Modern organizations rely extensively on computer based mathematical models designed to solve various statistical, optimization, and decision making problems, or to enhance the quality of the decisions made by humans. These models do not exist in isolation, but form complex relationships with each other resulting in organizational model bases. Large model bases require extensive structuring and organization to reduce complexity. Abstraction and decomposition are the two major tools of organization, and are shown to be the basis of macro and micro structure respectively. Both abstraction and decomposition are studied within a framework of model definition based on data models and constraints.
Index Terms:
decision support systems; business data processing; optimisation; mathematics computing; statistical analysis; decision models; structural analysis; organizations; computer based mathematical models; statistical problems; optimization problems; decision making problems; organizational model bases; complexity; micro structure; macro structure; abstraction; decomposition; data models; constraints
Citation:
L.V. Orman, "Structural analysis of decision models," hicss, pp.408, 28th Hawaii International Conference on System Sciences (HICSS'95), 1995