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Rigorously testing multialternative decision field theory against random utility models.

Nicolas A J Berkowitsch1, Benjamin Scheibehenne1, Jörg Rieskamp1

  • 1Department of Psychology, University of Basel.

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This study tested the multialternative decision field theory (MDFT) against other choice models. MDFT showed an advantage in predicting consumer product choices, especially when context effects were considered.

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Area of Science:

  • Cognitive psychology
  • Decision science
  • Consumer behavior

Background:

  • Cognitive models explain decision-making processes.
  • Sequential sampling models offer insights into choice behavior.
  • Comparing models like MDFT, probit, and logit is crucial for understanding decision mechanisms.

Purpose of the Study:

  • To empirically test the multialternative decision field theory (MDFT) against established random utility models.
  • To evaluate the predictive accuracy of MDFT in consumer choice scenarios.
  • To investigate the role of context effects in decision making.

Main Methods:

  • A within-subject experimental design was employed across two studies.
  • Participants repeatedly made choices among consumer products with varying attributes.
  • Model predictive performance was compared using empirical choice data.

Main Results:

  • Study 1 found all models equally predictive.
  • Study 2 demonstrated MDFT's superior predictive power for choices designed to differentiate models.
  • Study 2 revealed multiple, interdependent context effects within participants.

Conclusions:

  • Sequential sampling models, like MDFT, offer valuable insights into preferential choice cognition.
  • MDFT shows potential for improving predictions of complex consumer choices.
  • Understanding context effects is key to refining decision-making models.