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Re-examining the no-choice option in conjoint analysis

Author

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  • Hung, Cheng-Yu
  • Kurz, Peter
  • Bailey, Roger A.
  • Huber, Joel
  • Allenby, Greg M.

Abstract

The validity of using conjoint analysis to conduct an economic evaluation of product characteristics rests on the inclusion of brand names, prices, and an outside “no-choice” option in the choice task. The no-choice option is included in case respondents determine that some other offering, not included in the conjoint choice task, is preferred to those that are included and that it would be better to hold onto their money and not make a purchase at that time. Selecting the no-choice option assumes that respondents have some level of knowledge of the value and prices of goods in the market. In this paper, we show that survey respondents may lack this information and make inferences about market prices from the conjoint exercise itself. This learning effect is especially problematic for new products for which a set of reference prices do not yet exist, but can also be problematic in established markets that are familiar. We discuss results from two sets of conjoint experiments, one in a new product category conducted in three countries in Europe, and another in an established category in the United States involving three experimental conditions that inform respondents about products and prices available in the marketplace. We find that the lack of knowledge of competitive offerings and prices affects estimates of brand values but not the value of other product features. In addition, we discuss aspects of how a well-designed conjoint study mitigates the effects of this type of learning in conjoint analysis.

Suggested Citation

  • Hung, Cheng-Yu & Kurz, Peter & Bailey, Roger A. & Huber, Joel & Allenby, Greg M., 2025. "Re-examining the no-choice option in conjoint analysis," Journal of choice modelling, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:eejocm:v:57:y:2025:i:c:s1755534525000417
    DOI: 10.1016/j.jocm.2025.100578
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    References listed on IDEAS

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