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A “Cognitive Miser” Theory of Cooperators Advantage

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  • Orbell, John
  • Dawes, Robyn M.

Abstract

We propose a new model of cooperators' advantage depending neither on supplementary incentives nor on cooperators' capacity to recognize, and play selectively with, other cooperators. It depends, rather, on players' making the play-no play decision by the heuristic of projecting their own “cooperate-defect” choices onto potential partners. Cooperators offer to play more often, and fellow cooperators will more often accept their offer. When certain boundary conditions are met, this results in a higher expected payoff for cooperators than for defectors. Empirical support for this heuristic is suggested by expectations data from related social dilemma experiments. Moreover, its use can be justified in Bayesean terms. Our model brings behavioral decision theory's “cognitive miser” paradigm to bear on interdisciplinary concern with the evolution of cooperative behavior and shows how, if other mechanisms provide a suitable “initial kick,” cooperation can evolve in the absence of iteration and in large, mobile societies.

Suggested Citation

  • Orbell, John & Dawes, Robyn M., 1991. "A “Cognitive Miser” Theory of Cooperators Advantage," American Political Science Review, Cambridge University Press, vol. 85(2), pages 515-528, June.
    • Handle: RePEc:cup:apsrev:v:85:y:1991:i:02:p:515-528_17
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    Cited by:

    1. John Ermisch & Diego Gambetta & Heather Laurie & Thomas Siedler & S. C. Noah Uhrig, 2009. "Measuring people's trust," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(4), pages 749-769, October.
    2. Elinor Ostrom, 2010. "Analyzing collective action," Agricultural Economics, International Association of Agricultural Economists, vol. 41(s1), pages 155-166, November.
    3. Subhasish M. Chowdhury & Alexandros Karakostas, 2020. "An experimental investigation of the ‘tenuous trade-off’ between risk and incentives in organizations," Theory and Decision, Springer, vol. 88(1), pages 153-190, February.
    4. Florian Heine & Martin Sefton, 2018. "To Tender or Not to Tender? Deliberate and Exogenous Sunk Costs in a Public Good Game," Games, MDPI, vol. 9(3), pages 1-28, June.
    5. Feng, Sinan & Liu, Xuesong & Dong, Yida, 2022. "Limited punishment pool may promote cooperation in the public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    6. Pradeep, Siddhartha, 2019. "Game theory, Strategies and the convoluted triangle - India, Pakistan, Kashmir," EconStor Preprints 195929, ZBW - Leibniz Information Centre for Economics.
    7. Jordan Mansell, 2020. "Causation and Behavior: The Necessity and Benefits of Incorporating Evolutionary Thinking into Political Science," Social Science Quarterly, Southwestern Social Science Association, vol. 101(5), pages 1677-1698, September.
    8. Nosenzo, Daniele & Tufano, Fabio, 2017. "The effect of voluntary participation on cooperation," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 307-319.
    9. Teck-Hua Ho & Keith Weigelt, 2005. "Trust Building Among Strangers," Management Science, INFORMS, vol. 51(4), pages 519-530, April.
    10. Bicchieri, Cristina & Maras, Marta, 2022. "Intentionality matters for third-party punishment but not compensation in trust games," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 205-220.
    11. Esther Hauk & Rosemarie Nagel, 2001. "Choice of Partners in Multiple Two-Person Prisoner's Dilemma Games," Journal of Conflict Resolution, Peace Science Society (International), vol. 45(6), pages 770-793, December.
    12. Robert Neumann, 2016. "Understanding trustworthiness: using response latencies from CATI surveys to learn about the “crucial” variable in trust research," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 43-64, January.

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