Second-price Experimental Auction
Second-price experimental auctions (SPEA (s)) elicit subjects’ true willingness to pay (WTP) values for products or product attributes1 . Researchers have utilized SPEAs to determine WTP for improved food safety, value-added production properties (e.g. improved animal welfare), and sensory quality2,3,4,5. In typical central location tests, consumers rate their acceptance of product(s) based on predominantly sensory attributes; however, in SPEAs, consumers can determine the contribution of sensory and non-sensory attributes to their WTP values. Thus, perhaps the SPEA can better capture the total satisfaction consumers derive from product(s).
The SPEA is structured so that the highest bidder wins the auction but pays the second-highest bid, which insures incentive compatibility (i.e. consumers are compelled to bid their true WTP) (see6). For example, if a consumer’s true WTP were $5 and he bid $6 (an overbid), he may win the auction and have to pay $5.50, more than his true WTP. If he bid $4 (an underbid), someone else may win the auction and pay $4.50, which is less than his true WTP. In this way, underbidding and overbidding offer no strategic advantage.
To explain what drives WTP, after the bids are collected and before subjects leave, subjects fill out a survey with demographic and attitudinal questions. The nature of these questions depends on the context of the study, though the objective is to explain what drives WTP. For example, if the product were a nutraceutical, some questions should address the health consciousness of the consumer.
After the data is collected, regression analysis is used to predict willingness to pay. Willingness to pay is the y-variable, and the x-variables are chosen for their ability to explain WTP. The best models explain the most variance. If zeros bids are prevalent in the data, than tobit regression is appropriate to correct potential bias in the model. If zero bids are not prevalent, then random effects regression may be appropriate.
The SPEA is advantageous over other methods. For one, the laboratory setting in which SPEAs are executed reduces external distractions7. Secondly, the auction is non-hypothetical, which reminds consumers that real money is involved and thus eliminates hypothetical bias that may lead to inflated WTP values8,9. The winner (i.e. highest bidder) of the auction actually pays the second highest bid and consumes the product. This structure compels subjects to bid their true WTP.
Generally, the SPEA costs more than other methods that measure WTP (e.g. conjoint analysis). Additionally, compensation payments can potentially bias consumers’ bids7. The SPEA does not mimic the grocery store setting because only one subject receives the product in the end. Potentially, this leads to competitive subjects inflating their bids because they receive additional utility from winning. Ideally, subjects should only bid on the utility they receive from the test product or product attribute. Alternative auction systems, such as the Becker, Degroot and Marschak (BDM) mechanism10 reduce the competitive nature of the auction through the establishment of a market price, any bidders above which are winners. Recently, the BDM mechanism elicited WTP for health benefits associated with added fiber11, which demonstrates the BDM mechanism’s ability to determine the value of non-sensory product attributes.
SPEAs elicit WTP through a non-hypothetical mechanism. Measuring and explaining WTP can promote understanding of the consumer and potentially predict new product success12. The SPEA is potentially a valuable asset to the sensory scientist.
1 Vickrey, W. (1961). Counterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance, 16, 8-37.
2 Napolitano, F., Pacelli, C., Girolami, A. & Braghieri, A. (2008). Effect of information about animal welfare on consumer willingness to pay for yogurt. Journal of dairy science, 91, 910-917.
3 Lund, C.M., Jaeger, S.R., Amos, R.L., Brookfield, P. & Harker, F.R. (2006). Tradeoffs between emotional and sensory perceptions of freshness influence the price consumers will pay for apples: Results from an experimental market. Postharvest Biology and Technology, 41, 172-180.
4 Brown, J., Cranfield, J.A.L. & Henson, S. (2005). Relating consumer willingness-to-pay for food safety to risk tolerance: An experimental approach. Canadian Journal of Agricultural Economics-Revue Canadienne D Agroeconomie, 53, 249-263.
5 Napolitano, F. (2009). Meat liking, animal welfare and consumer willingness to pay. Italian Journal of Animal Science, 8, 469-476.
6 Lusk, J.L., Shogren, J.F. (2007). Experimental Auctions. Cambridge: Cambridge University Press.
7 Lee, K.H. & Hatcher, C.B. (2001). Willingness to pay for information: An analyst’s guide. Journal of Consumer Affairs, 35, 120-140.
8 Aadland D, Caplan A.J. (2006). Cheap talk reconsidered: New evidence from CVM. Journal of Economic Behavior & Organization 60, 562-578.
9 Harrison G.W. (2006). Experimental evidence on alternative environmental valuation methods. Environmental & Resource Economics, 34, 125-162.
10 G.M. Becker, G.M., Degroot, M.H., & Marschak, J. (1964). Measuring utility by a single-response sequential method. Behavioral Science, 9, 226-232.
11 Ginon, E., Lohéac, Y., Martin, C., Combris, P., & Issanchou, S. (2009).
Effect of fibre information on consumer willingness to pay for French baguettes. Food Quality and Preference, 20, 343-352.
12 Wertenbroch, K., Skiera, B. (2002). Measuring Consumers’ Willingness to Pay at the Point of Purchase. Journal of Marketing Research, 39, 228-241.