Eric R. Stone, Jason Luu, Cory K. Costello, Annie H. Somerville
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引用次数: 0
Abstract
In two studies, we investigated the effectiveness of an automated form of calibration training via individualized feedback as a means to improve calibration in forecasts. In Experiment 1, this training procedure was tested in a realistic forecasting situation, namely, predicting the outcome of baseball games. Experiment 2 was similar but used a more controlled forecasting task, predicting whether competitors would bust in a modified version of blackjack. In comparison to a control group without training, participants provided with calibration training had reduced confidence levels, which translated into reduced overconfidence and better overall calibration in Experiment 2. The results across both studies suggest that an automated form of individualized performance feedback can reduce the confidence of initially overconfident forecasters.
期刊介绍:
The Journal of Behavioral Decision Making is a multidisciplinary journal with a broad base of content and style. It publishes original empirical reports, critical review papers, theoretical analyses and methodological contributions. The Journal also features book, software and decision aiding technique reviews, abstracts of important articles published elsewhere and teaching suggestions. The objective of the Journal is to present and stimulate behavioral research on decision making and to provide a forum for the evaluation of complementary, contrasting and conflicting perspectives. These perspectives include psychology, management science, sociology, political science and economics. Studies of behavioral decision making in naturalistic and applied settings are encouraged.