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The Peter principle revisited: A computational study

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  • Pluchino, Alessandro
  • Rapisarda, Andrea
  • Garofalo, Cesare

Abstract

In the late sixties the Canadian psychologist Laurence J. Peter advanced an apparently paradoxical principle, named since then after him, which can be summarized as follows: ‘Every new member in a hierarchical organization climbs the hierarchy until he/she reaches his/her level of maximum incompetence’. Despite its apparent unreasonableness, such a principle would realistically act in any organization where the mechanism of promotion rewards the best members and where the competence at their new level in the hierarchical structure does not depend on the competence they had at the previous level, usually because the tasks of the levels are very different to each other. Here we show, by means of agent based simulations, that if the latter two features actually hold in a given model of an organization with a hierarchical structure, then not only is the Peter principle unavoidable, but also it yields in turn a significant reduction of the global efficiency of the organization. Within a game theory-like approach, we explore different promotion strategies and we find, counterintuitively, that in order to avoid such an effect the best ways for improving the efficiency of a given organization are either to promote each time an agent at random or to promote randomly the best and the worst members in terms of competence.

Suggested Citation

  • Pluchino, Alessandro & Rapisarda, Andrea & Garofalo, Cesare, 2010. "The Peter principle revisited: A computational study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 467-472.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:3:p:467-472
    DOI: 10.1016/j.physa.2009.09.045
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    References listed on IDEAS

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    1. David Dickinson & Marie Claire Villeval, 2007. "The Peter Principle: An Experiment," Post-Print halshs-00175426, HAL.
    2. John H. Miller & Scott E. Page, 2007. "Social Science in Between, from Complex Adaptive Systems: An Introduction to Computational Models of Social Life," Introductory Chapters, in: Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.
    3. John H. Miller & Scott E. Page, 2007. "Complexity in Social Worlds, from Complex Adaptive Systems: An Introduction to Computational Models of Social Life," Introductory Chapters, in: Complex Adaptive Systems: An Introduction to Computational Models of Social Life, Princeton University Press.
    4. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, December.
    5. J. Doyne Farmer & Andrew W. Lo, 1999. "Frontiers of Finance: Evolution and Efficient Markets," Working Papers 99-06-039, Santa Fe Institute.
    6. Klimek, Peter & Hanel, Rudolf & Thurner, Stefan, 2009. "To how many politicians should government be left?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(18), pages 3939-3947.
    7. Julius Kane, 1970. "Dynamics of the Peter Principle," Management Science, INFORMS, vol. 16(12), pages 800-811, August.
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