A memory processes account of the calibration of probability judgments was examined. A multiple-trace memory model, Minerva-Decision Making (MDM; M. R. P. Dougherty, C. F. Gettys, & E. E. Ogden, 1999), used to integrate the ecological (Brunswikian) and the error (Thurstonian) models of overconfidence, is described. The model predicts that overconfidence should decrease both as a function of experience and as a function of encoding quality. Both increased experience and improved encoding quality result in lower variance in the output of the model, which in turn leads to improved calibration. Three experiments confirmed these predictions. Implications of MDM's account of overconfidence are discussed.
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http://dx.doi.org/10.1037//0096-3445.130.4.579 | DOI Listing |
PLoS One
January 2025
Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia.
Background: Online malicious attempts such as scamming continue to proliferate across the globe, aided by the ubiquitous nature of technology that makes it increasingly easy to dupe individuals. This study aimed to identify the predictors for online fraud victimization focusing on Personal, Environment and Behavior (PEB).
Methods: Social Cognitive Theory (SCT) was used as a guide in developing the PEB framework.
Behav Sci (Basel)
January 2025
School of Business, Law & Entrepreneurship, Swinburne University of Technology, Melbourne, VIC 3122, Australia.
The paper aims to examine the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making financial decisions. In doing so, the paper showcases the financial illiteracy of Australian female consumers when confronted with irregularities within the Australian financial markets. From a theoretical standpoint, the study adopts the notions of the adaptive market hypothesis (AMH) to understand the reasoning behind the relationships between behavioural biases (such as overconfidence and herding) and the rational behaviour of Australian female consumers when making decisions rationally.
View Article and Find Full Text PDFSensors (Basel)
November 2024
Intelligent Maintenance and Operations Systems, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
Intelligent fault diagnosis (IFD) based on deep learning can achieve high accuracy from raw condition monitoring signals. However, models usually perform well on the training distribution only, and experience severe performance drops when applied to a different distribution. This is also observed in fault diagnosis, where assets are often operated in working conditions different from the ones in which the labeled data have been collected.
View Article and Find Full Text PDFEntropy (Basel)
November 2024
Bayesfusion, LLC, Pittsburgh, PA 15217, USA.
There is a widely spread belief in the Bayesian network (BN) community that the overall accuracy of results of BN inference is not too sensitive to the precision of their parameters. We present the results of several experiments in which we put this belief to a test in the context of medical diagnostic models. We study the deterioration of accuracy under random symmetric noise but also biased noise that represents overconfidence and underconfidence of human experts.
View Article and Find Full Text PDFPLoS One
November 2024
Department of Industrial Management, National Taiwan University of Science and Technology, Taipei City, Taiwan.
Experts in traditional pricing literature often assume that consumers are rational in their purchasing decisions, and tend to ignore the effect of psychological behavior. One of the fundamental irrational psychological behaviors is overconfidence, which refers to overestimation. The benefits of three-part tariffs under demand uncertainty caused by overconfident consumers have been demonstrated in various forms.
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