Angewandte empirische Forschung - M.Sc./PhD

General Information

  • Module: Angewandte empirische Forschung
  • Module number lecture: M.WIWI-WIN.0012
  • UniVZ: 800423
  • Cycle: Every winter term
  • Credits: 6 ECTS
  • Courses of study: PhD, Master WI, Master Ufü, Master MDM
  • Type of teaching and learning: Block course
  • Examination: Presentation and final paper
  • Lecturer: Dr. Matthias Meyer (Member of the Management Board, Blue Avenir GmbH)
  • Language: German
  • Contact:

Please check this website regularly for updates.


07.11.2022, 9:00 - 17:00 Block 1 SUB großer Seminarraum
08.11.2022, 9:00 - 17:00 Block 2 tbd
30.01.2023, 9:00-17:00 Presentation SUB großer Seminarraum
Furthermore, students will have to submit a report. The submission date for the written report will be provided during the seminar and will likely be after January 30, 2023.
01.09.2022 - 10.10.2022 Registration/enrollment period
Please register for the course via email to Registration is first-come-first-served. Maximum number of participants: 12

If you are a PhD student, you can register, too. However, you can only participate if fewer than 12 master students register until the start of the lecture.


The course discusses the practical use of empirical research methods concerning information management and business economics. This course is aimed toward students and postgraduates focusing on Business Informatics, Marketing, and Administration. Participants will be provided with the necessary tools for empirically founded work for term papers or dissertations.

At the end of the seminar, students should possess the basic knowledge and experience necessary to conduct quantitative analyses for studies or practice. Furthermore, students should understand the concept of expressing and validating propositions and analyzing collected data.

Overview of the module contents

  • Basic principles of empirical research
  • Research process
  • Operationalization
  • Data collection
  • Evaluation and interpretation
  • Applied empirical research
  • Execution of own empirical research
  • Presentation of results
  • "Lessons learned"