FUZZY UNCERTAINTY IN IMPERFECT COMPETITION

A prototype decision support system (DSS) that directly addresses the nonstochastic uncertainties of an oligopolistic environment is describ ed. The DSS evaluates price and advertising decisions in the light of imperfect judgmental knowledge about the price and advertising decisio ns of competitors in an oligopolistic environment. Traditional econome tric forecasting methods used to develop the existing system are maint ained, but the theory of fuzzy sets equips the models with direct asse ssment 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 refle cted directly in the output of the enhanced DSS. Using Zadeh's ''exten sion principle'' and the alpha-level sets representation of fuzzy sets , a practical implementation of the decision support system is achieve d and exercised for the purpose of describing the benefits of sensitiv ity analysis.