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In the Short Term We Divide, in the Long Term We Unite: Demographic Crisscrossing and the Effects of Faultlines on Subgroup Polarization

Author

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  • Michael Mäs

    (Chair of Sociology, in particular of Modeling and Simulation, ETH Zurich, 8092 Zurich, Switzerland)

  • Andreas Flache

    (Department of Sociology/Interuniversity Center of Social Science Theory and Methodology, University of Groningen, 9712TG Groningen, The Netherlands)

  • Károly Takács

    (MTA TK “Lendület” Research Center for Educational and Network Studies (RECENS), H-1014 Budapest, Hungary)

  • Karen A. Jehn

    (Melbourne Business School, Carlton, Victoria, 3053 Australia)

Abstract

Do strong demographic faultlines breed opinion polarization in work teams? We integrate two theories that have been used to explain faultline effects. The first, the approach of Lau and Murnighan [Lau DC, Murnighan JK (1998) Demographic diversity and faultlines: The compositional dynamics of organizational groups. Acad. Management Rev. 23(2):325–340], suggests that in teams with strong faultlines the mechanisms of homophilous selection of interaction partners and persuasive influence cause subgroup polarization, defined as the split of the team into subgroups holding opposing opinions. The second, from sociological and anthropological traditions, emphasizes that crisscrossing actors bridge faultlines because they share demographic attributes with several subgroups. Demographically crisscrossing actors help to prevent polarization in social groups. We argue that Lau and Murnighan’s theory implicitly factors in the effects of crisscrossing actors. However, we show that the authors overlooked crucial implications of their theory because they did not consider crisscrossing actors explicitly. Most importantly, we demonstrate that demographic crisscrossing implies that even teams with strong faultlines will overcome polarization in the long run, although they might suffer from it in the short term. We develop and analyze a formal computational model of the opinion and network dynamics in work teams to show the consistency of our reasoning with Lau and Murnighans’ theory. The model also revealed another counterintuitive effect: strong faultlines lead to structures of interaction that make teams with strong faultlines faster in arriving at a stable consensus than teams with weak faultlines.

Suggested Citation

  • Michael Mäs & Andreas Flache & Károly Takács & Karen A. Jehn, 2013. "In the Short Term We Divide, in the Long Term We Unite: Demographic Crisscrossing and the Effects of Faultlines on Subgroup Polarization," Organization Science, INFORMS, vol. 24(3), pages 716-736, June.
  • Handle: RePEc:inm:ororsc:v:24:y:2013:i:3:p:716-736
    DOI: 10.1287/orsc.1120.0767
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    References listed on IDEAS

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    1. Eric Molleman, 2005. "Diversity in Demographic Characteristics, Abilities and Personality Traits: Do Faultlines Affect Team Functioning?," Group Decision and Negotiation, Springer, vol. 14(3), pages 173-193, May.
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    3. Jehn, Karen A. & Bezrukova, Katerina, 2010. "The faultline activation process and the effects of activated faultlines on coalition formation, conflict, and group outcomes," Organizational Behavior and Human Decision Processes, Elsevier, vol. 112(1), pages 24-42, May.
    4. Katerina Bezrukova & Karen A. Jehn & Elaine L. Zanutto & Sherry M. B. Thatcher, 2009. "Do Workgroup Faultlines Help or Hurt? A Moderated Model of Faultlines, Team Identification, and Group Performance," Organization Science, INFORMS, vol. 20(1), pages 35-50, February.
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    6. Kenneth A. Frank & Kyle Fahrbach, 1999. "Organization Culture as a Complex System: Balance and Information in Models of Influence and Selection," Organization Science, INFORMS, vol. 10(3), pages 253-277, June.
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    Cited by:

    1. Shuai Chen & Duanxu Wang & Yun Zhou & Ziguang Chen & Daoyou Wu, 2017. "When too little or too much hurts: Evidence for a curvilinear relationship between team faultlines and performance," Asia Pacific Journal of Management, Springer, vol. 34(4), pages 931-950, December.
    2. Andreas Flache, 2018. "About Renegades And Outgroup Haters: Modeling The Link Between Social Influence And Intergroup Attitudes," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 21(06n07), pages 1-32, September.
    3. Tanzhe Tang & Amineh Ghorbani & Flaminio Squazzoni & Caspar G. Chorus, 2022. "Together alone: a group-based polarization measurement," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3587-3619, October.
    4. Takasumi Kurahashi-Nakamura & Michael Mäs & Jan Lorenz, 2016. "Robust Clustering in Generalized Bounded Confidence Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(4), pages 1-7.
    5. Li Li & Haifen Lin & Yibo Lyu, 2022. "Technology cluster coupling and invulnerability of industrial innovation networks: the role of centralized structure and technological turbulence," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(3), pages 1209-1231, March.
    6. Lucila G Alvarez-Zuzek & Cristian E La Rocca & Federico Vazquez & Lidia A Braunstein, 2016. "Interacting Social Processes on Interconnected Networks," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-17, September.
    7. Ulrich Leicht‐Deobald & Hendrik Huettermann & Heike Bruch & Barbara S. Lawrence, 2021. "Organizational Demographic Faultlines: Their Impact on Collective Organizational Identification, Firm Performance, and Firm Innovation," Journal of Management Studies, Wiley Blackwell, vol. 58(8), pages 2240-2274, December.
    8. Sangseok You & Lionel P. Robert, 2023. "Subgroup formation in human–robot teams: A multi‐study mixed‐method approach with implications for theory and practice," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(3), pages 323-338, March.
    9. Thomas Feliciani & Andreas Flache & Michael Mäs, 2021. "Persuasion without polarization? Modelling persuasive argument communication in teams with strong faultlines," Computational and Mathematical Organization Theory, Springer, vol. 27(1), pages 61-92, March.
    10. Nicoletta Corrocher & Camilla Lenzi, 2022. "Exploring the sources of knowledge diversity in founding teams and its impact on new firms’ innovation," Journal of Evolutionary Economics, Springer, vol. 32(4), pages 1091-1118, September.

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