Willingness to Pay and Competition in Online Auctions

Abstract

We model how to measure consumer willingness to pay (WTP) from an English or ascending first-price auction based on two general bidding premises: no bidder bids more than her WTP, and no bidder allows a rival bidder to win at a price that she is willing to beat (Haile and Tamer 2003). In other words, we propose a "no regret" rule in bidding. Other than that, we do not impose restrictive assumptions on maximands or behavior of bidders in a competitive auction context. We postulate WTP as having two components: a pure product feature component and one based on the auction market environment. The latter includes bidder experience, seller reputation, and measures for competition among bidders and among items. The proposed model is general enough to include "buy it now" (BIN) (equivalent to a posted price) auction mechanism.

We use data of notebook auctions from one of the largest Internet auction sites in Korea. We find that most product characteristics matter in the expected ways. Our other primary findings are as follows: (1) WTP declines as more similar items are concurrently listed with the focal item; there is an additional effect if these similar items also belong to the same brand. Therefore, market thickness matters for consumer WTP. (2) More extensive site-surfing and bidding histories lead to lower WTP, implying that search costs and experience matter in bidding. As specific substantive benefits, we demonstrate how sellers can calculate changes in WTP, and hence the expected revenue, as the number of concurrently available similar items varies.