Abstract
Recent years have witnessed a growing interest in analyzing a variety of socio-economic phenomena using methods from statistical and nonlinear physics. We study a class of complex systems arising from economics, the lowest unique bid auction (LUBA) systems, which is a recently emerged class of online auction game systems. Through analyzing large, empirical data sets of LUBA, we identify a general feature of the bid price distribution: an inverted J-shaped function with exponential decay in the large bid price region. To account for the distribution, we propose a multi-agent model in which each agent bids stochastically in the field of winner’s attractiveness, and develop a theoretical framework to obtain analytic solutions of the model based on mean field analysis. The theory produces bid-price distributions that are in excellent agreement with those from the real data. Our model and theory capture the essential features of human behaviors in the competitive environment as exemplified by LUBA, and may provide significant quantitative insights into complex socio-economic phenomena.
Highlights
In recent years, theories and methods of statistical and nonlinear physics have been used to understand a variety of complex social and economical phenomena [1,2,3,4,5,6,7,8,9,10]
Guided by this basic principle from statistical physics, in this paper we study a class of complex economical systems: online auction systems for which a large amount of empirical data is available
Online auctions represent an important type of socio-economical activities in the modern world
Summary
Any further distribution of Recent years have witnessed a growing interest in analyzing a variety of socio-economic phenomena this work must maintain using methods from statistical and nonlinear physics. We study a class of complex systems arising attribution to the author(s) and the title of from economics, the lowest unique bid auction (LUBA) systems, which is a recently emerged class of the work, journal citation and DOI. Empirical data sets of LUBA, we identify a general feature of the bid price distribution: an inverted J-shaped function with exponential decay in the large bid price region. Our model and theory capture the essential features of human behaviors in the competitive environment as exemplified by LUBA, and may provide significant quantitative insights into complex socio-economic phenomena
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