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Article published In: Interaction Studies
Vol. 17:3 (2016) ► pp.371–389

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Does successful small-scale coordination help or hinder coordination at larger scales?

 | Dartmouth College, USA | Indiana University, USA
 | Indiana University, USA
Published online: 30 March 2017
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https://doi.org/10.1075/is.17.3.03fre
Abstract
An individual can interact with the same set of people over many different scales simultaneously. Four people might interact as a group of four and, at the same time, in pairs and triads. What is the relationship between different parallel interaction scales, and how might those scales themselves interact?
We devised a four-player experimental game, the Modular Stag Hunt, in which participants chose not just whether to coordinate, but with whom, and at what scale. Our results reveal coordination behavior with such a strong preference for dyads that undermining pairwise coordination actually improves group-scale outcomes. We present these findings as experimental evidence for competition, as opposed to complementarity, between different possible scales of multi-player coordination. This result undermines a basic premise of approaches, like those of network science, that fail to model the interacting effects of dyadic, triadic, and group-scale structures on group outcomes.
Article outline
  • Introduction
  • Generalizing the study of coordination across scales
  • Methods
    • The Modular Stag Hunt
    • Experimental design
    • Subjects and procedure
    • Measures
      • Dependent variable
      • Supporting dependent variables
  • Results
    • Descriptives
    • Main test
    • Supporting analyses
  • Discussion
    • Pairwise coordination prevents coordination at higher scales
    • Alternative explanations
    • History dependence
  • Conclusion
  • Acknowledgements
  • Notes
  • References
References (45)
References
Ahn, T., Esarey, J., & Scholz, J. (2009). Reputation and Cooperation in Voluntary Exchanges: Comparing Local and Central Institutions. The Journal of Politics, 71(02), 398–413. Retrieved from [URL]
Ahn, T., Isaac, R., & Salmon, T. (2008). Endogenous group formation. Journal of Public Economic Theory, 10(2), 171. Google Scholar logo with link to Google Scholar
Bavelas, A. (1950). Communication patterns in task-oriented groups. Journal of the Acoustical Society of America, 221(61), 725–730. Google Scholar logo with link to Google Scholar
(1952). Communication patterns in problem-solving groups. Cybernetics: Circular Causal, and Feedback Mechanisms in Biological and Social Systems, 1–44.Google Scholar logo with link to Google Scholar
Berninghaus, S. K., Ehrhart, K. M., & Keser, C. (2002). Conventions and local interaction structures: Experimental evidence. Games and Economic Behavior, 39(2), 177–205. Google Scholar logo with link to Google Scholar
Berninghaus, S. K., Ehrhart, K. M., & Ott, M. (2010). Cooperation and forward-looking behavior in Hawk-Dove games in endogenous networks: experimental evidence. Mimeo, Karlsruhe Institute of Technology, Faculty of Economics.Google Scholar logo with link to Google Scholar
Bornstein, G., Budescu, D., & Zamir, S. (1997). Cooperation in intergroup, N-person, and two-person games of chicken. Journal of Conflict Resolution, 41(3), 384. Google Scholar logo with link to Google Scholar
Camerer, C. F. (2003). Behavioral game theory: Experiments in strategic interaction. Princeton University Press.Google Scholar logo with link to Google Scholar
Camerer, C. F., & Weber, R. (2007). Experimental Organizational Economics. In the Handbook of Organizational Economics, Eds. R. Gibbons and J. Roberts. New Jersey: Princeton University Press.Google Scholar logo with link to Google Scholar
(2008). Growing organizational culture in the laboratory. In C. R. Plott & V. L. Smith (Eds.), Handbook of Experimental Economics Results. Amsterdam: Elsevier. Google Scholar logo with link to Google Scholar
Christie, L., Luce, R., & Macy, J. (1952). Communication and learning in task-oriented groups. Technical Report. MIT.Google Scholar logo with link to Google Scholar
Cooper, D. J., & Kagel, J. H. (2005). Are two heads better than one? Team versus individual play in signaling games. American Economic Review, 95(3), 477–509. Google Scholar logo with link to Google Scholar
Cooper, R., DeJong, D., & Forsythe, R. (1990). Selection criteria in coordination games: Some experimental results. American Economic Review, 80(1), 218–233.Google Scholar logo with link to Google Scholar
Devetag, G. (2005). Precedent transfer in coordination games: An experiment. Economic Letters, 891, 227–232. Google Scholar logo with link to Google Scholar
Duffy, J., & Hopkins, E. (2005). Learning, information, and sorting in market entry games: theory and evidence. Games and Economic Behavior, 51(1), 31–62. Google Scholar logo with link to Google Scholar
Frey, S., & Goldstone, R. L. (2010). Group Stratification and Coordination Failure in a Continuous N-Player Stag Hunt. Presented at the 2010 Proceedings of the Cognitive Science Society.Google Scholar logo with link to Google Scholar
Fu, F., Hauert, C., Nowak, M. A., & Wang, L. (2008). Reputation-based partner choice promotes cooperation in social networks. Physical Review E, 78(2), 026117. Google Scholar logo with link to Google Scholar
Glanzer, M., & Glaser, R. (1961). Techniques for the study of group structure and behavior II: Empirical studies of the effects of structure in small groups. Psychological Bulletin, 58(1), 1–27. Google Scholar logo with link to Google Scholar
Goldstone, R. L., Roberts, M., Mason, W., & Gureckis, T. (2010). Collective Search in Concrete and Abstract Spaces. In T. Kugler, J. C. Smith, T. Connolly, & Y. Son (Eds.), Decision Modeling and Behavior in Complex and Uncertain Environments (pp. 277–308). New York: Springer Verlag.Google Scholar logo with link to Google Scholar
Goldstone, R. L., Wisdom, T. N., Roberts, M. E., & Frey, S. (2013). Learning Along With Others. In Psychology of Learning and Motivation (Vol. 581, pp. 1–45). Elsevier.
