Curvature of the probability weighting function
Management Science
A Behavioral Choice Model When Computational Ability Matters
Applied Intelligence
The Midweight Method to Measure Attitudes Toward Risk and Ambiguity
Management Science
Extreme events and entropy: A multiple quantile utility model
International Journal of Approximate Reasoning
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Utilizing the Russian roulette problem as an exemplar, Kahneman and Tversky (1979) developed a weighting function @p to explain that the Allais Paradox arises because people behave so as to maximize overall value rather than expected utility (EU). Following the way that ''overweighting of small probabilities'' originated from the Russian roulette problem, this research measured individuals' willingness to pay (WTP) as well as their happiness for a reduction of the probability of death, and examined whether the observed figures were compatible with the nonlinearity of the weighting function. Data analysis revealed that the nonlinear properties estimated by straight measures differed from those derived from preferential choices [D. Kahneman, A. Tversky, Prospect theory: an analysis of decision under risk, Econometrica 47 (1979) 263-291] and formulated by [A. Tversky, D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty, Journal of Risk and Uncertainty 5 (1992) 297-323]. The controversies and questions to the proposed properties of the decision weight were discussed. An attempt was made to draw the research attention from which function was being maximized to whether people behave as if they were trying to maximize some generalized expectation.