IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v665y2025ics0378437125001487.html

Group size matters: Synergistic effects and reduced inequality in performance rankings

Author

Listed:
  • Reia, Sandro M.
  • Pfoser, Dieter
  • Campos, Paulo R.A.

Abstract

Contemporary society often employs ranking systems to evaluate and reward individual performances based on meritocratic principles. However, these systems can have unintended consequences, impacting creativity and equality. This study presents a statistical analysis of a ranking performance model to examine the implications of these systems on social dynamics. Using a simulation approach, we explore the role of imitation in determining individuals’ success and how these dynamics influence overall group productivity and inequality. Our results unveil a synergistic effect of increasing group size and enhancing collective output while reducing individual performance inequality. Additionally, we investigate the social dynamics on random graphs, scale-free, and small-world networks to understand the influence of network topology, showing that connectivity within the group significantly influences both performance and inequality. Our results also demonstrate that high clustering combined with short path lengths reduces inequalities. These findings provide insights into optimizing ranking systems to balance merit-based recognition with the need for innovation and equality, suggesting strategies to enhance group synergy.

Suggested Citation

  • Reia, Sandro M. & Pfoser, Dieter & Campos, Paulo R.A., 2025. "Group size matters: Synergistic effects and reduced inequality in performance rankings," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 665(C).
    • Handle: RePEc:eee:phsmap:v:665:y:2025:i:c:s0378437125001487
    DOI: 10.1016/j.physa.2025.130496
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437125001487
    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.2025.130496?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

    for a different version of it.

