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

Daniel Baier , Marcin Pełka , Aneta Rybicka , Stefanie Schreiber


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 aremeasured 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.
Author Daniel Baier
Daniel Baier,,
, Marcin Pełka (EMaT / DEaCS)
Marcin Pełka,,
- Department of Econometrics and Computer Science
, Aneta Rybicka (EMaT / DEaCS / ZMiIE)
Aneta Rybicka,,
- Zakład Mikroekonometrii i Informatyki Ekonomicznej
, Stefanie Schreiber
Stefanie Schreiber,,
Publication size in sheets0.55
Book Lausen Berthold, Krolak-Schwerdt Sabine, Böhmer Matthias (eds.): Data Science, Learning by Latent Structures, and Knowledge Discovery, Studies in Classification, Data Analysis, and Knowledge Organization, 2015, Springer-Verlag, ISBN 978-3-662-44982-0, [978-3-662-44983-7], 560 p., DOI:10.1007/978-3-662-44983-7
Keywords in Englishmodels, issues
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
Publication indicators WoS Citations = 2
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