Market Research II
Modul M.WIWI-BWL.0079
discontinued module
Lecturer:
- Prof. Dr. Yasemin Boztuğ
- Prof. Dr. Maik Hammerschmidt
- Prof. Dr. Waldemar Toporowski
Lecturer exercise:
- Chiara Pfeiffer
Module for the following Master's degree programmes:
- Marketing and E-Business (M.Sc.)
- Finance, Accounting and Taxes (M.Sc.)
- Management (M.Sc.)
- Global Business (M.Sc.)
- Taxation (M.Sc.)
- Business Information Systems (M.Sc.)
- Business and Human Resource Education (M.Ed.)
- Business Education and Human Resource Development (M.Sc.)
- Development Economics (M.Sc.)
- International Economics (M.Sc.)
- History of Global Markets (M.A.)
- Applied Statistics (M.Sc.)
- Pferdewissenschaften (M.Sc.)
- Psychology (M.Sc.)
Course language:
German
Admission requirements:
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
Time and place of lecture:
Digital lecture: digital event
- 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.
Start of lecture:
The event will be made available digitally
For more information, please refer to the announcements in Stud.IP.
Examination:
Written exam: 90 Min (6 CP)
Examination requirements:
Proof of knowledge in multivariate procedures. Application on marketing relevant problems and interpretation of multivariate methods results.
Date of written exam:
Date: 22.07.2024, 10:15 - 11:45 a.m.
Room: ZHG 105
Date of second written exam:
Date: tba
Room: tba
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 courses:
The exercises take place in digital format
Start of exercise courses:
tbd
For more information, please refer to the announcements in Stud.IP.
Recommended references for the lecture: