Decision making process: typology, intelligence, and optimization

  • Authors:
  • Behnam Malakooti

  • Affiliations:
  • Systems Engineering, Electrical Engineering and Computer Science Department, Case Western Reserve University, Cleveland, USA 44106

  • Venue:
  • Journal of Intelligent Manufacturing
  • Year:
  • 2012

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Abstract

Decision making is concerned with evaluating and/or ranking possible alternatives of action. In this paper, we develop a model for the process of decision making. Understanding the decision process can provide insights into how humans make decisions, understand their decision making approaches, and how they differ from each other. We believe that decision makers who are conscious of their decision process types can make more effective and balanced decisions. In this paper, we present a new decision process model based on the following four dimensions where each dimension is defined by two opposing types: Information Processing (Concrete and Abstract), Alternative Generation (Adaptive and Constructive), Alternative Evaluation (Moderate and Bold), and Decision Closure (Organized and Flexible). Furthermore, an approach for assessing each of the four decision process types by a mathematical function is presented. In a much boarder scope than decision making, these assessed functions can be used to evaluate and rank alternatives. The decision process model can also be used in conjunction with multiple criteria decision making and multiple objective optimization. The model can also be used to explain the reasons that the classical decision making models fail to describe real decision makers' behavior, and mistakenly label such behavior as irrational. The proposed decision process model can be used for developing new behavioral, rational, and intelligent decision making theories and approaches. Extensions of this work may include group decision making, organizational decision making, team formation, and risk behavior analysis. Experimental results of over four hundred engineering students are reported. A web site has been developed for users ( http://car.cwru.edu/decision/ ).