Non-linear pricing effects in conjoint analysis

YiChun Miriam Liu (), Jeff D. Brazell () and Greg M. Allenby ()
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YiChun Miriam Liu: Towson University
Jeff D. Brazell: University of Utah
Greg M. Allenby: The™ Ohio State University

Quantitative Marketing and Economics (QME), 2022, vol. 20, issue 4, No 3, 397-430

Abstract: 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.

Keywords: Willingness to pay; Willingness to buy; Behavioral decision theory (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11129-022-09256-3

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