IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v576y2021ics0378437121002958.html
   My bibliography  Save this article

The Peter Principle and learning: A safer way to promote workers

Author

Listed:
  • Farias, B.
  • Rapôso, O.
  • Penna, T.J.P.
  • Girardi, D.

Abstract

In 1969, the psychologist Laurence J. Peter made a observation about how organizations promote its members: “The members of an organization climb the hierarchy until the level of maximum incompetence”. The first computational study on this principle suggests that promoting members randomly is the safest strategy. Here, we modify the original model adding the diversity of competences and learning. Our results suggest that, even though the Peter principle negatively affects the efficiency of a business, this effect is less drastic than the one suggested in the previous work when adding the new ingredients. The strategy of promoting the individual with the best performance in a level really seems to be the best strategy, recovering the common sense hypothesis.

Suggested Citation

  • Farias, B. & Rapôso, O. & Penna, T.J.P. & Girardi, D., 2021. "The Peter Principle and learning: A safer way to promote workers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 576(C).
    • Handle: RePEc:eee:phsmap:v:576:y:2021:i:c:s0378437121002958
    DOI: 10.1016/j.physa.2021.126023
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121002958
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.126023?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alan Benson & Danielle Li & Kelly Shue, 2019. "Promotions and the Peter Principle," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 134(4), pages 2085-2134.
    2. Edward P. Lazear, 2004. "The Peter Principle: A Theory of Decline," Journal of Political Economy, University of Chicago Press, vol. 112(S1), pages 141-163, February.
    3. Pluchino, Alessandro & Rapisarda, Andrea & Garofalo, Cesare, 2011. "Efficient promotion strategies in hierarchical organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3496-3511.
    4. 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.
    5. Julius Kane, 1970. "Dynamics of the Peter Principle," Management Science, INFORMS, vol. 16(12), pages 800-811, August.
    6. Fetta, A.G. & Harper, P.R. & Knight, V.A. & Vieira, I.T. & Williams, J.E., 2012. "On the Peter Principle: An agent based investigation into the consequential effects of social networks and behavioural factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2898-2910.
    7. Pluchino, Alessandro & Garofalo, Cesare & Rapisarda, Andrea & Spagano, Salvatore & Caserta, Maurizio, 2011. "Accidental politicians: How randomly selected legislators can improve parliament efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3944-3954.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng, Yuan & Chang, Meng & Xue, Yanbo, 2020. "A computational study of promotion dynamics and organizational efficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    2. Fetta, A.G. & Harper, P.R. & Knight, V.A. & Vieira, I.T. & Williams, J.E., 2012. "On the Peter Principle: An agent based investigation into the consequential effects of social networks and behavioural factors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(9), pages 2898-2910.
    3. Sobkowicz, Pawel, 2016. "Agent based model of effects of task allocation strategies in flat organizations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 17-30.
    4. Udhayanan, Prateksha & Mishra, Swasti S. & Rao, Shrisha, 2021. "Firm dynamics and employee performance management in duopoly markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    5. Alessandro Pluchino & Alessio Emanuele Biondo & Andrea Rapisarda, 2018. "Talent Versus Luck: The Role Of Randomness In Success And Failure," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(03n04), pages 1-31, May.
    6. Javarone, Marco Alberto, 2014. "Social influences in opinion dynamics: The role of conformity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 414(C), pages 19-30.
    7. Alessio Emanuele Biondo & Alessandro Pluchino & Andrea Rapisarda & Dirk Helbing, 2013. "Are Random Trading Strategies More Successful than Technical Ones?," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-13, July.
    8. Caserta, Maurizio & Pluchino, Alessandro & Rapisarda, Andrea & Spagano, Salvatore, 2021. "Why lot? How sortition could help representative democracy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    9. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    10. João Ricardo Faria & Franklin G. Mixon, 2020. "The Peter and Dilbert Principles applied to academe," Economics of Governance, Springer, vol. 21(2), pages 115-132, June.
    11. Pawel Sobkowicz, 2010. "Dilbert-Peter Model of Organization Effectiveness: Computer Simulations," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(4), pages 1-4.
    12. Alessio Emanuele Biondo & Alfio Giarlotta & Alessandro Pluchino & Andrea Rapisarda, 2016. "Perfect Information vs Random Investigation: Safety Guidelines for a Consumer in the Jungle of Product Differentiation," PLOS ONE, Public Library of Science, vol. 11(1), pages 1-26, January.
    13. Inturri, Giuseppe & Le Pira, Michela & Giuffrida, Nadia & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea & D'Angelo, Riccardo, 2019. "Multi-agent simulation for planning and designing new shared mobility services," Research in Transportation Economics, Elsevier, vol. 73(C), pages 34-44.
    14. Amanda Goodall & Margit Osterloh & Mandy Fong, 2020. "Women Shy Away From Competition – How To Overcome It," CREMA Working Paper Series 2020-21, Center for Research in Economics, Management and the Arts (CREMA).
    15. Grabner, Isabella & Künneke, Judith & Moers, Frank, 2024. "Promotion decisions and the adoption of explicit potential assessment," Other publications TiSEM cd81d3bd-ce65-4a47-b552-6, Tilburg University, School of Economics and Management.
    16. A. E. Biondo & A. Pluchino & A. Rapisarda & D. Helbing, 2013. "Are random trading strategies more successful than technical ones?," Papers 1303.4351, arXiv.org, revised Jul 2013.
    17. L. S. Di Mauro & A. Pluchino & A. E. Biondo, 2018. "A Game of Tax Evasion: evidences from an agent-based model," Papers 1809.08146, arXiv.org.
    18. Nadia Giuffrida & Michela Le Pira & Giuseppe Inturri & Matteo Ignaccolo & Giovanni Calabrò & Blochin Cuius & Riccardo D’Angelo & Alessandro Pluchino, 2020. "On-Demand Flexible Transit in Fast-Growing Cities: The Case of Dubai," Sustainability, MDPI, vol. 12(11), pages 1-15, May.
    19. Anja Schöttner & Veikko Thiele, 2010. "Promotion Tournaments and Individual Performance Pay," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 19(3), pages 699-731, September.
    20. Jed DeVaro & Oliver Gürtler, 2020. "Strategic shirking in competitive labor markets: A general model of multi‐task promotion tournaments with employer learning," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 29(2), pages 335-376, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:576:y:2021:i:c:s0378437121002958. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.