A Dynamic Model of Auctions with Buy-It-Now: Theory and Evidence

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In the ascending-price auctions with Yahoo!-type buy-it-now (BIN), we characterize and derive the closed-form solution for the optimal bidding strategy of the bidders and the optimal BIN price of the seller when they are both risk-averse. The seller is shown to be strictly better off with the BIN option, while the bidders are better off only when their valuation is high enough. The theory also implies that the expected transaction price is higher in an auction with an optimal BIN price than one without a BIN option. This prediction is confirmed by our data collected from Taiwan's Yahoo! auctions.