Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration
First-order stochastic dominance is a core principle in rational decision-making. If lottery A has a higher or equal chance of winning an amount $x $ or more compared to lottery B for all x, and a strictly higher chance for at least one $x $ , then A should be preferred over B. Previous...
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Cambridge University Press
2025-01-01
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| Series: | Judgment and Decision Making |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S1930297524000408/type/journal_article |
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| author | Edika Quispe-Torreblanca Neil Stewart Michael H. Birnbaum |
| author_facet | Edika Quispe-Torreblanca Neil Stewart Michael H. Birnbaum |
| author_sort | Edika Quispe-Torreblanca |
| collection | DOAJ |
| description | First-order stochastic dominance is a core principle in rational decision-making. If lottery A has a higher or equal chance of winning an amount
$x $
or more compared to lottery B for all x, and a strictly higher chance for at least one
$x $
, then A should be preferred over B. Previous research suggests that violations of this principle may result from failures in recognizing coalescing equivalence. In Expected Utility Theory (EUT) and Cumulative Prospect Theory (CPT), gambles are represented as probability distributions, where probabilities of equivalent events can be combined, ensuring stochastic dominance. In contrast, the Transfer of Attention Exchange (TAX) model represents gambles as trees with branches for each probability and outcome, making it possible for coalescing and stochastic dominance violations to occur. We conducted two experiments designed to train participants in identifying dominance by splitting coalesced gambles. By toggling between displays of coalesced and split forms of the same choice problem, participants were instructed to recognize stochastic dominance. Despite this training, violations of stochastic dominance were only minimally reduced, as if people find it difficult—or even resist—shifting from a trees-with-branches representation (as in the TAX model) to a cognitive recognition of the equivalence among different representations of the same choice problem. |
| format | Article |
| id | doaj-art-6789f50030a74bc4997bdbe965d413cc |
| institution | Kabale University |
| issn | 1930-2975 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj-art-6789f50030a74bc4997bdbe965d413cc2025-01-16T21:47:03ZengCambridge University PressJudgment and Decision Making1930-29752025-01-012010.1017/jdm.2024.40Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaborationEdika Quispe-Torreblanca0https://orcid.org/0000-0002-0974-0705Neil Stewart1Michael H. Birnbaum2https://orcid.org/0000-0002-2584-2007Leeds University Business School, University of Leeds, Leeds, UKWarwick Business School, University of Warwick, Coventry, UKDepartment of Psychology, California State University, Fullerton, CA, USAFirst-order stochastic dominance is a core principle in rational decision-making. If lottery A has a higher or equal chance of winning an amount $x $ or more compared to lottery B for all x, and a strictly higher chance for at least one $x $ , then A should be preferred over B. Previous research suggests that violations of this principle may result from failures in recognizing coalescing equivalence. In Expected Utility Theory (EUT) and Cumulative Prospect Theory (CPT), gambles are represented as probability distributions, where probabilities of equivalent events can be combined, ensuring stochastic dominance. In contrast, the Transfer of Attention Exchange (TAX) model represents gambles as trees with branches for each probability and outcome, making it possible for coalescing and stochastic dominance violations to occur. We conducted two experiments designed to train participants in identifying dominance by splitting coalesced gambles. By toggling between displays of coalesced and split forms of the same choice problem, participants were instructed to recognize stochastic dominance. Despite this training, violations of stochastic dominance were only minimally reduced, as if people find it difficult—or even resist—shifting from a trees-with-branches representation (as in the TAX model) to a cognitive recognition of the equivalence among different representations of the same choice problem.https://www.cambridge.org/core/product/identifier/S1930297524000408/type/journal_articlestochastic dominancesplitting trainingdominance training |
| spellingShingle | Edika Quispe-Torreblanca Neil Stewart Michael H. Birnbaum Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration Judgment and Decision Making stochastic dominance splitting training dominance training |
| title | Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration |
| title_full | Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration |
| title_fullStr | Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration |
| title_full_unstemmed | Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration |
| title_short | Surprisingly robust violations of stochastic dominance despite splitting training: A quasi-adversarial collaboration |
| title_sort | surprisingly robust violations of stochastic dominance despite splitting training a quasi adversarial collaboration |
| topic | stochastic dominance splitting training dominance training |
| url | https://www.cambridge.org/core/product/identifier/S1930297524000408/type/journal_article |
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