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Information acquisition and cognitive processes during strategic decision-making: Combining a policy-capturing study

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This study reveals that individuals develop cognitive models to efficiently process information during policy-capturing (PC) experiments. Experience improves efficiency, and information selection aligns with decision-making evaluations.

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Area of Science:

  • Cognitive Psychology
  • Decision Science
  • Human-Computer Interaction

Background:

  • Policy-capturing (PC) methodologies are used to study decision-making processes.
  • A key assumption is that decision-makers develop cognitive models to manage information complexity in PC studies.
  • Understanding information acquisition and cognitive processes in PC is crucial.

Purpose of the Study:

  • To analyze the cognitive processes and information acquisition during policy-capturing experiments.
  • To investigate the influence of experience on decision-making within PC studies.
  • To compare cognitive models of students and professionals.

Main Methods:

  • Utilized eye-tracking technology to monitor information acquisition.
  • Employed policy-capturing (PC) methodology with student and professional samples.
  • Analyzed information processing and judgment formation.

Main Results:

  • Respondents demonstrated increased efficiency with practice during the PC experiment.
  • Information acquisition was selective and consistent with decision evaluations.
  • Despite some differences, student and professional samples showed remarkable similarities in information processing.

Conclusions:

  • The study supports the assumption that cognitive models are built to handle information in PC experiments.
  • The development and function of these cognitive models are not substantially affected by the sample type (students vs. professionals).
  • Eye-tracking provides valuable insights into the cognitive mechanisms underlying policy-capturing.