Complexity and Satisficing: Theory with Evidence from Chess.

We develop a satisficing model of choice in which the available alternatives differ in their inherent complexity. We assume—and experimentally validate—that complexity leads to errors in the perception of alternatives' values. The model yields sharp predictions about the effect of complexity on choi...

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Publicado en:Review of Economic Studies Vol. 93; no. 2; pp. 1296 - 1323
Autores principales: Salant, Yuval, Spenkuch, Jörg L
Formato: Artículo
Publicado: Oxford University Press / USA Mar2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2026
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      pub: Oxford University Press / USA
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        10.1093/restud/rdaf041
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        atl: Complexity and Satisficing: Theory with Evidence from Chess.
      aug:
        au:
          Salant, Yuval
          Spenkuch, Jörg L
        affil:
          Kellogg School of Management, Northwestern University, USA
          Kellogg School of Management, Northwestern University, USA and NBER
      su:
        Decision making
        Bounded rationality
        Rational choice theory
        Empirical research
        Chess
        Computational complexity
        Behavioral economics
        Mathematical optimization
      sug:
        subj:
          Decision making
          Bounded rationality
          Rational choice theory
          Empirical research
          Chess
          Computational complexity
          Behavioral economics
          Mathematical optimization
      keyword:
        Choice
        Complexity
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        inLanguage:en
        Maximization
        publisher:Oxford University Press
        sameAs:https://dx.doi.org/10.1093/restud/rdaf041
        Satisficing
        Choice
        Complexity
        copyrightHolder:Review of Economic Studies Ltd
        copyrightYear:2026
        inLanguage:en
        Maximization
        publisher:Oxford University Press
        sameAs:https://dx.doi.org/10.1093/restud/rdaf041
        Satisficing
      ab: We develop a satisficing model of choice in which the available alternatives differ in their inherent complexity. We assume—and experimentally validate—that complexity leads to errors in the perception of alternatives' values. The model yields sharp predictions about the effect of complexity on choice probabilities, some of which qualitatively contrast with those of maximization-based choice models. We confirm the predictions of the satisficing model—and thus reject maximization—in a novel data set with information on hundreds of millions of real-world chess moves by highly experienced players. Looking beyond chess, our work offers a blueprint for incorporating complexity at the level of individual objects into models of choice and for detecting satisficing outside of the laboratory.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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