Information on individual educational components (ECTS-Course descriptions) per semester

  
Degree programme:Master International Management and Leadership
Type of degree:FH Master´s Degree Programme
 Part-time
 Summer Semester 2023
  

Course unit titleResearch Methods
Course unit code080322021001
Language of instructionEnglish
Type of course unit (compulsory, optional)Compulsory
Semester when the course unit is deliveredSummer Semester 2023
Teaching hours per week2
Year of study2023
Level of course unit (e.g. first, second or third cycle)Second Cycle (Master)
Number of ECTS credits allocated2
Name of lecturer(s)Florian BÜHLER
Markus FEDERAU


Prerequisites and co-requisites

None

Course content

Qualitative methods:

  • data collection methods (interviews, observations, experience)
  • interview / experiment design
  • case study analysis
  • data analysis methods -quality criteria

 Quantitative methods:

  • sampling
  • survey design, incl. questionnaire
  • application of descriptive statistics
  • application of inductive statistics
  • overview of selected multivariate analysis, e.g. factor analysis, regression analysis, conjoint analysi, multidimensional scaling etc.
  • Application of quality criteria
Learning outcomes

Business and society revert to an increasingly scientific view on problems and issues. Students need to be able to understand and create evidence-based argumentation from secondary and primary research.

This course will prepare students to:

  • Identify the importance of empirical information in a business / management context
  • understand the process of empirical research – locally and in an international context
  • know the fundamental concepts to be applied to empirical research problems
  • know the basic methods of qualitative and quantitative research and when it is appropriate to apply them
  • read and interprete existing research papers and their findings
  • design empirical data collection and apply methods to analyse the data
  • know and apply statistical software to create analysis from data
  • understand the limits of validity and reliability of a given research concept
Planned learning activities and teaching methods
  • Lectures
  • Discussions
  • practical Exercises
  • Online tutorials
  • The seminar provides an exemplary overview - self-study of contents not explicitly discussed is a significant component
Assessment methods and criteria

Exam

Comment

Course will be closely connected to the course “Data collection and Interpretation”, where the learnt skills can be applied

Recommended or required reading
  • Nunan, Daniel, Birks, David F, Malhottra, Naresh K. Marketing Research, Applied Insights, 6ed, Harlow, United Kingdom, Pearson 2020
  • Heidig. W. / Dobbelstein, T.: Quick Guide Marktforschung im Mittelstand, Wiesbaden 2021
  • Denzin, Norman K. The Sage Handbook of Qualitative Research. 4. Book, Whole. Los Angeles, California: Sage Publishing, 2011.
  • Provost, Foster, and Tom Fawcett. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. 1. Book, Whole. Sebastopol, California: O’Reilly, 2013.
  • Bryman, Alan, and Emma Bell. Business Research Methods. 3. Book, Whole. Oxford: Oxford University Press, 2011.
Mode of delivery (face-to-face, distance learning)

Face-to-face instruction with mandatory attendance.

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