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THE OPTIMAL LISTING STRATEGIES IN ONLINE AUCTIONS
Author(s) -
Chen KongPin,
Ho SzuHsien,
Liu ChiHsiang,
Wang ChienMing
Publication year - 2017
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/iere.12222
Subject(s) - reverse auction , forward auction , revenue equivalence , common value auction , listing (finance) , auction theory , dutch auction , microeconomics , english auction , vickrey auction , bin , value (mathematics) , generalized second price auction , economics , computer science , finance , algorithm , machine learning
This article proposes a unified framework to completely characterize the seller's optimal listing strategy in the online auction as a function of her rate of time impatience. Specifically, the fixed‐price listing, the regular auction, and the buy‐it‐now (BIN) auction are each a solution of the seller's single optimization problem under different values of the rate of intertemporal discount: The perfectly patient seller adopts the regular auction, the sellers with a medium range of time impatience adopt the BIN auction, and the most impatient of sellers adopt the fixed‐price listing. Moreover, under mild conditions, the reverse price is inversely related to the value of the seller's discount factor, either within or across formats. This in turn implies that the posted price in the fixed‐price sale is greater than the reserve price of the BIN auction, followed by that of the regular auction. These predictions offer clear empirical implications.