Universität Wien FIND

390020 DK PhD-M: Management Decision Making (2019W)

Continuous assessment of course work

service email address: opim.bda@univie.ac.at

Registration/Deregistration

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Monday 14.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 21.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 28.10. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 04.11. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 11.11. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 02.12. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 09.12. 15:00 - 18:15 Seminarraum 5 Oskar-Morgenstern-Platz 1 1.Stock
Monday 16.12. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 13.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 20.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
Monday 27.01. 16:45 - 18:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock

Information

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 modules

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 Decisions under incomplete information and sensitivity analysis

Assessment and permitted materials

Classroom work and exercises (20%)
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 07.10.2019 17:09