2023
DOI: 10.1007/s40271-023-00625-y
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Taking the Shortcut: Simplifying Heuristics in Discrete Choice Experiments

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Cited by 14 publications
(4 citation statements)
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“…A 2-class latent class model was used where Class 1 is used to represent the utility maximising data generation process and Class 2 predicts service mode by restricting all attributes to be zero except for service mode. 26 In Class 2, the coefficient of face-to-face is 6.264 ( P <0.01), so we thought it may be the dominant decision-making behaviour.…”
Section: Resultsmentioning
confidence: 82%
“…A 2-class latent class model was used where Class 1 is used to represent the utility maximising data generation process and Class 2 predicts service mode by restricting all attributes to be zero except for service mode. 26 In Class 2, the coefficient of face-to-face is 6.264 ( P <0.01), so we thought it may be the dominant decision-making behaviour.…”
Section: Resultsmentioning
confidence: 82%
“…In addition, to evaluate the robustness of the original latent class results, a further latent class model was estimated with an additional class that constrained all attributes to zero. This model was used to examine task non-attendance with the assumption that there is a group of respondents who are inattentive to all the attributes presented in the task [ 16 , 17 ].…”
Section: Methodsmentioning
confidence: 99%
“…Printed copies of six choice tasks were provided, and contributors completed them in the presence of two researchers, one of whom took notes. The order of the choice tasks was designed to progressively increase in complexity to determine the point at which respondents experienced fatigue or resorted to the use of simplifying heuristics i.e., decision-making strategies which allow individuals to make choices with less cognitive effort, such as choosing to ignore some attributes (Veldwijk et al, 2023 ).…”
Section: Methodsmentioning
confidence: 99%