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Willingness to pay and competition in online auctions
The authors model how to measure consumer willingness to pay (WTP) using an English, or ascending first-price, auction based on two general bidding premises: No bidder bids more than his or her WTP, and no bidder allows a rival bidder to win at a price that he or she is willing to beat. In other words, the authors propose a "no-regret" rule in bidding. They impose no other restrictive assumptions on "maximands" or the bidders' behaviors in a competitive auction context. The authors model 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 items. The proposed model is general enough to include a "buy-it-now" (equivalent to a posted price) auction mechanism. The authors use data on notebook auctions from one of the largest Internet auction sites in Korea. They find that most product characteristics matter in the expected ways. There are two additional primary findings: First, 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. Second, more extensive site surfing and bidding histories lead to lower WTP, implying that search costs and experience matter in bidding. As specific substantive benefits, the authors demonstrate how sellers can calculate changes in WTP and, thus, the expected revenue as the number of concurrently available similar items varies.Printed Journal
Call Number | Location | Available |
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PSB lt.dasar - Pascasarjana | 1 |
Penerbit | American Marketing Association., |
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Edisi | - |
Subjek | Competition Economic models Auctions Electronic commerce Willingness to pay studies |
ISBN/ISSN | 222437 |
Klasifikasi | - |
Deskripsi Fisik | - |
Info Detail Spesifik | - |
Other Version/Related | Tidak tersedia versi lain |
Lampiran Berkas | Tidak Ada Data |