PORTFOLIO MODELING IN MULTIPLE-CRITERIA SITUATIONS UNDER UNCERTAINTY

There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse. The method involves the use of a time-based decision tree structure called a “project tree.” Using this basic format, an illustrative six-project example is presented and analyzed. Various forms of objectives are discussed, ranging from the maximization of expected portfolio value to the maximization of the minimum weighted portfolio deviation from two goals. In each case, formulated numerical problems are given, and the solutions derived are presented. The approach is shown to be very flexible and capable of handling a variety of situations and objectives.     

SUBJECTIVE EVALUATIONS FOR PRODUCT DESIGN DECISIONS

This paper presents a simple methodology to enable a firm to incorporate consumers' subjective evaluations early into the concept screening stage of a new product introduction process. The methodology involves eliciting ranked preference judgments toward a set of alternative product concepts, each described as a profile of attributes and derived from an interval-scaled utility score using Thurstone's comparative judgment model. The derived utility scores are then decomposed into simple effects attributable to each of the attributes, thus yielding functional representations of consumer preferences. Mathematical models are developed to utilize the functions to determine the best concept. Empirical illustrations are provided for application of the methodology.