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Decision heuristics as predictors of public choice
Author(s) -
Wang X. T.
Publication year - 2008
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.577
Subject(s) - heuristics , voting , affect (linguistics) , psychology , contempt , normative , social heuristics , social psychology , heuristic , cognition , cognitive psychology , computer science , artificial intelligence , political science , communication , social change , politics , social competence , law , operating system , neuroscience
Two studies examined cognitive and affect‐based heuristics as predictors of public choice. Participants, recruited before the 2004 Presidential Election, identified the issues that would determine their voting decision and provided ratings of importance and Likelihood of Success for these issues (decision cues) regarding each presidential candidate. Both well‐known and new heuristics were evaluated for descriptive fit between predicted and actual voting choices and overall predictive accuracy regarding who the winner of the sample would be. In Study 1, the performance of cue‐weight free simple heuristics, particularly those based on frequency counts, matched or outperformed that of normative Franklin's rule that used both cue values and cue weights. In Study 2, the affect (admiration and contempt)‐based heuristics performed even better. The Take‐The‐Best Emotion heuristic performed as well as the affect heuristics utilizing multiple social emotions. These findings highlight the utility of event frequency‐based and interpersonal affect‐based heuristics in predicting public choice under uncertainty. Copyright © 2007 John Wiley & Sons, Ltd.

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