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Chapter 12Analyzing SemistructuredDecision Support Systems.ppt

Chapter 12Analyzing SemistructuredDecision Support Systems.ppt

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Chapter 12Analyzing SemistructuredDecision Support Systems.ppt

Chapter 12 Analyzing Semistructured Decision Support Systems Systems Analysis and Design Kendall and Kendall Fifth Edition Major Topics Decision support systems Decision-making style Analytic and heuristic decision making Intelligence, choice, and design Semistructured decisions Decision support system methods Decision Support Systems Decision support systems are a class of information systems that emphasize the process of decision making and changing users through their interaction with the system Decision support systems are well suited for addressing semistructured problems where human judgment is still desired or required Decision Support Systems Decision support systems function to Organize information for decision situations Interact with decision makers Expand the decision makers horizons Present information for decision-maker understanding Add structure to decisions Use multiple-criteria decision-making models Decision Support System Users Decision support systems support the decision-making process by helping the user explore and analyze alternatives through different modeling techniques Decision Making Under Risk Decisions are made under three’ sets of conditions: Certainty The decision makers know everything in advance of making the decision Uncertainty The decision makers know nothing about the probabilities or the consequences of decisions Risk Decision-Making Style Decision-making styles of users are categorized as either Analytic or Heuristic Analytic Decision Making Relies on information that is systematically acquired and systematically evaluated to narrow alternatives and make a choice Use methodical, step-by-step procedures to make decisions Value quantitative information and the models that generate and use it Analytic Decision Making Use mathematics to model problems and algorithms to solve them They seek optimal rather than completely satisfying solutions They use decision techniques such as graphing, probability models, and mathematical t

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