DS-631
Decision Analysis
Decision Analysis
DS631 entails studying analytic techniques for rational decision-making that address uncertainty, conflicting objectives, and risk attitudes. Topics covered in the course include:
Learning rational decision-making principles.
Structuring decision models.
Capturing uncertainty.
Conducting sensitivity analysis and simulation.
We also examine objective hierarchies and networks, practice incorporating risk attitudes into our analyses, and study the value of information.
One of the vital objectives of this course is to present decision problems using various graphic tools, such as influence diagrams and decision trees. Students also practice interpreting analysis results and obtaining business insights. In the end, students will choose a decision topic in business contexts and demonstrate their skills and knowledge of applying these tools and techniques learned through the course in their project sites.
The website collects past student project sites and serves as a portal for students to refer to their past work and learned skills. It also offers a glimpse for future students of what to expect in the class.
I am an assistant professor of Decision Science in the College of Business at the University of Michigan-Dearborn. Before returning to academia, I worked in the supply chain management field for more than a decade. The experience guided my research and teaching interests. My current research area focuses on operational strategies that could influence firms’ environmental performance and sustainability, such as operational transparency and information dissemination. I enjoy teaching quantitative courses that require radical and philosophical thinking, like DS631.