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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 38% |
United States | 2 | 25% |
Unknown | 3 | 38% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 88% |
Scientists | 1 | 13% |
Mendeley readers
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% |