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Abstract:
Most decisions in life are gambles. Should I speed up or slow down as I approach the yellow traffic light ahead? Should I invest in the stock market or in treasury bills? Should I undergo surgery or radiation therapy to treat my tumor? From mundane choices rendered with scarcely a moment's reflection to urgent decisions founded on careful deliberation, we seldom know in advance and with certainty what the consequences of our choices will be. Thus, most decisions require not only an assessment of the attractiveness of potential consequences, but also some appraisal of their likelihood of occurrence. Virtually all decision theorists agree that values and beliefs jointly influence willingness to act under uncertainty. However, there is considerable disagreement about how to measure values and beliefs, and howto model their influence on decisions. Our purpose in this chapter is to bring into sharper focus the role of values and beliefs in decision under uncertainty and contrast some recent developments in the descriptive modeling of choice under uncertainty with the classical normative model.

risk, uncertainty, expected utility, prospect theory, ambiguity, judged probability, decision theory

Abstract:
This paper describes a decision analysis methodology to evaluate academic programs. It avoids the shortcomings of the well-known evaluations of universities and academic programs produced by the public media. In addition to evaluating traditional departments and schools, the methodology is designed to evaluate interdisciplinary programs or fields that typically span many areas of a university, such as operations research, risk analysis, and decision science. We first discuss general principles of using this methodology for the evaluation of disciplinary or interdisciplinary academic programs. Next, we apply this methodology to interdisciplinary graduate decision science programs in United States universities, focusing on both prescriptive decision analysis and descriptive decision research. Finally, we suggest how the methodology might be implemented to evaluate operations research programs.

academic program evaluation, academic rankings, decision analysis, education systems, operations

Abstract:
In 3 studies, participants viewed sequences of multiattribute objects (e.g., colored shapes) appearing with varying frequencies and judged the likelihood of the attributes of those objects. Judged probabilities reflected a compromise between (a) the frequency with which each attribute appeared and (b) the ignorance prior probability cued by the number of distinct values that the focal attribute could take on. Thus, judged probabilities were partition dependent, varying with the number of events into which the state space was subjectively divided. This bias was diminished among participants more confident in what they learned, was strong and insensitive to level of confidence when ignorance priors were especially salient, and required ignorance priors to be salient only when probabilities were elicited (not during encoding).

judgment, uncertainty, probability, learning, decision making

Abstract:
Many decisions made by authorities pose uncertain consequences for the individuals affected by them, yet people must determine the extent to which they will support the change. Integrating the social justice and behavioral decision theory literatures, the article argues that individuals determine their support for proposed initiatives by assessing how knowledgeable they feel and using 2 main sources of information more or less heavily: their prediction of how the outcome of the initiative is likely to affect them or the perceived fairness of the decision maker. Three studies (2 experiments, 1 longitudinal field survey) assessing support for proposed public policies reveal that when individuals feel very knowledgeable they rely more on their prediction of how the outcome will affect them, whereas when they feel less knowledgeable they rely more on an overall impression of procedural fairness. The theoretical account and findings shed interdisciplinary insights into how people use process and outcome cues in reacting to decisions under uncertainty and ambiguity.

justice-fairness, decision making, uncertainty-ambiguity, policy-political, behavioral, environment