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390020 DK PhD-M: Management Decision Making (2018W)
Continuous assessment of course work
Labels
Registration/Deregistration
Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).
- Registration is open from Mo 10.09.2018 09:00 to Th 20.09.2018 12:00
- Deregistration possible until Mo 15.10.2018 23:59
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Monday 14.01. 09:45 - 11:45 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 14.01. 12:45 - 14:45 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Wednesday 16.01. 09:45 - 11:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Wednesday 16.01. 13:15 - 15:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Friday 18.01. 09:45 - 11:45 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Friday 18.01. 13:15 - 15:15 Seminarraum 15 Oskar-Morgenstern-Platz 1 3.Stock
- Monday 21.01. 09:45 - 11:45 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Monday 21.01. 12:45 - 14:45 Seminarraum 13 Oskar-Morgenstern-Platz 1 2.Stock
- Wednesday 23.01. 09:45 - 11:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Wednesday 23.01. 12:45 - 14:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Friday 25.01. 09:45 - 11:45 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Friday 25.01. 13:15 - 15:15 Seminarraum 16 Oskar-Morgenstern-Platz 1 3.Stock
- Wednesday 20.02. 15:00 - 16:30 Seminarraum 4 Oskar-Morgenstern-Platz 1 1.Stock
Information
Aims, contents and method of the course
Assessment and permitted materials
Classroom work and exercises (20%)
Final exam (50%)
Research project or survey paper (based on student's choice) (30%)
Final exam (50%)
Research project or survey paper (based on student's choice) (30%)
Minimum requirements and assessment criteria
This course gives an in-depth coverage of main methods for supporting managemement decisions, allowing the students to develop a good understanding of the axiomatic foundations of decision theory and the implications that these foundations have for the validity of decision modelling. It also presents real-life examples on the development of decision models and equips the students with skills that are needed to choose and apply appropriate methods in their own work.
Examination topics
The course material consists of lectures notes and accompanying reading materials which will be made available to the students before class. The students are encouraged to read these materials before class so that sufficient time in the classroom can be devoted to instructive discussions.
Reading list
Lecture notes containing references will be available on Moodle
Association in the course directory
Last modified: Mo 07.09.2020 15:46
1. Decisions under uncertainty (probability elicitation, decision trees, expected utility theory, stochastic dominance, risk preferences, risk measures)
2. Decisions with multiple objectives (multi-attribute utility theory, multi-attribute value theory, analytic hierarchy process, outranking methods)
3. Decisions under incomplete information (dominance concepts, sensitivity analysis)
4. Group decision making (voting procedures, aggregation of utilities)
5. Multi-objective optimization
6. Efficiency and productivity analysis
7. Scenario analysis