Knowledge that Transforms

A four-attribute health state classification system designed to uniquely categorize the health status of all individuals two years of age and over is presented. A social preference function defined over the health state classification system is required. Standard multi-attribute utility theory is investigated for the task, problems are identified and modifications to the standard method are proposed. The modified method is field tested in a survey research project involving 112 home interviews. Results are presented and discussed in detail for both the social preference function and the performance of the modified method. A recommended social preference function is presented, complete with a range of uncertainty. The modified method is found to be applicable to the task—no insurmountable difficulties are encountered. Recommendations are presented, based on our experience, for other investigators who may be interested in reapplying the method in other studies.

Evidence exists that people do not always make decisions involving uncertain monetary rewards as if they were maximizing expected utility of final assets. Explanations for this behavior postulate that the cognitive demands of consistency to such a theory are too great. However, situations exist in which more than mental shortcuts are involved and these anomalies raise questions about expected utility theory as a guide to behavior. This paper explores the possibility that expected utility theory appears to fail because the single outcome descriptor—money—is not sufficient. After making a decision under uncertainty, a person may discover, on learning the relevant outcomes, that another alternative would have been preferable. This knowledge may impart a sense of loss, or regret. The decision maker who is prepared to tradeoff financial return in order to avoid regret will exhibit some of the behavioral paradoxes of decision theory. By explicitly incorporating regret, expected utility theory not only becomes a better descriptive predictor but also may become a more convincing guide for prescribing behavior to decision makers.

A general approach to testing for initialization bias in the mean of a simulation output series is presented. The output is transformed into a standardized test sequence that can be contrasted with a known limiting stochastic process. This transformation requires very little computation and the asymptotic theory is applicable to a wide variety of simulations. An initialization bias test is developed and several examples of its application are presented.

This paper reviews the relevant literature on the problem of determining suitable ordering policies for both fixed life perishable inventory, and inventory subject to continuous exponential decay. We consider both deterministic and stochastic demand for single and multiple products. Both optimal and sub-optimal order policies are discussed. In addition, a brief review of the application of these models to blood bank management is included. The review concludes with a discussion of some of the interesting open research questions in the area.