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This course focuses on choice-based conjoint (CBC) analysis as a tool for estimating individual-level preference parameters. Students learn the economic and statistical assumptions that underpin CBC, their managerial implications, and best practices for designing choice experiments and collecting data. Working in teams, students develop a research question, design a CBC study, and collect data. Using Bayesian estimation in R, specifically the bayesm package, they then estimate individual part-worth utilities and use them for segmentation, targeting, and “what-if” market simulations. By the end of the course, participants will be able to design a CBC study from scratch, estimate the model, interpret the results, and translate the findings into actionable marketing recommendations.
Prerequisite for participation: Successful participation in the course "Advanced Marketing Modeling" or "Causal Inference in Marketing". Students need to know how to code in R.
Max. number of participants: 20. Students with a case of hardship according to §90 (1) ZSP HU (health, social, disability, or family reasons) will be given preference in the selection process (proof must be submitted during the registration period). Otherwise, the decision will be made by lot.
Registration for the seminar will take place from 1 October to 10 October 2025. Please email all the necessary information, including your actual transcript of study success, to mktg@wiwi.hu-berlin.de. It is sufficient to provide a printout of your study success via Agnes. No official stamp is needed.
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StO/PO MA 2016: 6 LP, Modul: "Seminar Marketing"
StO/PO MEMS 2016: 6 LP, Modul: "Seminar Marketing", Major: Quantitative Management Science |
