Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2010
Abstract
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 pre-auction 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 pre-auction 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.
Discipline
Arts Management | Management Sciences and Quantitative Methods | Marketing
Research Areas
Marketing
Publication
Journal of Probability and Statistics
Volume
2010
First Page
1
Last Page
18
ISSN
1687-952X
Identifier
10.1155/2010/539763
Publisher
Hindawi
Citation
DASS, Mayukh; SEYMOUR, Lynne; and REDDY, Srinivas K..
An Investigation of Value Updating Bidders in Simultaneous Online Art Auctions. (2010). Journal of Probability and Statistics. 2010, 1-18.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/1868
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1155/2010/539763
Included in
Arts Management Commons, Management Sciences and Quantitative Methods Commons, Marketing Commons