MODELLING DECISION MAKING USING IMMEDIATE PROBABILITIES

Abstract

Abstract In this paper we provide a model of how a decision maker incorporates payoffs, event probabilities, and his level of optimism to select an alternative. We present a new decision making method that combines decision making under uncertainty with decision making under risk. We introduce a new concept of immediate probabilities for use by decision makers in selecting alternatives. We discuss the role of the decision maker's level of optimism in transforming probabilities into immediate probabilities to be used for a decision. We show how the Ordered Weighted Averaging (OWA) operators play a central role in this modification. We also provide a procedure to learn OWA structures and the decision maker's level of confidence from previous decisions and we show how this information can be used for new decisions. INDEX TERMS: Uncertaintydecision makingriskordered weighted averagingprobabilityimmediate probability Additional informationNotes on contributorsKURT J. ENGEMANN Kurt J. Engemann (Ph.D., New York University, Operations Research) is Chairman and Professor of Management Science and Systems at the Hagan School of Business at lona College. Dr. Engemann's main areas of teaching interest are computer based decision modeling, simulation, data analysis, optimization, and information systems. He actively consults, presents executive seminars, and speaks at professional conferences. His research includes publications in modeling decision making and risk management.