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Modeling attitude to risk in human decision processes: An application of fuzzy measures

机译：在人类决策过程中对风险的态度建模：模糊度量的应用

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Several models of the human decision process have been proposed, classical examples of which are utility theory and prospect theory. In recent times, the theory of fuzzy measures and integrals has emerged as an alternative meriting further investigation. Specifically, one is interested in the degrees of disjunction and conjunction and the veto and favor indices that represent the tolerance measure of the decision maker. Though several theoretical expositions have appeared in contemporary literature, empirical studies applying these concepts to the real world are scarce. This paper reports two studies based on a model of strategic telecommunication investment decisions from a research work involving a survey of executives. The first study involves building fuzzy models corresponding to each individual decision maker with the results grouped based on the decision makers' propensity to risk as determined by their degrees of disjunction. The Shapley indices and the interaction effects are determined for each pooled data set corresponding to each group. To contrast this approach with those of conventional nomothetic comparisons of decision policies, the decision makers are grouped based on a clustering analysis of the individual linear regression models. The data for each cluster are pooled and the fuzzy measures learned from the data set are analyzed for comparison purposes. The results not only serve as a demonstration of fuzzy measure analysis as a viable approach to studying qualitative decision making, but also provide useful methodological insights into applying fuzzy measures to strategic investment decisions under risk.
机译：已经提出了几种人类决策过程的模型，其中经典的例子是效用理论和预期理论。近年来，模糊测度和积分理论作为一种替代方法值得进一步研究。具体来说，人们对分离与合的程度以及代表决策者的容忍度的否决和偏爱指数感兴趣。尽管当代文学中出现了几种理论上的论述，但将这些概念应用于现实世界的实证研究却很少。本文基于一项涉及高管调查的研究工作，基于战略电信投资决策模型报告了两项研究。第一项研究涉及建立与每个决策者相对应的模糊模型，并根据决策者的分离程度确定其对风险的倾向，将结果分组。确定与每个组相对应的每个合并数据集的Shapley索引和交互作用。为了将这种方法与决策策略的传统常规方法进行比较，决策者基于单个线性回归模型的聚类分析进行分组。汇总每个聚类的数据，并分析从数据集中学习的模糊测度，以进行比较。结果不仅证明了模糊度量分析是研究定性决策的一种可行方法，而且还为将模糊度量应用于风险下的战略投资决策提供了有用的方法学见解。

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