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Dynamic pricing for impatient bidders

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Bansal, Nikhil, Chen, Ning, Cherniavsky, Neva, Rurda, Atri, Schieber, Baruch and Sviridenko, Maxim. (2010) Dynamic pricing for impatient bidders. ACM Transactions on Algorithms , Vol.6 (No.2). pp. 1-21. ISSN 1549-6325

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1145/1721837.1721851

Abstract

We study the following problem related to pricing over time. Assume there is a collection of bidders, each of whom is interested in buying a copy of an item of which there is an unlimited supply. Every bidder is associated with a time interval over which the bidder will consider buying a copy of the item, and a maximum value the bidder is willing to pay for the item. On every time unit, the seller sets a price for the item. The seller's goal is to set the prices so as to maximize revenue from the sale of copies of items over the time period. In the first model considered, we assume that all bidders are impatient, that is, bidders buy the item at the first time unit within their bid interval that they can afford the price. To the best of our knowledge, this is the first work that considers this model. In the offline setting, we assume that the seller knows the bids of all the bidders in advance. In the online setting we assume that at each time unit the seller only knows the values of the bids that have arrived before or at that time unit. We give a polynomial time offline algorithm and prove upper and lower bounds on the competitiveness of deterministic and randomized online algorithms, compared with the optimal offline solution. The gap between the upper and lower bounds is quadratic. We also consider the envy-free model in which bidders are sold the item at the minimum price during their bid interval, as long as it is not over their limit value. We prove tight bounds on the competitiveness of deterministic online algorithms for this model, and upper and lower bounds on the competitiveness of randomized algorithms with quadratic gap. The lower bounds for the randomized case in both models use a novel general technique.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions: Faculty of Science > Computer Science
Journal or Publication Title: ACM Transactions on Algorithms
Publisher: Association for Computing Machinery, Inc.
ISSN: 1549-6325
Date: 2010
Volume: Vol.6
Number: No.2
Page Range: pp. 1-21
Identification Number: 10.1145/1721837.1721851
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
URI: http://wrap.warwick.ac.uk/id/eprint/42393

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