuster, New York (1992)Google Scholar
  45. 45.
    Weaver, W.: Science and complexity. Am. Sci. 36(4), 536–544 (1948)Google Scholar
  46. 46.
    Wiener, N.: Cybernetics: Or Control and Communication in the Animal and the Machine. Hermann & Cie, Paris/MIT Press, Cambridge, MA (1948/1961)Google Scholar
  47. 47.
    Wittgenstein, L.: Philosophical Investigations. Blackwell Publishers, Oxford (2002)zbMATHGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Cracow University of EconomicCracowPoland

Personalised recommendations