Information Technology Reference
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for a fee (e.g. an analyst) or large information service providers such as car-
fax.com or credit report companies. It is commonly assumed that these informa-
tion providers indeed can control the level of accuracy they offer their customers.
Moreover, the accuracy of the information provided depends on the customer's
cooperation and the level of the inputs she provides. Against this background,
the importance of this equilibrium construction and analysis for auctioneers or
the information providers is clear, especially, in terms of the ability to control
the granularity in which information is provided.
Here, we show an interesting phenomenon where the auctioneer may benefit
in cases where the information provider cannot fully identify the exact state of
nature, even though the information is eventually offered exclusively to the auc-
tioneer. This phenomenon is explained by the stability requirement - beneficial
solutions that could not hold with the complete (”perfect”) information scheme,
because of stability considerations, are found to be stable once the information
being offered for sale is constrained.
Acknowledgment. This work was supported in part by the Israeli Science
Foundation grant no. 1083/13.
References
1. Akerlof, G.: The market for “lemons”: Quality uncertainty and the market mech-
anism. The Quarterly Journal of Economics 84(3), 488-500 (1970),
http://www.jstor.org/stable/1879431
2. Azoulay, R., David, E.: Truthful and ecient mechanisms for site oriented adver-
tizing auctions, multiagent and grid systems. An International Journal Press 10(2),
67-94 (2014)
3. Bagnall, A., Toft, I.: Autonomous adaptive agents for single seller sealed bid auc-
tions. Autonomous Agents and Multi-Agent Systems 12(3), 259-292 (2006)
4. Board, S.: Revealing information in auctions: the allocation effect. Economic The-
ory 38(1), 125-135 (2009)
5. Bredin, J., Parkes, D., Duong, Q.: Chain: A dynamic double auction framework
for matching patient agents. Journal of Artificial Intelligence Research (JAIR) 30,
133-179 (2007)
6. David, E., Azoulay-Schwartz, R., Kraus, S.: Bidding in sealed-bid and english
multi-attribute auctions. Decision Support Systems 42(2), 527-556 (2006)
7. David, E., Manisterski, E.: Strategy proof mechanism for complex task allocations
in prior consent for subtasks completion environment. In: IAT, pp. 209-215 (2013)
8. Dobzinski, S., Nisan, N.: Mechanisms for multi-unit auctions. Journal of Artificial
Intelligence Research (JAIR) 37, 85-98 (2010)
9. Dufwenberg, M., Gneezy, U.: Information disclosure in auctions: an experiment.
Journal of Economic Behavior & Organization 48(4), 431-444 (2002)
10. Dughmi, S., Immorlica, N., Roth, A.: Constrained signaling for welfare and revenue
maximization. ACM SIGecom Exchanges 12(1), 53-56 (2013)
11. Emek, Y., Feldman, M., Gamzu, I., Leme, R., Tennenholtz, M.: Signaling schemes
for revenue maximization. In: Proceedings of the 12th ACM Conference on Elec-
tronic Commerce (EC 2012), pp. 514-531 (2012)
 
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