A dynamic model of auctions with buy-it-now: theory and evidence
Jong-Rong Chen (),
Kong-Pin Chen (),
Chien-Fu Chou and
MPRA Paper from University Library of Munich, Germany
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: L81 D44 D02 (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)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:38371
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