040510 DK PhD-M: Management Decision Making (2008W)
Continuous assessment of course work
Labels
Summary
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 01.09.2008 09:00 to Su 21.09.2008 23:59
- Registration is open from Fr 26.09.2008 09:00 to Mo 29.09.2008 23:59
- Deregistration possible until Tu 14.10.2008 23:59
Registration information is available for each group.
Groups
Group 1
Will be provided via the e-learning platform
max. 15 participants
Language: English
Lecturers
Classes
Currently no class schedule is known.
Aims, contents and method of the course
Assessment and permitted materials
Classroom work and exercises (20%)
Final exam (40%)
Research project or teaching assignment (at the student's choice) (40%)
Final exam (40%)
Research project or teaching assignment (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.
Group 2
Will be provided via the e-learning platform
max. 15 participants
Language: English
Lecturers
Classes (iCal) - next class is marked with N
Wednesday
21.01.
14:00 - 17:00
Seminarraum 2
Thursday
22.01.
14:00 - 17:00
Seminarraum 1
Friday
23.01.
09:00 - 12:00
Hörsaal 11
Friday
23.01.
14:00 - 16:00
Seminarraum 1
Wednesday
28.01.
14:00 - 17:00
Seminarraum 1
Thursday
29.01.
14:00 - 17:00
Seminarraum 1
Friday
30.01.
09:00 - 12:00
Hörsaal 11
Friday
30.01.
14:00 - 16:00
Seminarraum 1
Aims, contents and method of the course
The course covers main areas of decision theory at an advanced level. It is structured into the following seven modules1 Introduction to preference modeling: Relations and scales2 Multidimensional evaluation Dominance and efficiency3 Decisions under risk: Introduction to expected utility theory4 Applications and extensions to expected utility theory5 Dynamic decision problems and the value of information6 Multicriteria decisions: additive models7 Multicriteria decisions: Non-compensatory models
Assessment and permitted materials
Classroom work and exercises (20%)Final exam (40%)Research project or teaching assignment (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.
Information
Reading list
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 Multicriteria decisions: additive models
7 Multicriteria decisions: Non-compensatory models