research-article

Online auctions efficiency: a survey of ebay auctions

Authors:

Wenyan Hu,

Alvaro BolivarAuthors Info & Claims

WWW '08: Proceedings of the 17th international conference on World Wide Web

Pages 925 - 934

https://doi.org/10.1145/1367497.1367621

Published: 21 April 2008 Publication History

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Abstract

Online auctions have become a pervasive transaction mechanism for e-commerce. As the largest online marketplace in the world, eBay is an attractive case study that enables the study of online auctions utilizing data involving real people and transactions.

In this paper, we present a detailed investigation and analysis of multiple online auction properties including: consumer surplus, sniping, bidding strategy and their cross-relationships. Our goal is to evaluate the theoretical foundations of online auctions and discover patterns and behaviors hidden due to the lack of real and extensive transaction data. Among our findings, we uncover an important correlation among sniping and high surplus ratios, which implies the uncertainty of true value in a competitive environment. The key issue is the wrong assumption that bidders' valuations are independent from each other, which leads to inefficient auctions.

In order to address the inefficiencies of current online formats we introduce a declining price auction model customized for online transactions. Conceptually, this model ought to deal with the complexities of competition in an online environment while maximizing social welfare.

References

[1]

Alvin E. Roth and Axel Ockenfels. Last-Minute Bidding and the Rules for Ending Second-Price Auctions: Evidence from eBay and Amazon Auctions on the Internet. The American Economic Review, 92(4):1093--1103, September 2002.

Crossref

Google Scholar

[2]

Axel Ockenfelsa and Alvin E. Roth. Late and Multiple Bidding in Second Price Internet Auctions: Theory and Evidence Concerning Different Rules for Ending an Auction. Games and Economic Behavior, 55(2):297--320, May 2006.

Crossref

Google Scholar

[3]

Wenli Wang, Zoltan Hidvegi, and Andrew B. Whinston. Shill-Proof Fee (SPF) Schedule: the Sunscreen against Seller Self-Collusion in Online English Auctions. October 2004. http://www.wenli.net/Application/Wenli-Shill.pdf.

Google Scholar

[4]

Salvatore Barbaro and Bernd Bracht. Shilling, Squeezing, Sniping: Explaining Late Bidding in Online Second-price Auctions. January 2006. http://www.staff.uni-mainz.de/barbaro/BarbaroBracht.pdf.

Google Scholar

[5]

Sean Gray and David Reiley. Measuring the Benefits to Sniping on eBay: Evidence from a Field Experiment. April 2007. http://www.u.arizona.edu/~dreiley/papers/Sniping.pdf.

Google Scholar

[6]

Ronald T. Wilcox. Experts and Amateurs: The Role of Experience in Internet Auctions. Marketing Letters, 11(4):363--374, November 2000.

Crossref

Google Scholar

[7]

Axel Ockenfels and Alvin E. Roth. The Timing of Bids in Internet Auctions: Market Design, Bidder Behavior, and Artificial Agents. Artificial Intelligence Magazine, 23(3):79--87, 2002.

Digital Library

Google Scholar

[8]

Ravi Bapna, Wolfgang Jank, and Galit Shmueli. Consumer Surplus in Online Auctions. July 2006. http://www.smith.umd.edu/faculty/wjank/consumerSurplusOnlineAuctions-ISR.pdf.

Google Scholar

[9]

Erik Brynjolfsson, Yu (Jeffrey) Hu, and Michael D. Smith. Consumer Surplus in the Digital Economy: Estimating the Value of Increased Product Variety at Online Booksellers. Management Science, 49(11):1580--1596, November 2003.

Digital Library

Google Scholar

[10]

Jeffrey C. Ely and Tanjim Hossain. Sniping and Squatting in Auction Markets. July 2006. http://ihome.ust.hk/~tanjim/squat.pdf.

Google Scholar

[11]

Tugba Giray, Kevin Hasker, and Robin Sickles. Estimating Consumer Surplus in eBay Computer Monitor Auctions. November 2006. http://www.bilkent.edu.tr/~hasker/Research/Giray-Hasker-Sickles-CS-eBay-06-02-23.pdf.

Google Scholar

[12]

William Vickrey. Counterspeculation, Auctions, and Competitive Sealed Tenders. The Journal of Finance, 16(1):8--37, March 1961.

Crossref

Google Scholar

[13]

David Lucking-Reiley. Using Field Experiments to Test Equivalence Between Auction Formats: Magic on the Internet. The American Economic Review, 89(5):1063--1080, December 1999.

