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Correcting for CBC model bias. A hybrid scanner data - conjoint model.

Natter, Martin and Feurstein, Markus (2001) Correcting for CBC model bias. A hybrid scanner data - conjoint model. Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science", 57. SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, Vienna.

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Abstract

Choice-Based Conjoint (CBC) models are often used for pricing decisions, especially when scanner data models cannot be applied. Up to date, it is unclear how Choice-Based Conjoint (CBC) models perform in terms of forecasting real-world shop data. In this contribution, we measure the performance of a Latent Class CBC model not by means of an experimental hold-out sample but via aggregate scanner data. We find that the CBC model does not accurately predict real-world market shares, thus leading to wrong pricing decisions. In order to improve its forecasting performance, we propose a correction scheme based on scanner data. Our empirical analysis shows that the hybrid method improves the performance measures considerably. (author's abstract)

Item Type: Paper
Keywords: Choice-Based Conjoint analysis / external validity / latent class model / pricing / scanner data model
Divisions: Departments > Informationsverarbeitung u Prozessmanag. > Produktionsmanagement > Taudes
Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Departments > Marketing > Service Marketing und Tourismus
Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft
Depositing User: Repository Administrator
Date Deposited: 08 Mar 2002 13:58
Last Modified: 15 Sep 2010 00:05
URI: http://epub.wu.ac.at/id/eprint/880

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