Details

Autor(en) / Beteiligte

• Baier, Daniel
• Pełka, Marcin
• Rybicka, Aneta
• Schreiber, Stefanie
• Lausen, Berthold
• Krolak-Schwerdt, Sabine
• Böhmer, Matthias

Titel

Ratings-/Rankings-Based Versus Choice-Based Conjoint Analysis for Predicting Choices

Ist Teil von

• Data Science, Learning by Latent Structures, and Knowledge Discovery, p.205-216

Ort / Verlag

Berlin, Heidelberg: Springer Berlin Heidelberg

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Nowadays, for market simulation in consumer markets with multi-attributed products, choice-based conjoint analysis (CBC) is most popular. The popularity stems—on one side—from the possibility to use online-panels for affordable data collection and—on the other side—from the possibility to estimate part worths at the respondent level using only few observations. However, a still open question is, whether this money- and time-saving approach provides the same or even better results than ratings-/rankings-based alternatives. An experiment with 787 students from Poland and Germany is used to answer this question: Cola preferences are measured using CBC as well as ratings-/rankings-based alternatives. The results are compared using the Multitrait-Multimethod Matrix for the estimated part worths and first choice hit rates for holdout choice sets. The experiment shows a superiority of CBC, but also important differences between Polish and German cola consumers that outweigh methodological differences.