IDEAS home Printed from
   My bibliography  Save this article

Augmenting Conjoint Analysis to Estimate Consumer Reservation Price


  • Kamel Jedidi

    () (Graduate School of Business, Columbia University, 3022 Broadway, New York, New York 10027)

  • Z. John Zhang

    () (The Wharton School, 700 Jon M. Huntsman Hall, 3730 Walnut Street, Philadelphia, Pennsylvania 19104-6340)


Consumer reservation price is a key concept in marketing and economics. Theoretically, this concept has been instrumental in studying consumer purchase decisions,competitive pricing strategies,and welfare economics. Managerially,knowledge of consumer reservation prices is critical for implementing many pricing tactics such as bundling,tar get promotions,nonlinear pricing,and one-to-one pricing,and for assessing the impact of marketing strategy on demand. Despite the practical and theoretical importance of this concept, its measurement at the individual level in a practical setting proves elusive. We propose a conjoint-based approach to estimate consumer-level reservation prices. This approach integrates the preference estimation of traditional conjoint with the economic theory of consumer choice. This integration augments the capability of traditional conjoint such that consumers' reservation prices for a product can be derived directly from the individuallevel estimates of conjoint coefficients. With this augmentation,we can model a consumer's decision of not only which product to buy,but also whether to buy at all in a category. Thus, we can simulate simultaneously three effects that a change in price or the introduction of a new product may generate in a market: the customer switching effect,the cannibalization effect,and the market expansion effect. We show in a pilot application how this approach can aid product and pricing decisions. We also demonstrate the predictive validity of our approach using data from a commercial study of automobile batteries.

Suggested Citation

  • Kamel Jedidi & Z. John Zhang, 2002. "Augmenting Conjoint Analysis to Estimate Consumer Reservation Price," Management Science, INFORMS, vol. 48(10), pages 1350-1368, October.
  • Handle: RePEc:inm:ormnsc:v:48:y:2002:i:10:p:1350-1368
    DOI: 10.1287/mnsc.48.10.1350.272

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Shaffer, G. & Zhang, Z.J., 1994. "Competitive Coupon Targeting," Papers 94-02, Michigan - Center for Research on Economic & Social Theory.
    2. Charlotte H. Mason, 1990. "New Product Entries and Product Class Demand," Marketing Science, INFORMS, vol. 9(1), pages 58-73.
    Full references (including those not matched with items on IDEAS)


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:48:y:2002:i:10:p:1350-1368. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matthew Walls). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.