Universität Wien

390028 DK PhD-M: Management Decision Making (2022S)

Continuous assessment of course work

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

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).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

EXAM: MO 27.06.2022 15.00-16.30 SR 3 Oskar-Morgenstern-Platz 1 2nd floor

  • Monday 07.03. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock (Kickoff Class)
  • Thursday 10.03. 09:45 - 11:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 14.03. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 17.03. 09:45 - 11:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 21.03. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Thursday 24.03. 09:45 - 11:15 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 28.03. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 02.05. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 09.05. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 16.05. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 23.05. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 30.05. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 20.06. 15:00 - 16:30 Seminarraum 3 Oskar-Morgenstern-Platz 1 1.Stock
  • Monday 27.06. 15:00 - 16:30 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%)
Note: The mode of the final exam (presence or online) will be decided on short notice, depending on the COVID situation
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. 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: Tu 21.06.2022 16:50