Decision Support Systems

Almost 30 years ago, Mintzberg et al. (1976) proposed a general model for the decision-making process. The Mintzberg model has stood the test of time; it is still widely accepted today as a general description of the multiple alternative processes and pathways, including feedback loops, that individuals and organizations use to get from problem recognition to problem resolution, which culminates in some course of action. Any software system that explicitly assists with the implementation of one or more components of the overall process can be described as a decision support system (DSS). Holsapple (2003, p. 551) nicely captures the essential features of a DSS as:

A computer-based system composed of a language system, presentation system, knowledge system, and problem-processing system whose collective purpose is the support of decision-making activities.

Two key attributes in the Holsapple definition are a subsystem for processing problems and purposeful support of a decision-making process. Many DSS focus exclusively, or nearly so, on the alternative-selection phase of the overall process. Some examples of systems that conform to the Mintzberg and Holsapple definitions and that usually focus on the alternative-selection phase include optimization systems, expert (or knowledge-based) systems that provide a framework for applying procedural or reasoning knowledge to decision problems, neural networks, Bayesian belief networks, and multi-criteria decision models (MCDM) that implement the Analytic Hierarchy Process (AHP) and similar MCDM methods.



Source Of Description

Reynolds, K.M., and D.L. Schmoldt. 2006. Computer-aided decision making. Pages 143-169 in Shao, G. and Reynolds, K.M., eds. Computer applications in sustainable forest management. New York: Springer.

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