An investigation of value updating bidders in simultaneous online art auctions

Mayukh Dass, Lynne Seymour, Srinivas K. Reddy

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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 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.

Original languageEnglish
Article number539763
JournalJournal of Probability and Statistics
DOIs
StatePublished - 2010

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