Last Minute Bidding and the Rules for Ending Second-Price Auctions: Theory and Evidence from a Natural Experiment on the Internet

By Alvin E. Roth, Axel Ockenfels. 2000

162 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Marketing, Safety Research

View Paper: https://www.semanticscholar.org/paper/dae8e679e40d88c0ca1e80c40a757b5c11aa78e4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Axel Ockenfels
2. Alvin E. Roth
3. Paul R. Milgrom
4. Richard J. Zeckhauser
5. Zuo-Jun Max Shen
6. Eric A. Walden
7. Xuanming Su
8. Paul Resnick

In Marketing

1. Alvin E. Roth
2. Axel Ockenfels
3. Zuo-Jun Max Shen
4. Paul R. Milgrom
5. Xuanming Su
6. Richard J. Zeckhauser
7. Paul Resnick
8. Robert J. Kauffman

In Safety Research

1. Richard J. Zeckhauser
2. Axel Ockenfels
3. Alvin E. Roth
4. Xuanming Su
5. Paul R. Milgrom
6. Zuo-Jun Max Shen
7. Paul Resnick
8. Ernst Fehr

Citations in the corpus

• Putting Auction Theory to Work (2004, background): “13 eBay also runs a similar auction, but its fixed ending time involves additional gaming issues as described by Roth and Ockenfels (2000).”
• Trust among strangers in internet transactions: Empirical analysis of eBay' s reputation system (2002, background): “We also plan to analyze whether negative feedback is correlated with decisions to stop participating altogether.”
• ADVERSE SELECTION IN ELECTRONIC MARKETS: EVIDENCE FROM ONLINE STAMP AUCTIONS (2004, background): “Roth and Ockenfels [2000] argue that late bidding need not arise from common value properties of the objects being sold, contending that bid sniping is driven by the fixed ending time of eBay auctions.”
• Economics and Electronic Commerce: Survey and Directions for Research (2001, background): “Roth and Ockenfels use this difference to evaluate bidder behavior [321].”
• Customer Behavior Modeling in Revenue Management and Auctions: A Review and New Research Opportunities (2007, background): “Their analysis reject the use of jump bidding (Avery 1998) or “snipe or war” bidding (Roth and Ockenfels 2000), even though they find that over 11% of the bids in their data sets were submitted in the last minute.”
• Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet (2002, methodology): “19 In Roth and Ockenfels (2000), we ran probit, logit, and ordinary least-squares (OLS) regressions using 5-, 10-, and 15-minute thresholds for late bidding, while controlling for the number of bidders per auction and bidders' feedback numbers.”