Return to search

Improving predictive validity of choice-based conjoint models

Up to date, it is unclear how Choice-Based Conjoint (CBC) models perform in terms of forecasting (external) real world aggregate shop data. In this contribution, we measure the performance of a Latent Class CBC model - not with an experimental holdout sample - but with aggregate real world scanning data. We find that the CBC model does not accurately predict real world market shares. In order to improve the forecasting performance, we propose a correction scheme based on external scanner data. Our analysis based on 8 brands shows that the use of the proposed correction vector improves the performance measure considerably. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_1ad
Date January 2000
CreatorsNatter, Martin, Feurstein, Markus
PublisherSFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypePaper, NonPeerReviewed
Formatapplication/pdf
Relationhttp://epub.wu.ac.at/1372/

Page generated in 0.0017 seconds