Optimal Release of Inventory Using Online Auctions: The Two Item Case

Abstract

In this paper we analyze policies for optimally disposing inventory using online auctions. We assume a seller has a fixed number of items to sell using a sequence of, possibly overlapping, single-item auctions. The decision the seller must make is when to start each auction. The decision involves a trade-off between a holding cost for each period an item remains unsold, and a higher expected final price the fewer the number of simultaneous auctions underway. Consequently the seller must trade-off the expected marginal gain for the ongoing auctions with the expected marginal cost of the unreleased items by further deferring their release. We formulate the problem as a discrete time Markov Decision Problem and consider two cases. In the first case we assume the auctions are guaranteed to be successful, while in the second case we assume there is a positive probability that an auction receives no bids. The reason for considering these two cases are that they require different analysis. We derive conditions to ensure that the optimal release policy is a control limit policy in the current price of the ongoing auctions, and provide several illustration of results. The paper focuses on the two item case which has sufficient complexity to raise challenging questions.

Keywords: Online Auctions, Price Cannibalization, Strategic Auction Release, Markov Decision Process