Journal of Probability and Statistics
Volume 2010 (2010), Article ID 539763, 18 pages
Research Article

An Investigation of Value Updating Bidders in Simultaneous Online Art Auctions

1Rawls College of Business, Texas Tech University, Lubbock, TX 79409, USA
2Department of Statistics, University of Georgia, 205 Statistics Building, Athens, GA 30602, USA
3Center for Marketing Excellence, Lee Kong Chian School of Business, Singapore Management University, 50 Stamford Road #05-01, 178899, Singapore

Received 2 July 2009; Revised 18 November 2009; Accepted 16 February 2010

Academic Editor: V. V. Anh

Copyright © 2010 Mayukh Dass et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Simultaneous online auctions, in which the auction of all items being sold starts at the same time and ends at the same time, are becoming popular especially in selling items such as collectables and art pieces. In this paper, we analyze the characteristics of bidders (Reactors) in simultaneous auctions who update their preauction value of an item in the presence of influencing bidders (Influencers). We represent an auction as a network of bidders where the nodes represent the bidders participating in the auction and the ties between them represent an Influencer-Reactor relationship. We further develop a random effects bilinear model that is capable of handling covariates of both bidder types at the same time and account for higher-order dependence among the bidders during the auction. Using the model and data from a Modern Indian Art auction, we find that Reactors tend to update their values on items that have high preauction estimates, bid on items created by high investment risk artists, bid selectively only on certain items, and are more active in the second half of the auction. Implications for the auction house managers are discussed.