We consider a dynamic auction problem motivated by the traditional single-leg, multi-period revenue management problem. A seller with C units to sell faces potential buyers with unit demand who arrive and depart over the course of T time periods. The time at which a buyer arrives, her value for a unit as well as the time by which she must make the purchase are private information. In this environment, we derive the revenue maximizing Bayesian incentive compatible selling mechanism.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
Publisher Info
Paper provided by Northwestern University, Center for Mathematical Studies in Economics and Management Science in its series Discussion Papers with number
1461.
Length: Date of creation: Mar 2008 Date of revision: Handle: RePEc:nwu:cmsems:1461
Contact details of provider: Postal: Center for Mathematical Studies in Economics and Management Science, Northwestern University, 580 Jacobs Center, 2001 Sheridan Road, Evanston, IL 60208-2014 Phone: 847/491-3527 Fax: 847/491-2530 Email: Web page: http://www.kellogg.northwestern.edu/research/math/ More information through EDIRC
Order Information: Email:
For technical questions regarding this item, or to correct its listing, contact: (Fran Walker).
Find related papers by JEL classification: D44 - Microeconomics - - Market Structure and Pricing - - - Auctions C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
This paper has been announced in the following NEP Reports:
References listed on IDEAS Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
Did you know? Citation analysis on IDEAS includes online papers that are freely accessible and whose text could be automatically analyzed, currently about 150000 papers.