Grosskopf, B. (2003). Reinforcement and directional learning in the ultimatum game with responder competition. Experimental Economics, 6(2), 141–158. Google Scholar logo with link to Google Scholar
Guetzkow, H., & Simon, H. (1955). The impact of certain communication nets upon organization and performance in task-oriented groups. Management Science, 1(3/4), 233–250. Google Scholar logo with link to Google Scholar
Harsanyi, J. C., & Selten, R. (1988). A General Theory of Equilibrium Selection in Games. MIT Press Books, 11.Google Scholar logo with link to Google Scholar
Hornsey, M. J. (2008). Social Identity Theory and Self-categorization Theory: A Historical Review. Social and Personality Psychology Compass, 2(1), 204–222.
Kearns, M., Suri, S., & Montfort, N. (2006). An experimental study of the coloring problem on human subject networks. Science, 313(5788), 824. Google Scholar logo with link to Google Scholar
Klamt, S., Haus, U.-U., & Theis, F. (2009). Hypergraphs and Cellular Networks. PLoS Computational Biology, 5(5), e1000385.
Kun, Á., Boza, G., & Scheuring, I. (2010). Cooperators Unite! Assortative linking promotes cooperation particularly for medium sized associations. BMC Evolutionary Biology, 10(173). Retrieved from [URL]
Leavitt, H. (1951). Some effects of certain communication patterns on group performance. Journal of Abnormal and Social Psychology, 46(1), 38–50. Google Scholar logo with link to Google Scholar
Maldonado, H., Klemmer, S. R., & Pea, R. D. (2009). When is collaborating with friends a good idea? Insights from design education (Vol. 11, pp. 227–231). Presented at the Proceedings of the 9th international conference on Computer supported collaborative learning, International Society of the Learning Sciences.
Mason, W., Jones, A., & Goldstone, R. L. (2008). Propagation of innovations in networked groups. Journal of Experimental Psychology, 137(3), 422–433. Google Scholar logo with link to Google Scholar
Mullen, B., Johnson, C., & Salas, E. (1991). Productivity loss in brainstorming groups: A meta-analytic integration. Basic and Applied Social Psychology, 12(1), 3–23. Google Scholar logo with link to Google Scholar
Newman, M. (2004). Detecting community structure in networks. The European Physical Journal B, 381, 321–330. Google Scholar logo with link to Google Scholar
Newman, M., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical Review E, 69(2). Google Scholar logo with link to Google Scholar
Rankin, F., Van Huyck, J., & Battalio, R. (2000). Strategic similarity and emergent conventions: Evidence from similar stag hunt games. Games and Economic Behavior, 321, 315–337. Google Scholar logo with link to Google Scholar
Ravasz, E., Somera, A., Mongru, D., Oltvai, Z., & Barabási, A. (2002). Hierarchical organization of modularity in metabolic networks. Science, 297(5586), 1551. Google Scholar logo with link to Google Scholar
Rick, S., Weber, R., & Camerer, C. F. (2007). Knowledge Transfer in Simple Laboratory Firms: The Role of Tacit vs. Explicit Knowledge. Department of Social and Decision Sciences Working Paper.Google Scholar logo with link to Google Scholar
Riedl, A., Rohde, I. M. T., & Strobel, M. (2016). Efficient Coordination in Weakest-Link Games. Review of Economic Studies, 83(2), 737–767.
Salmon, T. C., & Weber, R. A. (2016). Maintaining Efficiency While Integrating Entrants From Lower Performing Groups: An Experimental Study. The Economic Journal. Google Scholar logo with link to Google Scholar
Skyrms, B. (2004). The stag hunt and the evolution of social structure. Cambridge Univ Press.Google Scholar logo with link to Google Scholar
Skyrms, B., & Pemantle, R. (2000). A dynamic model of social network formation. Proceedings of the National Academy of Sciences of the United States of America, 97(16), 9340. Google Scholar logo with link to Google Scholar
Stahl, D. O. (2003). Action reinforcement learning versus rule learning. Greek Economic Review, 221, 27–56.
Weber, R. (2006). Managing growth to achieve efficient coordination in large groups. American Economic Review, 96(1), 114–126. Google Scholar logo with link to Google Scholar
Weber, R., & Camerer, C. F. (2003). Cultural conflict and merger failure: An experimental approach. Management Science, 49(4), 400–415. Google Scholar logo with link to Google Scholar
Wenzel, M., Mummendey, A., & Waldzus, S. (2007). Superordinate identities and intergroup conflict: The ingroup projection model. European Review of Social Psychology, 18(1), 331–372. http://doi.org/ Google Scholar logo with link to Google Scholar
Woolley, A., Chabris, C., Pentland, A., & Hashmi, N. (2010). Evidence for a Collective Intelligence Factor in the Performance of Human Groups. Science, 3301, 686–688. Google Scholar logo with link to Google Scholar
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