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This paper surveys recent studies of internet auctions. Four main areas of research are summarized. First, we survey several studies that document and attempt to explain the frequently observed sniping, or last-second bidding behavior, in these auctions. Second, we summarize several methods proposed to quantify the distortions caused by asymmetric information in these markets, most notably due to the winner's curse. Third, we explore research about the role of reputation mechanisms installed to help combat these distortions. Finally, we discuss what internet auctions have to teach us about auction design.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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