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Abstract

The recent advancements in network data modeling such as bilinear mixed models haveopened doors to many other social researches that were not possible to explore earlier. Inthis thesis, we demonstrate an application of a bilinear mixed model for a complex humanbehavior such as overbidding in auctions, i.e. placing a bid of higher value than his or herpreset valuation of the item.We use an innovative approach of illustrating auction data in theform of a network. The rich network framework allows us to consider bidder interdependenceand examine overbidders (termed in the study as Reactors) in the presence of bidders whohave influenced them to do so (termed here as Influencers). Results show that Reactors bidon fewer items, but on those with high pre-auction estimated values. They also tend to bidmore in the second half of the auction as compared to the first half. Implications for theauction house managers were also presented.

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