Designing Experimental Auctions For Marketing Research: Effect Of Values, Distributions, And Mechanisms On Incentives For Truthful Bidding
Accurately estimating consumer demand for new products is an arduous task made even more difficult by the fact that individuals tend to overstate the amount they are willing to pay for new goods when asked hypothetical questions. Despite their appeal in eliminating hypothetical bias, marketers have been slow to adopt experimental auctions as a standard tool in pre-test market research. One issue that has slowed adoption of the methodology is the proliferation of auction mechanisms and the lack of clear guidance in choosing between mechanisms. In this paper, we provide insight into the theoretical properties of two incentive compatible value elicitation mechanisms, the BDM and Vickrey 2nd price auction, such that practitioners can make more informed decisions in designing experimental auctions to determine consumer willingness-to-pay. In particular, we draw attention to the shapes of the payoff functions and show in a simulation that the two mechanisms differ with respect to the expected cost of deviating from truthful bidding. We show that incentives for truthful bidding depend on the distribution of competing bidders' values and/or prices and individuals' true values for a good. The simulation indicates the 2nd price auction punishes deviations from truthful bidding more severely for high value individuals than the BDM mechanism. These results are confirmed by an experimental study, where we find more accurate bidding for high-value individuals in the 2nd price auction as compared to the BDM. Our results also indicate that when implementing the BDM mechanism, the greatest incentives for truthful value revelation are created when the random price generator is based on a normal distribution centered on an individual's expected true value.
|Date of creation:||2004|
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