Crossref

Google Scholar

Cited By

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Emami AKeshavarz Kalhori GMirzakhani SAkhaee M(2023)A blockchain-based privacy-preserving anti-collusion data auction mechanism with an off-chain approachThe Journal of Supercomputing10.1007/s11227-023-05736-980:6(7507-7556)Online publication date: 8-Nov-2023
https://doi.org/10.1007/s11227-023-05736-9
Pei J(2022)A Survey on Data Pricing: From Economics to Data ScienceIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.304592734:10(4586-4608)Online publication date: 1-Oct-2022
https://doi.org/10.1109/TKDE.2020.3045927
Baarslag TKaisers MGerding EJonker CGratch J(2022)Self-sufficient, Self-directed, and Interdependent Negotiation Systems: A Roadmap Toward Autonomous Negotiation AgentsBargaining10.1007/978-3-030-76666-5_18(387-406)Online publication date: 19-Apr-2022
https://doi.org/10.1007/978-3-030-76666-5_18
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Index Terms

Online auctions efficiency: a survey of ebay auctions
1. Information systems
  1. Information systems applications

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Published In

WWW '08: Proceedings of the 17th international conference on World Wide Web

April 2008

1326 pages

ISBN:9781605580852

DOI:10.1145/1367497

General Chairs:
Jinpeng Huai
Beihang University, China
,
Robin Chen
AT&T Labs, USA
,
Hsiao-Wuen Hon
Microsoft Research Asia, China
,
Yunhao Liu
HK University of Science and Technology, Hong Kong
,
Program Chairs:
Wei-Ying Ma
Microsoft Research Asia, China
,
Andrew Tomkins
Yahoo! Research, USA
,
Xiaodong Zhang
The Ohio State University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2008

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Beijing, China

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Emami AKeshavarz Kalhori GMirzakhani SAkhaee M(2023)A blockchain-based privacy-preserving anti-collusion data auction mechanism with an off-chain approachThe Journal of Supercomputing10.1007/s11227-023-05736-980:6(7507-7556)Online publication date: 8-Nov-2023
https://doi.org/10.1007/s11227-023-05736-9
Pei J(2022)A Survey on Data Pricing: From Economics to Data ScienceIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2020.304592734:10(4586-4608)Online publication date: 1-Oct-2022
https://doi.org/10.1109/TKDE.2020.3045927
Baarslag TKaisers MGerding EJonker CGratch J(2022)Self-sufficient, Self-directed, and Interdependent Negotiation Systems: A Roadmap Toward Autonomous Negotiation AgentsBargaining10.1007/978-3-030-76666-5_18(387-406)Online publication date: 19-Apr-2022
https://doi.org/10.1007/978-3-030-76666-5_18
Rosenfeld AKraus S(2018)Predicting Human Decision-Making: From Prediction to ActionSynthesis Lectures on Artificial Intelligence and Machine Learning10.2200/S00820ED1V01Y201712AIM03612:1(1-150)Online publication date: 22-Jan-2018
https://doi.org/10.2200/S00820ED1V01Y201712AIM036
Baarslag TKaisers MGerding EJonker CGratch J(2017)When will negotiation agents be able to represent us? the challenges and opportunities for autonomous negotiatorsProceedings of the 26th International Joint Conference on Artificial Intelligence10.5555/3171837.3171943(4684-4690)Online publication date: 19-Aug-2017
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Baarslag TKaisers MGerding EJonker CGratch J(2017)Computers That Negotiate on Our Behalf: Major Challenges for Self-sufficient, Self-directed, and Interdependent Negotiating AgentsAutonomous Agents and Multiagent Systems10.1007/978-3-319-71679-4_10(143-163)Online publication date: 25-Nov-2017
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Sow JAnthony PHo C(2013)Analyzing the performance of multiple agents with varying bidding behaviors and standard bidders in online auctionsWeb Intelligence and Agent Systems10.5555/2590084.259009011:2(185-199)Online publication date: 1-Apr-2013
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Guo SWang MLeskovec JShoham YChen YRoughgarden T(2011)The role of social networks in online shoppingProceedings of the 12th ACM conference on Electronic commerce10.1145/1993574.1993598(157-166)Online publication date: 5-Jun-2011
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Kamins MNoy ASteinhart YMazursky D(2011)The Effect of Social Cues on Sniping Behavior in Internet Auctions: Field Evidence and a Lab ExperimentJournal of Interactive Marketing10.1016/j.intmar.2011.03.00225:4(241-250)Online publication date: 1-Nov-2011
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Ma HHu WLeung H(2010)Enhancing Continuous Double Auction for Handling Homogeneous Goods in Online AuctionsProceedings of the 12th IEEE International Conference on Commerce and Enterprise Computing10.1109/CEC.2010.28(32-39)Online publication date: 10-Nov-2010
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Recommendations

The effects of proxy bidding and minimum bid increments within eBay auctions

Overlapping online auctions: empirical characterization of bidder strategies and auction prices

Temporary and Permanent Buyout Prices in Online Auctions

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