390020 DK PhD-M: Management Decision Making (2017W)
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 Fr 08.09.2017 09:00 to Th 21.09.2017 12:00
- Deregistration possible until Sa 14.10.2017 23:59
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Monday
02.10.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
09.10.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
16.10.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
23.10.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
30.10.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
06.11.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
13.11.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
20.11.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
27.11.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
04.12.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
11.12.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
08.01.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
15.01.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday
22.01.
15:00 - 16:30
Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Wednesday
31.01.
15:00 - 16:30
Seminarraum 3 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 (40%)
Research project or survey paper (at the student's choice) (40%)
Final exam (40%)
Research project or survey paper (at the student's choice) (40%)
Minimum requirements and assessment criteria
As a PhD course, this course goes beyond a practical knowledge of methods of decision analysis. Students should be able to understand the inherent logic of models of decision analysis and their relation to fundamental assumptions about rationality as well as the inherent limitations implied by these assumptions. This should enable students to select and apply the appropriate methods for their own research work.
Examination topics
The course uses a blend of e-learning based self instruction and classroom teaching. Teaching notes and training material are provided in advance on the e-learning platform, students are expected to study this material before class. Classroom lectures and discussions will be used to strengthen the students' understanding of the material.
Reading list
Lecture notes containing references will be available on Moodle
Association in the course directory
Last modified: Mo 07.09.2020 15:46
2 Multidimensional evaluation Dominance and efficiency
3 Decisions under risk: Introduction to expected utility theory
4 Applications and extensions to expected utility theory
5 Dynamic decision problems and the value of information
6 Multicriteria decisions: Additive models
7 Decisions under incomplete information and sensitivity analysis