From recognition to decisions: Extending and testing recognition-based models for multialternative inference
Détails
ID Serval
serval:BIB_BA8BFAFDC0B1
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
From recognition to decisions: Extending and testing recognition-based models for multialternative inference
Périodique
Psychonomic Bulletin & Review
ISSN
1069-9384
Statut éditorial
Publié
Date de publication
06/2010
Peer-reviewed
Oui
Volume
17
Numéro
3
Pages
287-309
Langue
anglais
Résumé
The recognition heuristic is a noncompensatory strategy for inferring which of two alternatives, one recognized and the other not, scores higher on a criterion. According to it, such inferences are based solely on recognition. We generalize this heuristic to tasks with multiple alternatives, proposing a model of how people identify the consideration sets from which they make their final decisions. In doing so, we address concerns about the heuristic's adequacy as a model of behavior: Past experiments have led several authors to conclude that there is no evidence for a noncompensatory use of recognition but clear evidence that recognition is integrated with other information. Surprisingly, however, in no study was this competing hypothesis-the compensatory integration of recognition-formally specified as a computational model. In four studies, we specify five competing models, conducting eight model comparisons. In these model comparisons, the recognition heuristic emerges as the best predictor of people's inferences.
Web of science
Open Access
Oui
Création de la notice
14/10/2011 12:06
Dernière modification de la notice
20/08/2019 15:28