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Abstract
The growing popularity of online auctions and the availability of rich and detailed biddingdata have spawned many new empirical researches in auctions that were not possibleto explore earlier. Particularly, more information is now known about bidder behavior inauctions than ever before. Still, there are certain auction characteristics that desire for moreresearch. One such area is bidder competition in auctions. Current view on this topic considerseach bidder to compete against all the other bidders as a whole, without distinguishingone competitor from another. This consideration is inadequate in explaining the effects ofdifferent levels of rivalry between bidder pairs. To overcome this limitation, this dissertationpresents an innovative approach of looking at bidder competition at a dyadic bidder level.The context of the study is simultaneous online auctions selling modern Indian art. Simultaneousauction, a popular online auction format for selling highly complementary productsis ideal for such study as bidders in these auctions typically compete for more than one lot(item) simultaneously, thus engaging in both within-lot and between-lot interaction (competition).This dissertation consists of two essays. The first essay shows that after controllingfor aggregate level of competition, dyadic bidder interactions have significant effect on theauction outcome. Extending on these findings, a new approach of representing bidding datais presented. Each bidder is connected based on the dyadic interactions between them and abidder network is formed. Using the analytical tools from Social Network Analysis, the keyor important bidders in the network are identified and their effect on the auction outcomeis analyzed. In the second essay, dyadic bidder interactions are used to analyze situationswhere bidders reevaluate or update their reservation value for the item. Using choice models,it is established that high level of between-lot interaction has a significant effect on thepropensity of this behavior. The notion of dyadic interaction is further extended to analyzecharacteristics of bidders (termed here as Reactors) who change their pre-set reservationvalue for the item.