title: Predicting affective choice.
abstract: Affect is increasingly recognized as central to decision making. However, it is not clear whether affect can be used to predict choice. To address this issue, we conducted 4 studies designed to create and test a model that could predict choice from affect. In Study 1, we used an image rating task to develop a model that predicted approach-avoidance motivations. This model quantified the role of two basic dimensions of affect--valence and arousal--in determining choice. We then tested the predictive power of this model for two types of decisions involving images: preference based selections (Study 2) and risk-reward trade-offs (Study 3). In both cases, the model derived in Study 1 predicted choice and outperformed competing models drawn from well-established theoretical views. Finally, we showed that this model has ecological validity: It predicted choices between news articles on the basis of headlines (Study 4). These findings have implications for diverse fields, including neuroeconomics and judgment and decision making.
authors.affiliation: Department of Psychology, Stanford University, 450 Serra Mall, Stanford, CA 94305, USA. rsuri@stanford.edu
authors.forename: Gaurav
authors.initials: G
authors.lastname: Suri
authors.forename: Gal
authors.initials: G
authors.lastname: Sheppes
authors.forename: James J
authors.initials: JJ
authors.lastname: Gross
mesh_terms: D000328:Adult; D000339:Affect / Q000502:physiology*; D001143:Arousal / Q000502:physiology; D002755:Choice Behavior / Q000502:physiology*; D005260:Female; D006801:Humans; D008297:Male; D008960:Models, Psychological