the distortion of outcome and probability information in risky decisions or the effects of ambiguity on information … ambiguity by describing outcomes and probabilities using either point estimates or ranges of values. Results replicated those of … Study 1, with no effects of ambiguity on information distortion. …

the distortion of outcome and probability information in risky decisions or the effects of ambiguity on information …, we manipulated ambiguity by describing outcomes and probabilities using either point estimates or ranges of values …. Results replicated those of Study 1, with no effects of ambiguity on information distortion. …

with a probability distribution. Consequently, they do not allow for Knightian uncertainty, or ambiguity, with respect to … accident risk and cannot accommodate optimism (ambiguity loving) or pessimism (ambiguity aversion). This paper presents a … unilateral accident model under ambiguity. To incorporate ambiguity, I adopt the Choquet expected utility framework and represent …

We develop a theory of optimal stopping problems under ambiguity in continuous time. Using results from (backward … from the agent's ambiguity aversion. We show how to use these general results for search problems and American Options. …

We model and solve Best Choice Problems in the multiple prior framework: An ambiguity averse decision maker aims to … choose the best among a fixed number of applicants that appear sequentially in a random order. The decision faces ambiguity … stopping strategy is simple. Ambiguity can lead to substantial differences to the classical threshold rule. …

We consider optimal stopping problems for ambiguity averse decision makers with multiple priors. In general, backward …