Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition
Judgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential i...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2008-03-01
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| Series: | Judgment and Decision Making |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S1930297500002436/type/journal_article |
| _version_ | 1797701734192119808 |
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| author | Daniel Hausmann Damian Läge Arndt Bröder Ben Newell |
| author_facet | Daniel Hausmann Damian Läge Arndt Bröder Ben Newell |
| author_sort | Daniel Hausmann |
| collection | DOAJ |
| description | Judgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential information search until enough evidence has been accumulated to pass a decision threshold. In line with such theories, we conceptualize the evidence threshold as the “desired level of confidence” (DLC) of a person. This model is tested against a fixed stopping rule (one-reason decision making) and against the class of multi-attribute information integrating models. A series of experiments using an information board for horse race betting demonstrates an advantage of the proposed model by measuring the individual DLC of each subject and confirming its correctness in two separate stages. In addition to a better understanding of the stopping rule (within the narrow framework of simple heuristics), the results indicate that individual aspiration levels might be a relevant factor when modelling decision making by task analysis of statistical environments. |
| first_indexed | 2024-03-12T04:39:58Z |
| format | Article |
| id | doaj.art-634fcbf458434a40843421b29baa7e20 |
| institution | Directory Open Access Journal |
| issn | 1930-2975 |
| language | English |
| last_indexed | 2024-03-12T04:39:58Z |
| publishDate | 2008-03-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Judgment and Decision Making |
| spelling | doaj.art-634fcbf458434a40843421b29baa7e202023-09-03T09:45:43ZengCambridge University PressJudgment and Decision Making1930-29752008-03-01322924310.1017/S1930297500002436Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisitionDaniel Hausmann0Damian Läge1Arndt BröderBen NewellGeneral Psychology (Cognition), University of ZurichApplied Cognitive Psychology, University of ZurichJudgments and decisions under uncertainty are frequently linked to a prior sequential search for relevant information. In such cases, the subject has to decide when to stop the search for information. Evidence accumulation models from social and cognitive psychology assume an active and sequential information search until enough evidence has been accumulated to pass a decision threshold. In line with such theories, we conceptualize the evidence threshold as the “desired level of confidence” (DLC) of a person. This model is tested against a fixed stopping rule (one-reason decision making) and against the class of multi-attribute information integrating models. A series of experiments using an information board for horse race betting demonstrates an advantage of the proposed model by measuring the individual DLC of each subject and confirming its correctness in two separate stages. In addition to a better understanding of the stopping rule (within the narrow framework of simple heuristics), the results indicate that individual aspiration levels might be a relevant factor when modelling decision making by task analysis of statistical environments.https://www.cambridge.org/core/product/identifier/S1930297500002436/type/journal_articleevidence accumulationsequential information searchinformation acquisitionthreshold modelsstopping rulelevel of confidenceprobabilistic cuevalidityone-reason decision making |
| spellingShingle | Daniel Hausmann Damian Läge Arndt Bröder Ben Newell Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition Judgment and Decision Making evidence accumulation sequential information search information acquisition threshold models stopping rule level of confidence probabilistic cue validity one-reason decision making |
| title | Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition |
| title_full | Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition |
| title_fullStr | Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition |
| title_full_unstemmed | Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition |
| title_short | Sequential evidence accumulation in decision making: The individual desired level of confidence can explain the extent of information acquisition |
| title_sort | sequential evidence accumulation in decision making the individual desired level of confidence can explain the extent of information acquisition |
| topic | evidence accumulation sequential information search information acquisition threshold models stopping rule level of confidence probabilistic cue validity one-reason decision making |
| url | https://www.cambridge.org/core/product/identifier/S1930297500002436/type/journal_article |
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