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Quantitative Marketing and Economics
Published in: Quantitative Marketing and Economics 4/2022

13-10-2022 | Original Research

Non-linear pricing effects in conjoint analysis

Authors: YiChun Miriam Liu, Jeff D. Brazell, Greg M. Allenby

Published in: Quantitative Marketing and Economics | Issue 4/2022

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Abstract

The application of conjoint analysis to new product development is challenged in studies of complex products that simultaneously examine the major drivers of a purchase decision and the composition of product components. Demands on data increase as more product features are included in an analysis, and at some point it becomes necessary to study the components separately. This paper presents evidence of a non-linear pricing effect that complicates the analysis of large conjoint studies when multiple conjoint exercises are integrated, or bridged into a single analysis. Our model is illustrated with data from the automotive industry showing that option packages are under-valued without accounting for the non-linear effects of price.
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Appendix
Available only for authorised users
Footnotes
1
We do not claim that our results completely explain Thaler’s model, only that some aspects are consistent with his framework.
 
2
We assume that the amount of unspent money is always positive.
 
4
We tune the RWMH algorithm so that approximately 20% of the candidates are accepted.
 
19
available on 01/02/2021
 
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Metadata
Title
Non-linear pricing effects in conjoint analysis
Authors
YiChun Miriam Liu
Jeff D. Brazell
Greg M. Allenby
Publication date
13-10-2022
Publisher
Springer US
Published in
Quantitative Marketing and Economics / Issue 4/2022
Print ISSN: 1570-7156
Electronic ISSN: 1573-711X
DOI
https://doi.org/10.1007/s11129-022-09256-3