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Can self selection create high-performing teams?

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  • Chen, Roy
  • Gong, Jie

Abstract

Does the way that teams are formed affect their productivity? To address this question, we run an experiment comparing different methods of team formation: (1) random assignment; (2) self selection; and (3) algorithm assignment designed to maximize skill complementarity. We find that self selection creates high-performing teams. These teams perform better on a team task than randomly-assigned teams and as well as those assigned using the algorithm. Exploring the mechanism, we find evidence that, when given the choice, individuals self select into teams primarily based on their social networks and exert higher effort towards the team task.

Suggested Citation

  • Chen, Roy & Gong, Jie, 2018. "Can self selection create high-performing teams?," Journal of Economic Behavior & Organization, Elsevier, vol. 148(C), pages 20-33.
    • Handle: RePEc:eee:jeborg:v:148:y:2018:i:c:p:20-33
    DOI: 10.1016/j.jebo.2018.02.004
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    Cited by:

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    2. Julien Senn & Jan Schmitz & Christian Zehnder, 2023. "Leveraging social comparisons: the role of peer assignment policies," ECON - Working Papers 427, Department of Economics - University of Zurich, revised Aug 2023.
    3. Fischer, Mira & Rilke, Rainer Michael & Yurtoglu, B. Burcin, 2020. "Two field experiments on self-selection, collaboration intensity, and team performance," Discussion Papers, Research Unit: Market Behavior SP II 2020-201, WZB Berlin Social Science Center.
    4. Chadi, Adrian & Homolka, Konstantin, 2022. "Little Lies and Blind Eyes – Experimental Evidence on Cheating and Task Performance in Work Groups," Journal of Economic Behavior & Organization, Elsevier, vol. 199(C), pages 122-159.
    5. Brown, Christopher L., 2024. "Team production in endogenous networks," Journal of Economic Behavior & Organization, Elsevier, vol. 217(C), pages 560-580.
    6. Kenju Kamei & Thomas Markussen, 2023. "Free Riding and Workplace Democracy—Heterogeneous Task Preferences and Sorting," Management Science, INFORMS, vol. 69(7), pages 3884-3904, July.
    7. Kristian López Vargas & Julian Runge & Ruizhi Zhang, 2022. "Algorithmic Assortative Matching on a Digital Social Medium," Information Systems Research, INFORMS, vol. 33(4), pages 1138-1156, December.
    8. Lukas Kiessling & Jonas Radbruch & Sebastian Schaube, 2022. "Self-Selection of Peers and Performance," Management Science, INFORMS, vol. 68(11), pages 8184-8201, November.
    9. Youjin Hahn & Asadul Islam & Eleonora Patacchini & Yves Zenou, 2020. "Friendship and Female Education: Evidence from a Field Experiment in Bangladeshi Primary Schools," The Economic Journal, Royal Economic Society, vol. 130(627), pages 740-764.
    10. Julius Duker & Alexander Rieber, 2024. "Performance, Knowledge Acquisition and Satisfaction in Self-selected Groups: Evidence from a Classroom Field Experiment," Papers 2403.12694, arXiv.org.
    11. Gjedrem, William Gilje & Kvaløy, Ola, 2020. "Relative performance feedback to teams," Labour Economics, Elsevier, vol. 66(C).
    12. Mira Fischer & Rainer Michael Rilke & B. Burcin Yurtoglu, 2023. "When, and why, do teams benefit from self-selection?," Experimental Economics, Springer;Economic Science Association, vol. 26(4), pages 749-774, September.

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    More about this item

    Keywords

    Group formation; Teamwork; Self selection; Field experiment;
    All these keywords.

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D23 - Microeconomics - - Production and Organizations - - - Organizational Behavior; Transaction Costs; Property Rights

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