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Attribute commensurability and context effects in preferential choice.

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  • 1Department of Psychology, Binghamton University, State University of New York, PO Box 6000, Binghamton, NY, 13902, USA. whayes2@binghamton.edu.

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Summary
This summary is machine-generated.

Choice presentation format significantly impacts decision-making context effects. Incommensurable attributes enhance attraction and compromise effects, while commensurable attributes diminish them.

Keywords:
AttentionEvidence accumulation modelsMulti-alternative multi-attribute choicePresentation format

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Area of Science:

  • Decision Science
  • Cognitive Psychology
  • Marketing Science

Background:

  • Context effects in multi-alternative, multi-attribute choice are well-known but often difficult to predict.
  • The presentation format of choice options can influence consumer behavior and decision-making processes.

Purpose of the Study:

  • To investigate how the commensurability of attribute values influences attention allocation and context effects in choice.
  • To predict and demonstrate how manipulating attribute commensurability alters decision patterns.

Main Methods:

  • Developed a modeling framework to predict the impact of attribute commensurability on attention and context effects.
  • Conducted two online choice experiments with 954 adult participants to test the model's predictions.

Main Results:

  • When attributes were incommensurable (e.g., different units or scales), robust attraction and compromise effects were observed.
  • When attributes were commensurable (e.g., same scale), context effects were largely absent.
  • Attribute commensurability significantly altered information integration and choice patterns.

Conclusions:

  • The format of choice information, specifically attribute commensurability, substantially impacts how information is integrated.
  • Understanding attribute commensurability is crucial for predicting and managing context effects in consumer choice.
  • Choice architecture can be designed to influence decision outcomes by manipulating attribute commensurability.