2022
DOI: 10.31234/osf.io/hj8dg
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Attentional Dynamics Explain the Elusive Nature of Context Effects

Abstract: Context effects in multi-alternative, multi-attribute choice are pervasive and yet, paradoxically, elusive at the same time. For example, simple changes to the spatial layout of alternatives on the screen can nullify or reverse the effects. Despite the success of dynamic decision models in explaining the occurrence of context effects, a coherent theory for understanding their elusiveness is currently lacking. We introduce a novel theoretical framework that relies on attention modulated comparisons to explain t… Show more

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Cited by 4 publications
(7 citation statements)
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“…For instance, when the target and the decoy are presented beside each other on the information display, the attraction effect is strengthened (Evans, Holmes, Dasari, & Trueblood, 2021;Hasan, Liu, Owens, & Trueblood, 2023). Computational modeling has revealed that this might be accounted for by additional comparisons between neighboring options (Trueblood et al, 2022). Thus while visual factors might impact the comparative process, it seems to be independent of bottom-up salience.…”
Section: Discussionmentioning
confidence: 99%
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“…For instance, when the target and the decoy are presented beside each other on the information display, the attraction effect is strengthened (Evans, Holmes, Dasari, & Trueblood, 2021;Hasan, Liu, Owens, & Trueblood, 2023). Computational modeling has revealed that this might be accounted for by additional comparisons between neighboring options (Trueblood et al, 2022). Thus while visual factors might impact the comparative process, it seems to be independent of bottom-up salience.…”
Section: Discussionmentioning
confidence: 99%
“…We used a sequential sampling model framework, called the comparison sampling framework, to model the decisionmaking process in our task (Trueblood et al, 2022). As shown in Figure 4, this framework delineates a preference accumulation process and an attentional process, making it suitable for modeling our hypotheses.…”
Section: Modeling Methodsmentioning
confidence: 99%
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