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Title: The variable precision method for elicitation of probability weighting functions
Authors: Chai, J
Ngai, EWT 
Issue Date: Jan-2020
Source: Decision support systems, Jan. 2020, v. 128, 113166
Abstract: This study introduces a nonparametric method to elicit decision weights under prospect theory. These weights carry the attitudes and subjective beliefs of individuals toward risks and uncertainties. Our variable precision method adopts a dynamic mechanism that can elicit the measuring points of individual probability weighting flexibly. These points are used to exhibit violations of expected utility theory, which measures individual risk attitudes and captures subjective beliefs on probabilities. Our method is flexible, tractable, and cognitively less demanding compared with other nonparametric elicitations in the literature. Experimental studies are conducted on a sample of Hong Kong (China) residents to verify our method. Our experimental results yield a prevailing inverse-S shape. We conduct the analyses and uncover their implications by comparing them with the results of residents of Beijing, Shanghai, Paris, and Amsterdam.
Keywords: Behavioral decision making
Nonparametric elicitation
Probability weighting
Prospect theory
Tradeoff method
Publisher: Elsevier
Journal: Decision support systems 
ISSN: 0167-9236
EISSN: 1873-5797
DOI: 10.1016/j.dss.2019.113166
Rights: © 2019 Elsevier Ltd. All rights reserved.
© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.
The following publication Chai, J., & Ngai, E. W. (2020). The variable precision method for elicitation of probability weighting functions. Decision Support Systems, 128, 113166 is available at https://doi.org/10.1016/j.dss.2019.113166.
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