Economics at your fingertips  

The Psychological Force Model for Lowest Unique Bid Auction

Rui Hu, Jinzhong Guo, Qinghua Chen () and Tao Zheng
Additional contact information
Rui Hu: Beijing Normal University
Jinzhong Guo: Xinjiang University
Qinghua Chen: Beijing Normal University
Tao Zheng: Beijing Normal University

Computational Economics, 2017, vol. 50, issue 4, No 6, 655-667

Abstract: Abstract We study a type of complex system arising from economics, the lowest unique bid auction (LUBA) system which is a new generation of online markets. Different from the traditional auction in which the winner is who bids the highest price, in LUBA, the winner is whoever places the lowest of all unique bids. In this paper, we propose a multi-agent model to factually describes the human psychologies of the decision-making process in LUBA. The model produces bid-price distributions that are in excellent agreement with those from the real data, including the whole inverted-J shape which is a general feature of the real bid price distribution, and the exponential decreasing shape in the higher price range. This implies that it is possible for us to capture the essential features of human psychologies in the competitive environment as exemplified by LUBA and that we may provide significant quantitative insights into complex socio-economic phenomena.

Keywords: Lowest unique bid auction; Psychological force; Multi-agent model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link) Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10614/PS2

DOI: 10.1007/s10614-016-9614-z

Access Statistics for this article

Computational Economics is currently edited by Hans Amman

More articles in Computational Economics from Springer, Society for Computational Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla ().

Page updated 2020-04-28
Handle: RePEc:kap:compec:v:50:y:2017:i:4:d:10.1007_s10614-016-9614-z