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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Risk preferences in decision-making: A construal level perspective.

Hwan-Ho Noh1, Hye Bin Rim2, Byung-Kwan Lee2

  • 1Barun ICT Research Center, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea.

Acta Psychologica
|December 22, 2024
PubMed
Summary

Construal levels significantly impact risky decision-making. Abstract thinking amplifies framing effects in choices, while detailed thinking reduces them, influencing attention and perception.

Keywords:
Construal level theoryDecision-making contextEnd-stateInformation focusProcessRisky-choice framing effect

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Area of Science:

  • Decision Science
  • Cognitive Psychology

Background:

  • Framing effects influence decision-making by altering how options are presented.
  • Construal level theory posits that abstract thinking (high-level construal) focuses on goals, while concrete thinking (low-level construal) focuses on specifics.

Purpose of the Study:

  • To investigate how construal levels moderate the impact of risky-choice framing on decision preferences.
  • To understand the role of abstract versus concrete thinking in susceptibility to framing effects.

Main Methods:

  • Participants evaluated risky choices presented in gain- and loss-frames.
  • Construal levels were manipulated to create high-level (abstract) and low-level (concrete) thinking conditions.

Main Results:

  • Significant framing effects were observed in high-level construal, with distinct preferences for risky options under gain versus loss frames.
  • Framing effects were substantially reduced in low-level construal, where participants focused more on probabilities.
  • Attention allocation towards outcomes versus processes differed between high- and low-level construal conditions.

Conclusions:

  • Construal level is a critical factor influencing the magnitude of framing effects in risky decision-making.
  • Abstract thinking amplifies framing effects, suggesting potential for bias, while concrete thinking mitigates them.
  • Findings have implications for understanding cognitive biases and designing interventions to improve decision quality.