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Information is a fundamental asset in any organization and as such is assigned a value reflecting its importance. We define information to be valuable if it either confirms the choice that a decision maker (DM) would make based on the information acquired on a given alternative or prevents him from making a regrettable choice, or both. We introduce a novel information acquisition algorithm where the value of information is used as a verification and regret-prevention mechanism determining the behavior of the DM. The proposed algorithm shows how the incentives of the DM to continue acquiring information on a given alternative are determined by his attitude toward regret and the relative spread exhibited by the domains on which the characteristics of the alternative are defined. Moreover, our model proves the existence of relative spread scenarios where indecision arises, leading the DM to behave randomly. The generality and flexibility of the model allows to easily develop extensions and applications to decision theory, psychology, economics and operational research. [ABSTRACT FROM AUTHOR]

Highlights: [•] We propose a formal approach for transforming uncertainty into risk. [•] The proposed approach considers information revelation processes. [•] A class of revelation processes is introduced. [•] Probabilistic predictions are formulated within a given confidence range. [Copyright &y& Elsevier]

We consider the problem of a decision maker (DM) who must choose among a set of alternatives offered by different information senders (ISs). Each alternative is characterized by finitely many characteristics. We assume that the DM and the ISs have their own perception of the available alternatives. These perceptions are reflected by the evaluations provided for the characteristics of the alternatives and the order of importance assigned to the characteristics. Due to these subjective components, the DM may not envision the exact alternative that an IS describes, even when a complete description of the alternative is provided. These subjective biases are common in the literature analyzing the effect of framing on the behavior of the DMs. This paper provides a normative setting illustrating how the DMs should consider these differences in perception when interacting with other DMs. We design an evaluation criterion that allows the DM to generate a reliability ranking on the set of ISs and, hence, to quantify the likelihood of choosing any alternative. This ranking is based on the existing differences between the preference order of the DM and those of the ISs. Our results constitute a novel approach to choice and search under uncertainty that enhances the findings of the expected utility literature. We provide several examples to demonstrate the applicability of the method proposed and exhibit the efficacy of the ranking criterion designed. [ABSTRACT FROM AUTHOR]