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Barter Markets for Conjoint Analysis

Author

Listed:
  • Min Ding

    (Smeal College of Business, Pennsylvania State University, University Park, Pennsylvania 16802)

  • Young-Hoon Park

    (The Johnson School, Cornell University, Ithaca, New York 14853)

  • Eric T. Bradlow

    (Marketing, Statistics, and Education, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

We propose a new alternative preference measurement method, barter conjoint, to contrast with traditional choice-based conjoint (CBC) approaches. Barter conjoint collects a substantially larger amount of data compared to CBC and allows for information diffusion among respondents. We conducted two empirical studies that compare CBC (with and without incentive alignment) and barter conjoint. The studies employed a total of three product categories, each with two validation tasks (one follows immediately and one conducted two weeks later). Our results confirmed prior research that incentive alignment, in general, substantially improves out-of-sample predictive performance of CBC. Furthermore, we found barter conjoint performs substantially better than the incentive-aligned CBC. However, in the spirit of "no free lunch," barter conjoint is more taxing (in various ways) than CBC, suggesting a potential trade-off between consumer resource allocation (at the time of the task) and (managerial) predictive accuracy downstream. Given that this is the first study on barter conjoint, we discuss various limitations of the current implementation and fruitful directions for future research.

Suggested Citation

  • Min Ding & Young-Hoon Park & Eric T. Bradlow, 2009. "Barter Markets for Conjoint Analysis," Management Science, INFORMS, vol. 55(6), pages 1003-1017, June.
  • Handle: RePEc:inm:ormnsc:v:55:y:2009:i:6:p:1003-1017
    DOI: 10.1287/mnsc.1090.1003
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    References listed on IDEAS

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    Cited by:

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    9. Dongling Huang & Lan Luo, 2016. "Consumer Preference Elicitation of Complex Products Using Fuzzy Support Vector Machine Active Learning," Marketing Science, INFORMS, vol. 35(3), pages 445-464, May.
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