Publication statistics

Pub. period:2002-2007
Pub. count:4
Number of co-authors:2


Number of publications with 3 favourite co-authors:

David M. Pennock:
Hemant K. Bhargava:



Productive colleagues

Juan Feng's 3 most productive colleagues in number of publications:

Hemant K. Bhargava:17
David M. Pennock:12

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Juan Feng


Publications by Juan Feng (bibliography)

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Bhargava, Hemant K. and Feng, Juan (2007): The impact of sponsored results on the quality of information gatekeepers. In: Gini, Maria L., Kauffman, Robert J., Sarppo, Donna, Dellarocas, Chrysanthos and Dignum, Frank (eds.) Proceedings of the 9th International Conference on Electronic Commerce - ICEC 2007 August 19-22, 2007, Minneapolis, MN, USA. pp. 147-152.

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Bhargava, Hemant K. and Feng, Juan (2004): Pure Bundling Better than Mixed? Or, Why doesn?t AOL Offer Standardized Dial-Up Service?. In: HICSS 2004 2004. .

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Feng, Juan, Bhargava, Hemant K. and Pennock, David M. (2003): Comparison of allocation rules for paid placement advertising in search engines. In: Sadeh, Norman M., Dively, Mary Jo, Kauffman, Robert J., Labrou, Yannis, Shehory, Onn, Telang, Rahul and Cranor, Lorrie Faith (eds.) Proceedings of the 5th International Conference on Electronic Commerce - ICEC 2003 September 30 - October 03, 2003, Pittsburgh, Pennsylvania, USA. pp. 294-299.

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Bhargava, Hemant K. and Feng, Juan (2002): Paid placement strategies for internet search engines. In: Proceedings of the 2002 International Conference on the World Wide Web 2002. pp. 117-123.

Internet search engines and comparison shopping have recently begun implementing a paid placement strategy, where some content providers are given prominent positioning in return for a placement fee. This bias generates placement revenues but creates a disutility to users, thus reducing user-based revenues. We formulate the search engine design problem as a tradeoff between these two types of revenues. We demonstrate that the optimal placement strategy depends on the relative benefits (to providers) and disutilities (to users) of paid placement. We compute the optimal placement fee, characterize the optimal bias level, and analyze sensitivity of the placement strategy to various factors. In the optimal paid placement strategy, the placement revenues are set below the monopoly level due to its negative impact on advertising revenues. An increase in the search engine's quality of service allows it to improve profits from paid placement, moving it closer to the ideal. However, an increase in the value-per-user motivates the gatekeeper to increase market share by reducing further its reliance on paid placement and fraction of paying providers.

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