Order Effects in Sequential Judgments and Decisions

Wang, Zheng; Busemeyer, Jerome R.

doi:10.1002/9781118865064.ch18

Cited by 1 publication

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“…For example, similar models have been used to address "irrational" probability judgment errors, such as disjunction and conjunction fallacies (Busemeyer et al, 2011;Busemeyer, Z. Wang, Pothos, & Trueblood, 2015) and asymmetric similarity judgments Pothos & Trueblood, 2014), attitude judgments (White, Pothos, & Busemeyer, 2014), as well as order effects on sequential judgments and decisions (Z. , 2016Z. Wang, Solloway, Shiffrin, & Busemeyer, 2014) and inferences .…”

Section: Broader Perspectivesmentioning

confidence: 99%

Interference effects of categorization on decision making

Wang

Busemeyer

2016

Cognition

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Many decision making tasks in life involve a categorization process, but the effects of categorization on subsequent decision making has rarely been studied. This issue was explored in three experiments (N=721), in which participants were shown a face stimulus on each trial and performed variations of categorization-decision tasks. On C-D trials, they categorized the stimulus and then made an action decision; on X-D trials, they were told the category and then made an action decision; on D-alone trials, they only made an action decision. An interference effect emerged in some of the conditions, such that the probability of an action on the D-alone trials (i.e., when there was no explicit categorization before the decision) differed from the total probability of the same action on the C-D or X-D trials (i.e., when there was explicit categorization before the decision). Interference effects are important because they indicate a violation of the classical law of total probability, which is assumed by many cognitive models. Across all three experiments, a complex pattern of interference effects systematically occurred for different types of stimuli and for different types of categorization-decision tasks. These interference effects present a challenge for traditional cognitive models, such as Markov and signal detection models, but a quantum cognition model, called the belief-action entanglement (BAE) model, predicted that these results could occur. The BAE model employs the quantum principles of superposition and entanglement to explain the psychological mechanisms underlying the puzzling interference effects. The model can be applied to many important and practical categorization-decision situations in life.

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