Market Research II
Prof. Dr. Yasemin Boztuğ
Prof. Dr. Maik Hammerschmidt
Prof. Dr. Waldemar Toporowski
Carsten Leo Demming, M.Sc.
- MEB, M.Sc. 1-2 (formerly MDM, M.Sc.)
- FRS, M.Sc.
- MAN, M.Sc.
- VWL D from 5
- WINF D from 5
- SOW D from 5
No admission requirements.
Learning outcomes/core skills:
After successful participation students will have a profound understanding of the following multivariate analysis methods: factor analysis, structural equation model, conjoint analysis (traditional, hybrid, adaptive and choice-based conjoint analysis) and discrete choice modelling. Furthermore, basic knowledge of test theory and matrix calculations is imparted. Students are able to choose appropriate procedures for marketing related problems and use them autonomously. Moreover, students can critically evaluate chosen methods with regard to its requirements and assumptions. Students have the ability to describe the methods underlying methodical and statistical ideas, interpret concrete results and derive recommendations for action. Additionally, they are able to apply their the theoretical knowledge practically using suitable statistics software.
Contents of the lecture:
- Introduction to test theory
- Mathematical essentials
- Factor analysis
- Structure equation modelling
- Conjoint analysis (traditional, hybrid, adaptive and choice-based conjoint analysis)
- Discrete choice modelling
Every Monday 10:15 - 11:45 a.m., room ZHG 002
Written exam: 90 Min (6 CP)
Proof of knowledge in multivariate procedures. Application on marketing relevant problems and interpretation of multivariate methods results.
Date of written exam:
Date: 29.07.2019, 10:15 - 11:45 a.m.
Room: ZHG 010
Date of second written exam:
Contents of the exercise:
In the accompanying practice sessions students deepen and broaden their knowledge from the lecture by applying methods to typical market research problems. Contents are thought using SPSS, AMOS and Sawtooth software. In the exercises, worksheets with practical application cases are used. The exercises specifically instruct the execution and interpretation of analyses.
Date of exercise coures:
Every Thursday, 2:00 - 4:00 p.m. or 4:00 - 6:00 p.m., room MZG 7.153
Recommended references for the lecture:
- Lattin, J. M., Caroll, J. D., & Green, P. E. (2003): Analyzing Multivariate Data, Belmont.
- Tabachnick, B.G., & Fidell, L.S (2013): Using Multivariate Statistics, Pearson Education, Boston.
- Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2018): Multivariate Analysemethoden, Springer-Gabler, Berlin.
- Backhaus, K., Erichson, W., & Weiber, R. (2015): Fortgeschrittene Multivariate Analysemethoden, Springer-Gabler, Berlin.
- Hair, J.F., Black, W.D., Babin, B.J., & Anderson, R.E. (2013): Multivariate Data Analysis, Pearson, Upper Saddle River.