We develop a belief-based account of decision under uncertainty. This model predicts decisions under uncertainty from (i) judgments of probability, which are assumed to satisfy support theory; and (ii) decisions under risk, which are assumed to satisfy prospect theory. In two experiments,...

The competitive survival of many organizations depends on delivering projects on time and on budget. These firms face decisions concerning how to scale the size of work teams. Larger teams can usually complete tasks more quickly, but the advantages associated with adding workers are often...

Decision and risk analysts have considerable discretion in designing procedures for eliciting subjective probabilities. One of the most popular approaches is to specify a particular set of exclusive and exhaustive events for which the assessor provides such judgments. We show that assessed...

The additive conjoint measurement model is applied to the study of decision making under certainty and risk. A data matrix is called additive if it is possible to rescale its cell entries such that their order is preserved and that every rescaled entry can be expressed as a sum of its row and...