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Rationality, Irrationality and Escalating Behavior in Lowest Unique Bid Auctions

Overview of attention for article published in PLOS ONE, January 2012
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Title
Rationality, Irrationality and Escalating Behavior in Lowest Unique Bid Auctions
Published in
PLOS ONE, January 2012
DOI 10.1371/journal.pone.0029910
Pubmed ID
Authors

Filippo Radicchi, Andrea Baronchelli, Luís A. N. Amaral

Abstract

Information technology has revolutionized the traditional structure of markets. The removal of geographical and time constraints has fostered the growth of online auction markets, which now include millions of economic agents worldwide and annual transaction volumes in the billions of dollars. Here, we analyze bid histories of a little studied type of online auctions--lowest unique bid auctions. Similarly to what has been reported for foraging animals searching for scarce food, we find that agents adopt Lévy flight search strategies in their exploration of "bid space". The Lévy regime, which is characterized by a power-law decaying probability distribution of step lengths, holds over nearly three orders of magnitude. We develop a quantitative model for lowest unique bid online auctions that reveals that agents use nearly optimal bidding strategies. However, agents participating in these auctions do not optimize their financial gain. Indeed, as long as there are many auction participants, a rational profit optimizing agent would choose not to participate in these auction markets.

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Geographical breakdown

Country Count As %
United States 2 3%
Spain 1 1%
United Kingdom 1 1%
Japan 1 1%
Luxembourg 1 1%
Unknown 64 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Researcher 13 19%
Student > Master 11 16%
Professor > Associate Professor 6 9%
Lecturer 4 6%
Other 14 20%
Unknown 6 9%
Readers by discipline Count As %
Physics and Astronomy 10 14%
Computer Science 10 14%
Agricultural and Biological Sciences 7 10%
Social Sciences 7 10%
Economics, Econometrics and Finance 5 7%
Other 22 31%
Unknown 9 13%