IDEAS home Printed from https://ideas.repec.org/a/spr/minsoc/v23y2024i1d10.1007_s11299-024-00307-8.html
   My bibliography  Save this article

Interpersonal factors that contribute to collective intelligence in small groups a qualitative systematic review

Author

Listed:
  • Alexis Jeffredo

    (Université de Lorraine)

  • Christophe Clesse

    (Queen Mary University of London)

  • Martine Batt

    (Université de Lorraine)

Abstract

The study of collective intelligence has focused in the last years on crowdsourcing and artificial swarm intelligence. Currently, large online communities have demonstrated their effectiveness but even if the contributions in this domain are significant, it remains essential to question the functioning of collective intelligence in small groups, especially since the gain in popularity of brainstorming strategies, focus groups and co-working practices. In this context, we conducted a qualitative systematic review using Prospero, PRISMA protocol and bias assessment to identify the factors currently recognised as impacting on the emergence of collective intelligence in small groups. These factors were then organised according to the different levels of abstraction observed in research about collective intelligence. From this work, collective intelligence appears as the crystallization of emerging properties that manifest themselves in interactions and whose possibility of existing is intrinsically linked to meta-cognition and meta-communication processes.

Suggested Citation

  • Alexis Jeffredo & Christophe Clesse & Martine Batt, 2024. "Interpersonal factors that contribute to collective intelligence in small groups a qualitative systematic review," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 23(1), pages 145-162, December.
    • Handle: RePEc:spr:minsoc:v:23:y:2024:i:1:d:10.1007_s11299-024-00307-8
    DOI: 10.1007/s11299-024-00307-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11299-024-00307-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11299-024-00307-8?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. Xiao-Liang Shen & Matthew K O Lee & Christy M K Cheung, 2012. "Harnessing collective intelligence of Web 2.0: group adoption and use of Internet-based collaboration technologies," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 10(4), pages 301-311, December.
    2. repec:cup:judgdm:v:8:y:2013:i:4:p:407-424 is not listed on IDEAS
    3. Andrew Mao & Winter Mason & Siddharth Suri & Duncan J Watts, 2016. "An Experimental Study of Team Size and Performance on a Complex Task," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-22, April.
    4. Massari, Giovanni F. & Giannoccaro, Ilaria & Carbone, Giuseppe, 2019. "Are distrust relationships beneficial for group performance? The influence of the scope of distrust on the emergence of collective intelligence," International Journal of Production Economics, Elsevier, vol. 208(C), pages 343-355.
    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. Chao Fu & Wenjun Chang, 2024. "A Markov Chain-Based Group Consensus Method with Unknown Parameters," Group Decision and Negotiation, Springer, vol. 33(5), pages 1019-1048, October.
    2. Giannoccaro, Ilaria & Galesic, Mirta & Massari, Giovanni Francesco & Barkoczi, Daniel & Carbone, Giuseppe, 2020. "Search behavior of individuals working in teams: A behavioral study on complex landscapes," Journal of Business Research, Elsevier, vol. 118(C), pages 507-516.
    3. Zhu, Nibing & Liu, Chang & Yang, Zhilin, 2021. "Team Size, Research Variety, and Research Performance: Do Coauthors’ Coauthors Matter?," Journal of Informetrics, Elsevier, vol. 15(4).
    4. Namjun Cha & Junseok Hwang & Eungdo Kim, 2020. "The optimal knowledge creation strategy of organizations in groupthink situations," Computational and Mathematical Organization Theory, Springer, vol. 26(2), pages 207-235, June.
    5. Jiye Baek & Jesse Shore, 2020. "Forum Size and Content Contribution per Person: A Field Experiment," Management Science, INFORMS, vol. 66(12), pages 5906-5924, December.
    6. Annetta Burger & Talha Oz & William G. Kennedy & Andrew T. Crooks, 2019. "Computational Social Science of Disasters: Opportunities and Challenges," Future Internet, MDPI, vol. 11(5), pages 1-31, April.
    7. Aisha J Ali & Javier Fuenzalida & Margarita Gómez & Martin J Williams, 2021. "Four lenses on people management in the public sector: an evidence review and synthesis," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(2), pages 335-366.
    8. Jeong Sik Kim, 2022. "An Empirical Analysis of the Relationships among Participatory Decision Making and Employees’ Task Performance and Personal Growth," Sustainability, MDPI, vol. 14(19), pages 1-16, September.
    9. Rafał Olszowski & Marcin Chmielowski, 2020. "Collective Intelligence in Polish-Ukrainian Internet Projects. Debate Models and Research Methods," Future Internet, MDPI, vol. 12(6), pages 1-20, June.
    10. Massari, Giovanni Francesco & Giannoccaro, Ilaria, 2021. "Investigating the effect of horizontal coopetition on supply chain resilience in complex and turbulent environments," International Journal of Production Economics, Elsevier, vol. 237(C).
    11. Ming Tang & Huchang Liao, 2023. "Group Structure and Information Distribution on the Emergence of Collective Intelligence," Decision Analysis, INFORMS, vol. 20(2), pages 133-150, June.

    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:spr:minsoc:v:23:y:2024:i:1:d:10.1007_s11299-024-00307-8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.