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 Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/27183

 Title: Revenue maximization in the dynamic knapsack problem Authors: Deniz Dizdar; Department of Economics, Bonn UniversityAlex Gershkov; Department of Economics, Hebrew University of JerusalemBenny Moldovanu; Department of Economics, Bonn University Keywords: Knapsack, revenue maximization, dynamic mechanism designD42, D44 Issue Date: 3-May-2011 Publisher: Theoretical Economics Citation: Theoretical Economics; Vol 6, No 2 (2011) Abstract: [This item is a preserved copy. To view the original, visit http://econtheory.org/] We analyze maximization of revenue in the dynamic and stochastic knapsack problem where a given capacity needs to be allocated by a given deadline to sequentially arriving agents. Each agent is described by a two-dimensional type that reflects his capacity requirement and his willingness to pay per unit of capacity. Types are private information. We first characterize implementable policies. Then we solve the revenue maximization problem for the special case where there is private information about per-unit values, but capacity needs are observable. After that we derive two sets of additional conditions on the joint distribution of values and weights under which the revenue maximizing policy for the case with observable weights is implementable, and thus optimal also for the case with two-dimensional private information. In particular, we investigate the role of concave continuation revenues for implementation. We also construct a simple policy for which per-unit prices vary with requested weight but not with time, and prove that it is asymptotically revenue maximizing when available capacity/ time to the deadline both go to infinity. This highlights the importance of nonlinear as opposed to dynamic pricing. URI: http://hdl.handle.net/1807/27183 Other Identifiers: http://econtheory.org/ojs/index.php/te/article/view/20110157 Rights: Authors who publish in Theoretical Economics will release their articles under the Creative Commons Attribution-NonCommercial license. This license allows anyone to copy and distribute the article for non-commercial purposes provided that appropriate attribution is given. Appears in Collections: Volume 6, Number 2 (May 2011)

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