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MBA 307 Decision Analysis (3 Credits)

Uncertainty and complexity make many decisions difficult. This course takes into account uncertainties and multiple objectives, managers need to make effective use of various types of information (past data, forecasts regarding future events, available alternatives, attitudes toward risk, tradeoffs among objectives, predictions of competitors' actions, etc.) that are available and to seek additional information (gather data, generate new alternatives, etc.) as appropriate. They also need to avoid cognitive biases.

This elective provides an introduction to decision analysis - the systematic evaluation of decision-making problems under uncertainty. Decision analysis provides a framework for analyzing these problems by breaking them down into more manageable parts. The goal of this course is to introduce some specific formal methods and, perhaps even more important, suggest a useful way of thinking about and approaching risky decisions.

The following are acceptable topics for this course:
  • Problem Structuring: decision trees, influence diagrams, sensitivity analysis.
  • Probability: probability assessment, revision, evaluating and combining forecasts.
  • Risk: decision criteria, utility theory, risk measurement and management.
  • Multiple Objectives: identifying objectives, tradeoffs, multi-attribute utility, life and death decision making.
  • Competitive Decision Making: bargaining, negotiation, integrative bargaining.
Recommended Text(s)
Representative Readings: Various articles from academic journals and other sources. Making Hard Decisions: An Introduction to Decision Analysis by Robert T. Clemen.
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