Abstract
A prototype decision support system (DSS) that directly addresses the nonstochastic uncertainties of an oligopolistic environment is described. The DSS evaluates price and advertising decisions in the light of imperfect judgmental knowledge about the price and advertising decisions of competitors in an oligopolistic environment. Traditional econometric forecasting methods used to develop the existing system are maintained, but the theory of fuzzy sets equips the models with direct assessment of nonstochastic uncertainty. In addition to parameterizing the econometric equations, the decisionmaker assesses his or her level of knowledge regarding the fuzzy quantities. These assessments are reflected directly in the output of the enhanced DSS. Using Zadeh's “extension principle” and the α-level sets representation of fuzzy sets, a practical implementation of the decision support system is achieved and exercised for the purpose of describing the benefits of sensitivity analysis.
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