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A dynamic model of auctions with buy-it-now: theory and evidence

Jong-Rong Chen (), Kong-Pin Chen, Chien-Fu Chou and Ching-I Huang

MPRA Paper from University Library of Munich, Germany

Abstract: 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 bidder and the optimal BIN price of the seller when they are both risk-averse. The seller is shown to be strictly better o with the BIN option, while the bidders are better o only when their valuation is greater than a threshold value. The theory also implies that the expected transaction price is higher in an auction with an optimal BIN price than one without a BIN. This prediction is conrmed by our data collected from Taiwan's Yahoo! auctions of Nikon digital cameras.

Keywords: online auction; but-it-now; risk-aversion (search for similar items in EconPapers)
JEL-codes: D02 D44 L81 (search for similar items in EconPapers)
Date: 2006-04-03, Revised 2011-11-24
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Journal Article: A Dynamic Model of Auctions with Buy-It-Now: Theory and Evidence (2013) Downloads
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