The Impact of Information in Electronic Auctions: An Analysis of Buy-It-Now Auctions

Authors:
Byungjoon Yoo;Kevin Ho;Kar Yan Tam
Affiliations:
Korea University;Hong Kong University of Science and Technology;Hong Kong University of Science and Technology
Venue:
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
Year:
2006

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Abstract

Our study on the Buy-it-now (BIN) option at electronic auctions examines the impact of information in making electronic transactions more efficient. We show that the BIN price itself works as valuable information, which can improve the performance of auctions even though the option may discourage bidders from participating in auctions because of the possibility of losing the auction when a competing bidder executes the option. With auction data, we empirically show that, even when the BIN option is not executed, the performance of auctions with the BIN option is better than that of auctions without the option. This shows that the BIN price helps bidders get a better estimate of the final auction price, while the negative discouraging impact is not so significant. We suggest that market makers should try their best to provide more information with devices like BIN and to minimize the negative side effects of more information.