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Non-linear pricing effects in conjoint analysis

Author

Listed:
  • YiChun Miriam Liu

    (Towson University)

  • Jeff D. Brazell

    (University of Utah)

  • Greg M. Allenby

    (The™ Ohio State University)

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.

Suggested Citation

  • YiChun Miriam Liu & Jeff D. Brazell & Greg M. Allenby, 2022. "Non-linear pricing effects in conjoint analysis," Quantitative Marketing and Economics (QME), Springer, vol. 20(4), pages 397-430, December.
    • Handle: RePEc:kap:qmktec:v:20:y:2022:i:4:d:10.1007_s11129-022-09256-3
    DOI: 10.1007/s11129-022-09256-3
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    References listed on IDEAS

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    1. Jerry Wind & Paul E. Green & Douglas Shifflet & Marsha Scarbrough, 1989. "Courtyard by Marriott : Designing a Hotel Facility with Consumer-Based Marketing Models," Interfaces, INFORMS, vol. 19(1), pages 25-47, February.
    2. Tetyana Kosyakova & Thomas Otter & Sanjog Misra & Christian Neuerburg, 2020. "Exact MCMC for Choices from Menus—Measuring Substitution and Complementarity Among Menu Items," Marketing Science, INFORMS, vol. 39(2), pages 427-447, March.
    3. Greg Allenby & Jeff Brazell & John Howell & Peter Rossi, 2014. "Economic valuation of product features," Quantitative Marketing and Economics (QME), Springer, vol. 12(4), pages 421-456, December.
    4. Richard H. Thaler, 2008. "Mental Accounting and Consumer Choice," Marketing Science, INFORMS, vol. 27(1), pages 15-25, 01-02.
    5. Greg M. Allenby & Jeff Brazell & John R. Howell & Peter E. Rossi, 2014. "Valuation of Patented Product Features," Journal of Law and Economics, University of Chicago Press, vol. 57(3), pages 629-663.
    6. Rajeev Kohli & Ramesh Krishnamurti, 1987. "A Heuristic Approach to Product Design," Management Science, INFORMS, vol. 33(12), pages 1523-1533, December.
    7. Garrett Sonnier & Andrew Ainslie & Thomas Otter, 2007. "Heterogeneity distributions of willingness-to-pay in choice models," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 313-331, September.
    8. Marshall P. & Bradlow E.T., 2002. "A Unified Approach to Conjoint Analysis Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 674-682, September.
    9. Mingyu Joo & Michael L. Thompson & Greg M. Allenby6, 2019. "Optimal Product Design by Sequential Experiments in High Dimensions," Management Science, INFORMS, vol. 65(7), pages 3235-3254, July.
    10. Jeff Brazell & Christopher Diener & Ekaterina Karniouchina & William Moore & Válerie Séverin & Pierre-Francois Uldry, 2006. "The no-choice option and dual response choice designs," Marketing Letters, Springer, vol. 17(4), pages 255-268, December.
    11. Oded Netzer & Olivier Toubia & Eric Bradlow & Ely Dahan & Theodoros Evgeniou & Fred Feinberg & Eleanor Feit & Sam Hui & Joseph Johnson & John Liechty & James Orlin & Vithala Rao, 2008. "Beyond conjoint analysis: Advances in preference measurement," Marketing Letters, Springer, vol. 19(3), pages 337-354, December.
    12. Jeffrey D. Camm & James J. Cochran & David J. Curry & Sriram Kannan, 2006. "Conjoint Optimization: An Exact Branch-and-Bound Algorithm for the Share-of-Choice Problem," Management Science, INFORMS, vol. 52(3), pages 435-447, March.
    13. P. V. (Sundar) Balakrishnan & Varghese S. Jacob, 1996. "Genetic Algorithms for Product Design," Management Science, INFORMS, vol. 42(8), pages 1105-1117, August.
    14. John R. Hauser & Felix Eggers & Matthew Selove, 2019. "The Strategic Implications of Scale in Choice-Based Conjoint Analysis," Marketing Science, INFORMS, vol. 38(6), pages 1059-1081, November.
    15. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    16. Peter J. Lenk & Wayne S. DeSarbo & Paul E. Green & Martin R. Young, 1996. "Hierarchical Bayes Conjoint Analysis: Recovery of Partworth Heterogeneity from Reduced Experimental Designs," Marketing Science, INFORMS, vol. 15(2), pages 173-191.
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