IDEAS home Printed from https://ideas.repec.org/a/ibf/ijmmre/v9y2016i2p81-100.html
   My bibliography  Save this article

The Performance Of Competitive And Lottery Incentive Schemes Vis-À-Vis Fixed Fee Incentive Schemes In Improving Conjoint Analysis

Author

Listed:
  • Srikant Vadali

Abstract

Paying a fixed amount of money to participants in choice-based conjoint (CBC) studies is the industry standard. Recently, Ding (2007) has shown that a lottery incentive scheme outperformed a fixed fee incentive scheme when predicting out-of-sample choices. We achieve two research goals in the current paper to extend our understanding of incentive schemes in the context of CBC studies. One, we investigate if a higher fixed-fee (e.g. $50 instead of $10) helps improve out-of-sample predictions. Two, the lottery incentive scheme does not induce competition among CBC study participants. Therefore, we investigate the theoretical properties and empirical effectiveness of competitive incentive schemes relative to lottery and fixed incentive schemes. Our key findings with respect to hit rates for out-of-sample predictions are: (a) offering higher amounts of money is ineffective, and (b) competitive incentive schemes outperform the lottery incentive scheme (Hit Rates of 41 % and 62% for the 2 proposed competitive schemes vs. 29% for the lottery incentive scheme)

Suggested Citation

  • Srikant Vadali, 2016. "The Performance Of Competitive And Lottery Incentive Schemes Vis-À-Vis Fixed Fee Incentive Schemes In Improving Conjoint Analysis," International Journal of Management and Marketing Research, The Institute for Business and Finance Research, vol. 9(2), pages 81-100.
  • Handle: RePEc:ibf:ijmmre:v:9:y:2016:i:2:p:81-100
    as

    Download full text from publisher

    File URL: http://www.theibfr2.com/RePEc/ibf/ijmmre/ijmmr-v9n2-2016/IJMMR-V9N2-2016-7.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Conjoint Analysis; Incentive Schemes; Experiments; HB Estimation; Multinomial Logit;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

    Statistics

    Access and download statistics

    Corrections

    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:ibf:ijmmre:v:9:y:2016:i:2:p:81-100. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mercedes Jalbert (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.