Institution: Fakultät für Betriebswirtschaft, Universität Hamburg
Lecturer: Tammo Bijmolt (University of Groningen, Faculty of Economics and Business)
Dates: 21st November 2016, 12th December 2016, 16th January 2017, 6th February 2017 (all sessions scheduled on Mondays)
Course Value: 3 SWS or 6 LP
Course Overview:
The PhD course deals with a variety of multivariate analysis methods. The main focus of the course is rather applied: students who have successfully finished the course should be able to apply multivariate analysis methods at an advanced level in scientific research in marketing (or more general, in business). A full-day lecture will be used to explain a particular method and to learn about conducting the analyses. There will be four topics, each with a lecture and an assignment (see below).
The course is open for students from outside Hamburg, from other departments within the Business School, and junior faculty members (max. 15-20 participants). In principle, participants could sign up for all sessions / the entire course, or cherry-pick the topic(-s) that they like.
Objectives:
After attending the course, students should have acquired:
a) State-of-the-art knowledge of potential application of these multivariate analysis methods
b) Understanding of the methodological underpinnings of the methods
c) Practical skills to perform the analyses
Assessment and Credits:
After the session, participants will have to work on an assignment (if the participant requires formal credits), using real data, and write a short report (about 10 pages; to be graded as pass/fail) about this. Participants who attend all sessions and pass the four assignments can attain 6 LP.
Potential topics:
Topics of the PhD course will be selected based on preferences of participants. Therefore, please indicate your preferred topic(s) out of the following methods when registering for the course. Four out of seven topics will be taught in the course.
# Topic
- Latent class analysis / mixture modelling
- Hierarchical models
- Hidden Markov models {assuming knowledge of 1}
- Moderation & mediation
- Meta-analysis
- Factor analysis & principal component analysis
- Duration models
Assessment and Credits: After the session, participants will have to work on an assignment (if the participant requires formal credits), using real data, and write a short report (about 10 pages; to be graded as pass/fail) about this. Participants who attend all sessions and pass the four assignments can attain 6 LP.
Registration: To register for this seminar please contact Marius Johnen (marius.johnen@uni-hamburg.de). Registration is open till 16th October 2016 and is on a first come, first serve basis.
Tammo H.A. Bijmolt is Professor of Marketing Research at the Department of Marketing. From March 2009 till November 2015, he has been Director of the research school SOM, Faculty of Economics and Business Administration, University of Groningen, The Netherlands. His research interests include conceptual and methodological issues such as consumer decision making, e-commerce, advertising, retailing, loyalty programs, and meta-analysis. His publications have appeared in international, prestigious journals, among others: Journal of Marketing Research, Journal of Marketing, Journal of Consumer Research, Marketing Science, International Journal of Research in Marketing, Psychometrika, and the Journal of the Royal Statistical Society (A). His articles have won best paper awards from International Journal of Research in Marketing (2007), Journal of Interactive Marketing (2011), and European Journal of Marketing (2015). He is member of the editorial board of International Journal of Research in Marketing and International Journal of Electronic Commerce. Tammo Bijmolt is vice-president of EIASM and lectures in the EDEN programs. He has lectured in a broad range of programs at the Bachelor, Master, PhD and executive MBA level. He has been involved in several research-based consultancy projects for a variety of companies including MetrixLab, GfK, Wehkamp, and Unilever. Finally, he served as expert in several legal cases involving market research projects.