Information combination and preference reversals: Eye-tracking data

• Eye-tracking is used to study attention in classical preference reversal tasks. • We focus on fixation transitions to study how information is compared across options. • Choice induces more across-bet comparisons than evaluation. • Transition patterns do not predict reversals, challenging context-based theories. • Depth of reflection is higher in evaluation, but not robustly tied to consistency. In the classic preference reversal (PR) phenomenon, individuals often choose the safer of two gambles but assign a higher monetary evaluation to the riskier one. A key distinction between choice and evaluation tasks is that the former typically require comparative processing of the two bets, while the latter can be conducted in isolation for each bet. If this task-mode difference plays a causal role in generating PRs, then the frequency of PRs across individuals should correlate with differences in comparative cognitive processes across tasks. Assuming that sequences of visual fixations reflect cognitive comparisons, we test this hypothesis using eye-tracking during a classic PR experiment. Specifically, we compare the prevalence of across-bet transitions , eye movements between the probabilities or prizes of different bets, with within-bet transitions , movements between attributes of the same bet. As expected, participants exhibit more across-bet transitions in Choice than in Evaluation. However, variation in transition patterns does not predict behavior or PR incidence, challenging context-dependent explanations of classical PRs.

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Publication Details

Journal
Journal of Economic Psychology
Published
2025-12-25
DOI
https://doi.org/10.1016/j.joep.2025.102875
Primary Topic
Decision-Making and Behavioral Economics
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article
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article

Information combination and preference reversals: Eye-tracking data

Eli Spiegelman, Raúl López-Pérez
Journal of Economic Psychology
Decision-Making and Behavioral Economics
article

Information combination and preference reversals: Eye-tracking data

Eli Spiegelman, Raúl López-Pérez
article en

Abstract

• Eye-tracking is used to study attention in classical preference reversal tasks. • We focus on fixation transitions to study how information is compared across options. • Choice induces more across-bet comparisons than evaluation. • Transition patterns do not predict reversals, challenging context-based theories. • Depth of reflection is higher in evaluation, but not robustly tied to consistency. In the classic preference reversal (PR) phenomenon, individuals often choose the safer of two gambles but assign a higher monetary evaluation to the riskier one. A key distinction between choice and evaluation tasks is that the former typically require comparative processing of the two bets, while the latter can be conducted in isolation for each bet. If this task-mode difference plays a causal role in generating PRs, then the frequency of PRs across individuals should correlate with differences in comparative cognitive processes across tasks. Assuming that sequences of visual fixations reflect cognitive comparisons, we test this hypothesis using eye-tracking during a classic PR experiment. Specifically, we compare the prevalence of across-bet transitions , eye movements between the probabilities or prizes of different bets, with within-bet transitions , movements between attributes of the same bet. As expected, participants exhibit more across-bet transitions in Choice than in Evaluation. However, variation in transition patterns does not predict behavior or PR incidence, challenging context-dependent explanations of classical PRs.

Journal of Economic PsychologyVol. 113
Université de Bourgogne (FR), Université Bourgogne Franche-Comté (FR), National Research Council (LK), Institute of History (HU), Université Bourgogne Europe (FR)
Openalex Percentile: Top 27%
Decision-Making and Behavioral Economics
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Information combination and preference reversals: Eye-tracking data — Eli Spiegelman, Raúl López-Pérez · Journal of Economic Psychology (2025) | TGRS Research Map | TGRS