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A simple satisficing model.

Erlend Dancke Sandorf1, Danny Campbell2, Caspar Chorus3

  • 1School of Economics and Business, Norwegian University of Life Sciences, Ås, Norway.

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People often satisfice rather than maximize utility due to information limits. This study presents a tractable satisficing model, demonstrating its ability to recover consistent parameters across conditions and in empirical applications.

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Area of Science:

  • Behavioral Economics
  • Decision Science

Background:

  • Traditional economic models assume rational agents are omniscient utility maximizers.
  • Real-world decision-making is constrained by information availability and search costs.
  • Satisficing behavior, choosing the first acceptable option, deviates from pure maximization.

Purpose of the Study:

  • To develop a simple and tractable economic model that captures satisficing behavior.
  • To demonstrate the model's ability to consistently estimate parameters under various experimental conditions.
  • To provide an empirical application and discuss implications for choice modeling.

Main Methods:

  • Development of a novel, tractable mathematical model for satisficing.
  • Testing the model's parameter recovery using synthetic data.
  • Application of the model to real-world empirical data.

Main Results:

  • The satisficing model successfully retrieves consistent parameters across a wide range of experimental conditions.
  • The model performs well on both synthetic and empirical datasets.
  • Parameter recovery is robust, indicating the model's reliability.

Conclusions:

  • The developed satisficing model offers a viable alternative to traditional utility maximization frameworks.
  • The model provides a practical tool for analyzing choices influenced by information constraints.
  • Findings support the broader use of satisficing models in economic and behavioral research.