    References listed on IDEAS

    as
    1. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    2. Christopher A. Parsons & Johan Sulaeman & Michael C. Yates & Daniel S. Hamermesh, 2011. "Strike Three: Discrimination, Incentives, and Evaluation," American Economic Review, American Economic Association, vol. 101(4), pages 1410-1435, June.
    3. Michael Park & Erin Leahey & Russell J. Funk, 2023. "Papers and patents are becoming less disruptive over time," Nature, Nature, vol. 613(7942), pages 138-144, January.
    4. Chengyi Tu & Paolo D’Odorico & Zhe Li & Samir Suweis, 2023. "The emergence of cooperation from shared goals in the governance of common-pool resources," Nature Sustainability, Nature, vol. 6(2), pages 139-147, February.
    5. Y. Ulrich & J. Saragosti & C. K. Tokita & C. E. Tarnita & D. J. C. Kronauer, 2018. "Fitness benefits and emergent division of labour at the onset of group living," Nature, Nature, vol. 560(7720), pages 635-638, August.
    6. Franck, Egon & Nüesch, Stephan, 2010. "The effect of talent disparity on team productivity in soccer," Journal of Economic Psychology, Elsevier, vol. 31(2), pages 218-229, April.
    7. Stanley L. Brue, 1993. "Retrospectives: The Law of Diminishing Returns," Journal of Economic Perspectives, American Economic Association, vol. 7(3), pages 185-192, Summer.
    8. Stephen P. Borgatti & Rob Cross, 2003. "A Relational View of Information Seeking and Learning in Social Networks," Management Science, INFORMS, vol. 49(4), pages 432-445, April.
    9. Ambler, Kate & Godlonton, Susan & Recalde, María P., 2021. "Follow the leader? A field experiment on social influence," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1280-1297.
    10. José F Fontanari, 2014. "Imitative Learning as a Connector of Collective Brains," PLOS ONE, Public Library of Science, vol. 9(10), pages 1-7, October.
    11. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    12. Chengyi Tu & Fabio Menegazzo & Paolo D'Odorico & Samir Suweis, 2024. "The role of the Allee effect in common-pool resource and its sustainability," Papers 2405.01271, arXiv.org.
    13. José Fontanari, 2015. "Exploring NK fitness landscapes using imitative learning," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(10), pages 1-7, October.
    14. Jonas Hedlund & Carlos Oyarzun, 2018. "Imitation in heterogeneous populations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(4), pages 937-973, June.
    15. Rafols, Ismael & Leydesdorff, Loet & O’Hare, Alice & Nightingale, Paul & Stirling, Andy, 2012. "How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management," Research Policy, Elsevier, vol. 41(7), pages 1262-1282.
    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. Tao Yi & Chaoying Tang, 2025. "Research exploration, collaborative partnerships, and scientific breakthrough: evidence from China’s State Key Laboratories," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(8), pages 4423-4464, August.
    2. Gerald C. Kane & Maryam Alavi, 2008. "Casting the Net: A Multimodal Network Perspective on User-System Interactions," Information Systems Research, INFORMS, vol. 19(3), pages 253-272, September.
    3. Linda Argote & Sunkee Lee & Jisoo Park, 2021. "Organizational Learning Processes and Outcomes: Major Findings and Future Research Directions," Management Science, INFORMS, vol. 67(9), pages 5399-5429, September.
    4. Brennecke, Julia & Rank, Olaf, 2017. "The firm’s knowledge network and the transfer of advice among corporate inventors—A multilevel network study," Research Policy, Elsevier, vol. 46(4), pages 768-783.
    5. Adrián Kovács & Bart Looy & Bruno Cassiman, 2015. "Exploring the scope of open innovation: a bibliometric review of a decade of research," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 951-983, September.
    6. Rakas, Marija & Hain, Daniel S., 2019. "The state of innovation system research: What happens beneath the surface?," Research Policy, Elsevier, vol. 48(9), pages 1-1.
    7. Elina H. Hwang & Param Vir Singh & Linda Argote, 2015. "Knowledge Sharing in Online Communities: Learning to Cross Geographic and Hierarchical Boundaries," Organization Science, INFORMS, vol. 26(6), pages 1593-1611, December.
    8. Sheen S. Levine & Michael J. Prietula, 2012. "How Knowledge Transfer Impacts Performance: A Multilevel Model of Benefits and Liabilities," Organization Science, INFORMS, vol. 23(6), pages 1748-1766, December.
    9. Simon Rodan, 2008. "Organizational learning: effects of (network) structure and (individual) strategy," Computational and Mathematical Organization Theory, Springer, vol. 14(3), pages 222-247, September.
    10. Christos Kolympiris & Sebastian Hoenen & Peter G. Klein, 2019. "Learning by Seconding: Evidence from National Science Foundation Rotators," Organization Science, INFORMS, vol. 30(3), pages 528-551, May.
    11. Jinyoung Min & Junyeong Lee & Sunghan Ryu & Heeseok Lee, 2022. "The effects of interaction between team climates and KMS value perception on knowledge activities: a multilevel socio-technical systems approach," Information Technology and Management, Springer, vol. 23(1), pages 1-21, March.
    12. Francis Ferreira Franco & Paulo Freitas Gomes, 2024. "New coevolution dynamic as an optimization strategy in group problem solving," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 97(12), pages 1-11, December.
    13. Abhirup Chakrabarti & Will Mitchell, 2013. "The Persistent Effect of Geographic Distance in Acquisition Target Selection," Organization Science, INFORMS, vol. 24(6), pages 1805-1826, December.
    14. Sriram Narayanan & Sridhar Balasubramanian & Jayashankar M. Swaminathan, 2009. "A Matter of Balance: Specialization, Task Variety, and Individual Learning in a Software Maintenance Environment," Management Science, INFORMS, vol. 55(11), pages 1861-1876, November.
    15. Massimiliano Ferrara & Roberto Mavilia & Bruno Antonio Pansera, 2017. "Extracting knowledge patterns with a social network analysis approach: an alternative methodology for assessing the impact of power inventors," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1593-1625, December.
    16. Davies, Andrew & Manning, Stephan & Söderlund, Jonas, 2018. "When neighboring disciplines fail to learn from each other: The case of innovation and project management research," Research Policy, Elsevier, vol. 47(5), pages 965-979.
    17. Whalen, Ryan, 2018. "Boundary spanning innovation and the patent system: Interdisciplinary challenges for a specialized examination system," Research Policy, Elsevier, vol. 47(7), pages 1334-1343.
    18. Myong-Hun Chang & Joseph E. Harrington, 2007. "Innovators, Imitators, and the Evolving Architecture of Problem-Solving Networks," Organization Science, INFORMS, vol. 18(4), pages 648-666, August.
    19. Guo, Liying & Wang, Yang & Li, Meiling, 2024. "Exploration, exploitation and funding success: Evidence from junior scientists supported by the Chinese Young Scientists Fund," Journal of Informetrics, Elsevier, vol. 18(2).
    20. Vallstrom, Daniel, 2025. "Cooperative Evolutionary Pressure and Diminishing Returns Might Explain the Fermi Paradox: On What Super-AIs Are Like," OSF Preprints bq438_v3, Center for Open Science.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:665:y:2025:i:c:s0378437125001487. 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.