Capacity constraints and the inevitability of mediators in adword auctions

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Abstract

One natural constraint in the sponsored search advertising framework arises from the fact that there is a limit on the number of available slots, especially for the popular keywords, and as a result, a significant pool of advertisers are left out. We study the emergence of diversification in the adword market triggered by such capacity constraints in the sense that new market mechanisms, as well as, new for-profit agents are likely to emerge to combat or to make profit from the opportunities created by shortages in ad-space inventory. We propose a model where the additional capacity is provided by for-profit agents (or, mediators), who compete for slots in the original auction, draw traffic, and run their own sub-auctions. The quality of the additional capacity provided by a mediator is measured by its fitness factor. We compute revenues and payoffs for all the different parties at a symmetric Nash equilibrium (SNE) when the mediator-based model is operated by a mechanism currently being used by Google and Yahoo!, and then compare these numbers with those obtained at a corresponding SNE for the same mechanism, but without any mediators involved in the auctions. Such calculations allow us to determine the value of the additional capacity. Our results show that the revenue of the auctioneer, as well as the social value (i.e. efficiency ), always increase when mediators are involved; moreover even the payoffs of all the bidders will increase if the mediator has a high enough fitness. Thus, our analysis indicates that there are significant opportunities for diversification in the internet economy and we should expect it to continue to develop richer structure, with room for different types of agents and mechanisms to coexist. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Singh, S. K., Roychowdhury, V. P., Gunadhi, H., & Rezaei, B. A. (2007). Capacity constraints and the inevitability of mediators in adword auctions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4858 LNCS, pp. 318–325). Springer Verlag. https://doi.org/10.1007/978-3-540-77105-0_33

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