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Network Formation and the Structure of the Commercial World Wide Web

Author

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  • Zsolt Katona

    (Haas School of Business, University of California at Berkeley, Berkeley, California 94720-1900)

  • Miklos Sarvary

    (INSEAD, 77305 Fontainebleau, France)

Abstract

We model the commercial World Wide Web as a directed graph that emerges as the equilibrium of a game in which utility maximizing websites purchase (advertising) in-links from each other while also setting the price of these links. In equilibrium, higher content sites tend to purchase more advertising links (mirroring the Dorfman-Steiner rule) while selling less advertising links themselves. As such, there seems to be specialization across sites in revenue models: high content sites tend to earn revenue from the sales of content, whereas low content ones earn revenue from the sales of traffic (advertising). In an extension, we also allow sites to establish (reference) out-links to each other and find that there is a general tendency to establish reference links to sites with higher content. Finally, we explore network formation in the presence of search engines and find that the higher the proportion of people using them, the more sites have an incentive to specialize in certain content areas. Our results have interesting practical implications for search-engine optimization, the pricing of online advertising, and the choice of Internet business models. They also shed light on why Google can use the web's link structure to rank sites by content.

Suggested Citation

  • Zsolt Katona & Miklos Sarvary, 2008. "Network Formation and the Structure of the Commercial World Wide Web," Marketing Science, INFORMS, vol. 27(5), pages 764-778, 09-10.
  • Handle: RePEc:inm:ormksc:v:27:y:2008:i:5:p:764-778
    DOI: 10.1287/mksc.1070.0349
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    References listed on IDEAS

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    1. Yann Bramoullé & Dunia López-Pintado & Sanjeev Goyal & Fernando Vega-Redondo, 2004. "Network formation and anti-coordination games," International Journal of Game Theory, Springer;Game Theory Society, vol. 33(1), pages 1-19, January.
    2. Brian Kahin & Hal R. Varian (ed.), 2000. "Internet Publishing and Beyond: The Economics of Digital Information and Intellectual Property," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262611597, April.
    3. Schmalensee, Richard, 1978. "A Model of Advertising and Product Quality," Journal of Political Economy, University of Chicago Press, vol. 86(3), pages 485-503, June.
    4. Mark Armstrong & Robert Porter (ed.), 2007. "Handbook of Industrial Organization," Handbook of Industrial Organization, Elsevier, edition 1, volume 3, number 1.
    5. J. Miguel Villas-Boas, 2004. "Communication Strategies and Product Line Design," Marketing Science, INFORMS, vol. 23(3), pages 304-316, January.
    6. Jackson, Matthew O. & Wolinsky, Asher, 1996. "A Strategic Model of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 71(1), pages 44-74, October.
    7. Deepak Agrawal, 1996. "Effect of Brand Loyalty on Advertising and Trade Promotions: A Game Theoretic Analysis with Empirical Evidence," Marketing Science, INFORMS, vol. 15(1), pages 86-108.
    8. Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
    9. Bagwell, Kyle, 2007. "The Economic Analysis of Advertising," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 28, pages 1701-1844, Elsevier.
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    4. Peitz, Martin & Reisinger, Markus, 2014. "The Economics of Internet Media," Working Papers 14-23, University of Mannheim, Department of Economics.
    5. James Rutt, 2011. "Aggregators and the News Industry: Charging for Access to Content," Working Papers 11-19, NET Institute, revised Sep 2011.
    6. He, Qiao-Chu, 2017. "Virtual items trade in online social games," International Journal of Production Economics, Elsevier, vol. 187(C), pages 1-14.
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    10. Calzada, Joan & Tselekounis, Markos, 2018. "Net Neutrality in a hyperlinked Internet economy," International Journal of Industrial Organization, Elsevier, vol. 59(C), pages 190-221.
    11. Kummer, Michael E. & Saam, Marianne & Halatchliyski, Iassen & Giorgidze, George, 2016. "Centrality and content creation in networks - The case of economic topics on German wikipedia," Information Economics and Policy, Elsevier, vol. 36(C), pages 36-52.
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    15. Tianshu Sun & Sean J. Taylor, 2020. "Displaying things in common to encourage friendship formation: A large randomized field experiment," Quantitative Marketing and Economics (QME), Springer, vol. 18(3), pages 237-271, September.
    16. Saeed Tajdini, 2023. "The effects of internet search intensity for products on companies’ stock returns: a competitive intelligence perspective," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(3), pages 352-365, September.
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    19. Gal OEstreicher-Singer & Barak Libai, 2011. "Assessing Value in Product Networks," Working Papers 11-29, NET Institute, revised Sep 2011.
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    22. Arun Sundararajan & Foster Provost & Gal Oestreicher-Singer & Sinan Aral, 2013. "Research Commentary ---Information in Digital, Economic, and Social Networks," Information Systems Research, INFORMS, vol. 24(4), pages 883-905, December.

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