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

Jong Rong Chen, Kong Pin Chen, Chien Fu Chou, Ching I. Huang

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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 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.

Original languageEnglish
Pages (from-to)393-429
Number of pages37
JournalJournal of Industrial Economics
Volume61
Issue number2
DOIs
StatePublished - Jun 2013

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