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Group Structure and Information Distribution on the Emergence of Collective Intelligence

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  • Ming Tang

    (Business School, Sichuan University, Chengdu 610064, China)

  • Huchang Liao

    (Business School, Sichuan University, Chengdu 610064, China)

Abstract

More and more decision-making problems are being solved by groups. Collective intelligence is the ability of groups to perform well when solving complex problems. Thus, it is important to encourage collective intelligence to emerge from groups. In this study, we explore how two critical characteristics of groups, that is, group structure and individual knowledge in groups, influence the emergence of collective intelligence. To do this, we propose a measure for group structure using the collaboration network of a group and a measure for the distribution of individual knowledge in groups. Group structure is measured based on the intensities of links and whether the network is hierarchical or flat. The distribution of individual knowledge is measured from the perspective of whether group information is shared or unique. Social interactions among group members and individual changes in opinion are modeled based on a simulation technique. We find that unbalanced information distribution undermines group performance, whereas group structure can modify the effect of information distribution. We also find that groups with broadly distributed knowledge are good at solving complex problems.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ordeca:v:20:y:2023:i:2:p:133-150
    DOI: 10.1287/deca.2022.0466
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    References listed on IDEAS

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    1. Giuseppe Carbone & Ilaria Giannoccaro, 2015. "Model of human collective decision-making in complex environments," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 88(12), pages 1-10, December.
    2. David V. Budescu & Eva Chen, 2015. "Identifying Expertise to Extract the Wisdom of Crowds," Management Science, INFORMS, vol. 61(2), pages 267-280, February.
    3. Diane L. Rulke & Joseph Galaskiewicz, 2000. "Distribution of Knowledge, Group Network Structure, and Group Performance," Management Science, INFORMS, vol. 46(5), pages 612-625, May.
    4. Frenken, Koen, 2006. "A fitness landscape approach to technological complexity, modularity, and vertical disintegration," Structural Change and Economic Dynamics, Elsevier, vol. 17(3), pages 288-305, September.
    5. Tang, Ming & Liao, Huchang & Xu, Jiuping & Streimikiene, Dalia & Zheng, Xiaosong, 2020. "Adaptive consensus reaching process with hybrid strategies for large-scale group decision making," European Journal of Operational Research, Elsevier, vol. 282(3), pages 957-971.
    6. 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).
    7. Nihal Berktaş & Hande Yaman, 2021. "A Branch-and-Bound Algorithm for Team Formation on Social Networks," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1162-1176, July.
    8. Tang, Ming & Liao, Huchang, 2021. "From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey," Omega, Elsevier, vol. 100(C).
    9. Arthur Carvalho, 2016. "An Overview of Applications of Proper Scoring Rules," Decision Analysis, INFORMS, vol. 13(4), pages 223-242, December.
    10. Jiapeng Liu & Miłosz Kadziński & Xiuwu Liao & Xiaoxin Mao, 2021. "Data-Driven Preference Learning Methods for Value-Driven Multiple Criteria Sorting with Interacting Criteria," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 586-606, May.
    11. Purva Grover & Arpan Kumar Kar & Yogesh K. Dwivedi, 2022. "Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions," Annals of Operations Research, Springer, vol. 308(1), pages 177-213, January.
    12. John P. Lightle & John H. Kagel & Hal R. Arkes, 2009. "Information Exchange in Group Decision Making: The Hidden Profile Problem Reconsidered," Management Science, INFORMS, vol. 55(4), pages 568-581, April.
    13. Asa B. Palley & Jack B. Soll, 2019. "Extracting the Wisdom of Crowds When Information Is Shared," Management Science, INFORMS, vol. 67(5), pages 2291-2309, May.
    14. Argote, Linda & Turner, Marlene E. & Fichman, Mark, 1989. "To centralize or not to centralize: The effects of uncertainty and threat on group structure and performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 43(1), pages 58-74, February.
    15. Gruenfeld, Deborah H & Mannix, Elizabeth A. & Williams, Katherine Y. & Neale, Margaret A., 1996. "Group Composition and Decision Making: How Member Familiarity and Information Distribution Affect Process and Performance," Organizational Behavior and Human Decision Processes, Elsevier, vol. 67(1), pages 1-15, July.
    16. Clintin P. Davis-Stober & David V. Budescu & Stephen B. Broomell & Jason Dana, 2015. "The Composition of Optimally Wise Crowds," Decision Analysis, INFORMS, vol. 12(3), pages 130-143.
    17. 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.
    18. Paul Varella & Mansour Javidan & David A. Waldman, 2012. "A Model of Instrumental Networks: The Roles of Socialized Charismatic Leadership and Group Behavior," Organization Science, INFORMS, vol. 23(2), pages 582-595, April.
    19. Hannu Nurmi, 1998. "Voting paradoxes and referenda," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 15(3), pages 333-350.
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