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Thirty Years of Conjoint Analysis: Reflections and Prospects

Author

Listed:
  • Paul E. Green

    (Suite 1400, Steinberg Hall-Dietrich Hall, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104-6371)

  • Abba M. Krieger

    (Suite 3000, Steinberg Hall-Dietrich Hall, The Wharton School)

  • Yoram Wind

    (Suite 1400, Steinberg Hall-Dietrich Hall, The Wharton School)

Abstract

Conjoint analysis is marketers' favorite methodology for finding out how buyers make trade-offs among competing products and suppliers. Conjoint analysts develop and present descriptions of alternative products or services that are prepared from fractional factorial, experimental designs. They use various models to infer buyers' part-worths for attribute levels, and enter the part-worths into buyer-choice simulators to predict how buyers will choose among products and services. Easy-to-use software has been important for applying these models. Thousands of applications of conjoint analysis have been carried out over the past three decades.

Suggested Citation

  • Paul E. Green & Abba M. Krieger & Yoram Wind, 2001. "Thirty Years of Conjoint Analysis: Reflections and Prospects," Interfaces, INFORMS, vol. 31(3_supplem), pages 56-73, June.
  • Handle: RePEc:inm:orinte:v:31:y:2001:i:3_supplement:p:s56-s73
    DOI: 10.1287/inte.31.3s.56.9676
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    References listed on IDEAS

    as
    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. Wittink, Dick R & Krishnamurthi, Lakshman & Nutter, Julia B, 1982. "Comparing Derived Importance Weights Across Attributes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 8(4), pages 471-474, March.
    3. S. Chan Choi & Wayne S. Desarbo & Patrick T. Harker, 1990. "Product Positioning Under Price Competition," Management Science, INFORMS, vol. 36(2), pages 175-199, February.
    4. Wayne S. DeSarbo & J. Douglas Carroll & Donald R. Lehmann & John O'Shaughnessy, 1982. "Three-Way Multivariate Conjoint Analysis," Marketing Science, INFORMS, vol. 1(4), pages 323-350.
    5. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    6. Paul E. Green & Abba M. Krieger, 1996. "Individualized Hybrid Models for Conjoint Analysis," Management Science, INFORMS, vol. 42(6), pages 850-867, June.
    7. 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.
    8. Paul E. Green & Ronald E. Frank & Patrick J. Robinson, 1967. "Cluster Analysis in Test Market Selection," Management Science, INFORMS, vol. 13(8), pages 387-400, April.
    Full references (including those not matched with items on IDEAS)

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