Abstract
Advertisements on the webpage provide good opportunity to get new customers. In recent years, a lot of webpages providing a search service have advertisements, which are related with searched word by user. A basic structure of the Internet advertisement is that the service providers decide order of placement of many advertisements and advertising fees by auctions when advertisers offer their promotions. Generalized Second Price Auction (GSP) mechanism is most efficient auction mechanism of the advertisement auction. Some searching companies, such as Google and Yahoo, employ GSP mechanism basically. There are many researches on GSP in order to analyze and clarify its feature and advantages. However, these researches assume that traded advertisements are mutually independent. It means that each advertisement does not influence other advertisements. Also these researches do not consider a value of advertisement, which means some criterions of a name value of a company, an effectiveness and an importance, that is dependently each other. This paper proposes a new advertisement auction mechanism based on GSP with considering the co-dependent value of advertisement. We analyze the auctioneer’s profit in comparison between normal GSP, normal VCG (Vickrey-Clarke-Groves Mechanism) and our proposed mechanism.
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References
Edelman, B., Ostrivsky, M., Schwarz, M.: Internet Advertising and the Generalized Second-Price Auction Selling of Dollars Worth of Keywords. The American Economic Review (2005)
Vickrey, W.: Couterspeculation, Auctions, and Competitive Sealed Tenders. Journal of Finance (1961)
Krishna, V.: Auction Theory. Academic Press (2002)
Edelman, B., Ostrovsky, M., Schwarz, M.: Internet Advertising and the Generalized Second Price Auction: Selling Billions of Dollars Worth of Keywords. American Economic Review 9(1), 242–259 (2007)
Brooks, N.: The Atlas Rank Report: How Search Engine Rank Impact Traffic. Insights, Atlas Institute Digital Marketing (2004)
Milgrom, P.: Putting Auction Theory to Work. Cambridge University Press (2004)
Varian, H.R.: Position auctions. International Journal of Industrial Organization (2005)
Abrams, Z., Schwarz, M.: Ad Auction Design and User Experience. In: Deng, X., Graham, F.C. (eds.) WINE 2007. LNCS, vol. 4858, pp. 529–534. Springer, Heidelberg (2007)
Guruswami, V., Hartline, J.D., Karlin, A.R., Kempe, D., Kenyon, C., McSherry, F.: On profit-maximizing envy-free pricing. In: Proceedings of the Sixteenth Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 1164–1173 (2005)
http://www-01.ibm.com/software/integration/optimization/cplex-optimizer
Ahuja, R.K., Magnanti, T.L., Orlin, J.B.: Network Flows: Theory, Algorithms, and Applications. Prentice Hall (1993)
Korte, B.H., Vygen, J.: Combinatorial optimization: theory and algorithms. Springer (2008)
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Takahashi, S., Matsuo, T., Ito, T., Lee, R.Y. (2012). A Co-dependent Value-Based Mechanism for the Internet Advertisement Auction. In: Cranefield, S., Song, I. (eds) Agent Based Simulation for a Sustainable Society and Multi-agent Smart Computing. PRIMA 2011. Lecture Notes in Computer Science(), vol 7580. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35612-4_5
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DOI: https://doi.org/10.1007/978-3-642-35612-4_5
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