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Integrating Cognitive Process and Descriptive Models of Attitudes and Preferences
journal contributionposted on 2023-05-18, 08:14 authored by Hawkins, GE, Marley, AAJ, Heathcote, A, Flynn, TN, Louviere, JL, Brown, SD
Discrete choice experiments—selecting the best and/or worst from a set of options—are increasingly used to provide more efficient and valid measurement of attitudes or preferences than conventional methods such as Likert scales. Discrete choice data have traditionally been analyzed with random utility models that have good measurement properties but provide limited insight into cognitive processes. We extend a well-established cognitive model, which has successfully explained both choices and response times for simple decision tasks, to complex, multi-attribute discrete choice data. The fits, and parameters, of the extended model for two sets of choice data (involving patient preferences for dermatology appointments, and consumer attitudes toward mobile phones) agree with those of standard choice models. The extended model also accounts for choice and response time data in a perceptual judgment task designed in a manner analogous to best–worst discrete choice experiments. We conclude that several research fields might benefit from discrete choice experiments, and that the particular accumulator-based models of decision making used in response time research can also provide process-level nstantiations for random utility models.
Publication titleCognitive Science: A Multidisciplinary Journal of Artificial Intelligence, Linguistics, Neuroscience, Philosophy and Psychology
PublisherElsevier Science Inc
Place of publication360 Park Ave South, New York, USA, Ny, 10010-1710
Rights statementCopyright 2013 Cognitive Science Society, Inc.