ÖH WU > Service > Aktuelle Studien-Infos > Decision Sciences: Game Theory, Psychology & Data Analysis
Aktuelle Studien-Infos

Decision Sciences: Game Theory, Psychology & Data Analysis

Spezialisierung: BW, IBW, WINF, WiRe, BBE                 Komplementärfach: VWL, WUPol

Duration: minimum 1 semester, 2 semesters recommended

Access to Specialization: CV, performance record, motivational letter

Spots per semester: 50 students

Language: English

aktualisiert am 08.02.2024
Teilen via

Description and course content

We constantly face difficult decisions, that involve strategic, psychological, and analytical components. This is especially true in the world of business and government. The SBWL “Decision Sciences” equips students with the tools necessary to make good decisions by focusing on three branches. In Game Theory, we teach students to analyze strategic interactions between agents and predict their behavior. In Business Psychology, students learn to understand basic concepts of psychology, and how these impact organizations. In Data Analysis, we equip students with the statistical methods and programming skills in R necessary to draw conclusions based on data.

These skills will prepare students directly for the job market. The main target audience are students who want to work and excel in positions with analytical and strategic roles. This includes consultants in all flavors like corporate finance (e.g., due diligence work), human resources (e.g., incentive systems), strategy consultancy (e.g., analysis of strategic market positioning), or supply chain management (process optimization and negotiation handling). It also includes corresponding roles within companies, like special assistant to management, key project managers, HR managers, data analytics specialists, risk management, forensic analysts, mergers and acquisitions, or supply chain management.

The SBWL “Decision Sciences” builds on the foundations provided in the STEOP/CBK (Grundlagen der BW/VW, Angewandte Mikorökonomik, Mathematik & Statistik) and the common BW courses (e.g., Personal, Führung, Organisation). The SBWL can provide important foundations for the study of other SBWLs (e.g., Entrepreneurship und Innovation, Unternehmensführung und Controlling, Personalmanagement, Verhaltenswissenschaftlich orientiertes Management, Data Science etc).


Access to Specialization:

First, you must register for AG “Access to Specialization: Decision Sciences: Game Theory, Psychology, and Data Analysis” in LPIS.

Afterwards fill out the application form on the website and upload your CV, performance record and motivational letter to LEARN@WU.


Structure and courses:

The SBWL Decision Sciences is completely taught in English. It comprises a set of six courses, of which you can choose five. All courses will be offered in each semester:

The following courses are compulsory, and you can visit them in the 1st half of semester

  • Empirical Data Analysis
  • Game Theory I 
  • Business Psychology I

Choose 2 out of 3 – they are offered in the 2nd half of semester

  • Game Theory II
  • Business Psychology II
  • Project/Advanced course


Bachelor thesis: 

Students who have completed the SBWL have the opportunity to write their bachelor thesis at the Institute for Markets and Strategy or the Institute for Cognition and Behavior. Further information can be found on the institutes’ websites. 



After the successful completion of the SBWL, students are familiar with different sources of empirical evidence and the appropriate methods to analyze them and can apply these in the programming language R. Students possess basic knowledge and understanding of game-theoretical tools and solution concepts. They can analyze strategic situations and the incentives of players therein. Further, students understand the underpinnings and core psychological concepts and biases involved in managerial decision-making. 


Here you can find the presentation from the Specializations fair!

Here you can find a video presentation from the Specializations fair! 

aktualisiert am 08.02.2024
Teilen via