Treffer: Incentive alignment in conjoint analysis: a meta-analysis on predictive validity.

Conjoint analysis is a widely used method in market research for predicting consumer purchases, making predictive validity a central tenet. Conjoint analyses, however, are typically conducted in hypothetical settings, making them susceptible to hypothetical bias. One solution is incentive-aligning conjoint studies to trigger truthful answering behavior, thereby increasing the accuracy of predictions. However, despite incentive alignment's conceptual appeal, practitioners rarely use it. One reason for this is the uncertainty of its effectiveness. This research systematically investigates the gains in predictive validity employing a meta-analysis of 134 effect sizes from 34 articles (N = 12,980). Incentive alignment increases the predictive validity (i.e., hit rate) by 12%, providing a significant increase in accuracy. In addition, its effectiveness is amplified when researching durable and service goods (vs. non-durable goods) and when the payout probability rises. In contrast to conventional wisdom, indirect (vs. direct) incentive procedures do not mitigate the positive effects on predictive validity. We hope to stimulate a rethink in practice to make more use of incentive alignment and help decide whether incentive alignment is worth the additional effort. [ABSTRACT FROM AUTHOR]

Copyright of Marketing Letters is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)