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Economic valuation of product features

Author

Listed:
  • Greg Allenby
  • Jeff Brazell
  • John Howell
  • Peter Rossi

    ()

Abstract

We develop a market-based paradigm to value the enhancement or addition of features to a product. We define the market value of a product or feature enhancement as the change in the equilibrium profits that would prevail with and without the enhancement. In order to compute changes in equilibrium profits, a valid demand system must be constructed to value the feature. The demand system must be supplemented by information on competitive offerings and cost. In many situations, demand data is either not available or not informative with respect to demand for a product feature. Conjoint methods can be used to construct the demand system via a set of designed survey-based experiments. We illustrate our methods using data on the demand for digital cameras and demonstrate how the profits-based metric provides very different answers than the standard welfare or Willingness-To-Pay calculations. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • 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.
  • Handle: RePEc:kap:qmktec:v:12:y:2014:i:4:p:421-456
    DOI: 10.1007/s11129-014-9150-x
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    References listed on IDEAS

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    1. Dan Horsky & Paul Nelson, 1992. "New Brand Positioning and Pricing in an Oligopolistic Market," Marketing Science, INFORMS, vol. 11(2), pages 133-153.
    2. Elie Ofek & V. Srinivasan, 2002. "How Much Does the Market Value an Improvement in a Product Attribute?," Marketing Science, INFORMS, vol. 21(4), pages 398-411, June.
    3. 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.
    4. Min Ding & Rajdeep Grewal & John Liechty, 2005. "Incentive-aligned conjoint analysis," Framed Field Experiments 00139, The Field Experiments Website.
    5. 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.
    6. Amil Petrin, 2002. "Quantifying the Benefits of New Products: The Case of the Minivan," Journal of Political Economy, University of Chicago Press, vol. 110(4), pages 705-729, August.
    7. Kenneth E. Train, 1998. "Recreation Demand Models with Taste Differences over People," Land Economics, University of Wisconsin Press, vol. 74(2), pages 230-239.
    8. repec:eee:ijrema:v:27:y:2010:i:1:p:25-32 is not listed on IDEAS
    9. Trajtenberg, Manuel, 1989. "The Welfare Analysis of Product Innovations, with an Application to Computed Tomography Scanners," Journal of Political Economy, University of Chicago Press, vol. 97(2), pages 444-479, April.
    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.
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    Citations

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    Cited by:

    1. Yegoryan, Narine & Guhl, Daniel & Klapper, Daniel, 2018. "Inferring Attribute Non-Attendance Using Eye Tracking in Choice-Based Conjoint Analysis," Rationality and Competition Discussion Paper Series 111, CRC TRR 190 Rationality and Competition.
    2. Nino Hardt & Alex Varbanov & Greg M. Allenby, 2016. "Monetizing Ratings Data for Product Research," Marketing Science, INFORMS, vol. 35(5), pages 713-726, September.
    3. 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.
    4. Federico Ciliberto & GianCarlo Moschini & Edward D. Perry, 2019. "Valuing product innovation: genetically engineered varieties in US corn and soybeans," RAND Journal of Economics, RAND Corporation, vol. 50(3), pages 615-644, September.
    5. Villas-Boas, Sofia B & Kiesel, Kristin & Berning, Joshua & Chouinard, Hayley & McCluskey, Jill, 2019. "Consumer and Strategic Firm Response to Nutrition Shelf Labels," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt58j648mk, Department of Agricultural & Resource Economics, UC Berkeley.

    More about this item

    Keywords

    Product features; Conjoint; Equilibrium profits; Bayesian analysis; C11; C23; C25; C81; D12; D43; K11; L13; M3;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • K11 - Law and Economics - - Basic Areas of Law - - - Property Law
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • M3 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising

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