Modelling decision making under risk and uncertainty by novel utility measures

被引：0
作者：
Industrial Engineering Department, Jordan University of Science and Technology, Jordan, Jordan [1 ]
机构：
[1] Industrial Engineering Department, Jordan University of Science and Technology, Jordan
来源：
Int. J. Appl. Decis. Sci. | / 2卷 / 179-202期
关键词：
Decision making; Decision science; Logistic regression; Uncertainty; Utility theory;
D O I：
10.1504/IJADS.2015.069608
中图分类号：
学科分类号：
摘要：
In this paper, we will address the classical decision theories (the expected value, EV, and expected utility theories, EUTs) along with their violations, such as the common consequence, common ratio effect, violation of betweenness and the fourfold risk pattern. In particular, a numerical method is proposed to determine the utility function of an individual or group of individuals. The approach depends on the individual's evaluation of the certainty equivalent (CE) of a decision problem under uncertainty. Later, we propose an optimisation model to predict human preference between pairs of reward scenarios in which uncertainty is involved. The optimisation model implements binary logistic regression (BLR). Both SPSS and Excel Solver were used in the optimisation and parameter fitting. The presented model is verified via collected survey and literature studies. It is found that the model is able to explain the violations and serve as a new replica to predict human preferences. Copyright © 2015 Inderscience Enterprises Ltd.
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页码：179 / 202
页数：23
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