ArticleJournal of the experimental analysis of behavior2026
Delay-probability asymmetry in discounting: An anomaly in multiattribute choice.
Article in Journal of the experimental analysis of behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Delay-probability asymmetry in discounting: An anomaly in multiattribute choice.Journal of the experimental analysis of behavior · 2026Article
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4 authors.
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Abstract
The discounting of delayed rewards plays an important role in everyday decision making, and steep discounting is associated with numerous behavioral problems. Most tasks used to assess delay discounting, however, are far simpler than many everyday decisions in which outcomes are both probabilistic and delayed. Probability, not delay, has been suggested to be the more salient attribute, a phenomenon we term delay-probability asymmetry. In two experiments, we compared preference on two-attribute (amount and either delay or probability) tasks designed to result in equivalent discounting with preference on three-attribute (amount, delay, and probability) tasks that included the same delay and probability conditions as well as interleaved three-attribute conditions. Although three prominent models of choice (Białaszek et al., 2020; Killeen, 2023a; Vanderveldt et al., 2015) accurately described preference on the three-attribute tasks, they failed to predict the asymmetry. Our results showed that the asymmetry resulted primarily from a decrease in delay discounting rather than from an increase in the salience of probability discounting. This decrease in degree of delay discounting may lead to more patient decisions in everyday choice situations and could reflect a shift to a better long-term decision-making strategy when outcomes are both probabilistic and delayed.
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