040510 DK PhD-M: Management Decision Making (2010S)
Continuous assessment of course work
Labels
Will be provided via the e-learning platform
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 08.02.2010 06:00 to Th 18.02.2010 16:00
- Registration is open from We 24.02.2010 13:00 to Fr 26.02.2010 16:00
- Deregistration possible until Su 14.03.2010 23:59
Details
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
- Friday 05.03. 10:00 - 12:00 Hörsaal 7
- Friday 19.03. 10:00 - 12:00 Hörsaal 7
- Friday 26.03. 10:00 - 12:00 Hörsaal 7
- Friday 16.04. 10:00 - 12:00 Hörsaal 7
- Friday 23.04. 10:00 - 12:00 Hörsaal 7
- Friday 30.04. 10:00 - 12:00 Hörsaal 7
- Friday 07.05. 10:00 - 12:00 Hörsaal 7
- Friday 14.05. 10:00 - 12:00 Hörsaal 7
- Friday 21.05. 10:00 - 12:00 Hörsaal 7
- Friday 28.05. 10:00 - 12:00 Hörsaal 7
- Friday 04.06. 10:00 - 12:00 Hörsaal 7
- Friday 11.06. 10:00 - 12:00 Hörsaal 7
- Friday 18.06. 10:00 - 12:00 Hörsaal 7
- Friday 25.06. 10:00 - 12:00 Hörsaal 7
Information
Aims, contents and method of the course
Assessment and permitted materials
Classroom work and exercises (20%)
Final exam (40%)
Term paper (40%)
Final exam (40%)
Term paper (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
Material is provided via the e-learning platform
Association in the course directory
Last modified: Mo 07.09.2020 15:29
1 Introduction to preference modeling: Relations and scales
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 Decisions with incomplete information
7 Multicriteria decisions: additive models
8 Multicriteria decisions: Non-compensatory models