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Auctions, Market Mechanisms and Their Applications

Overview of attention for book
Cover of 'Auctions, Market Mechanisms and Their Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Effects of Suboptimal Bidding in Combinatorial Auctions
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    Chapter 2 Using Prediction Markets to Track Information Flows: Evidence from Google
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    Chapter 3 A Copula Function Approach to Infer Correlation in Prediction Markets
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    Chapter 4 Manipulating Scrip Systems: Sybils and Collusion
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    Chapter 5 A Centralized Auction Mechanism for the Disability and Survivors Insurance in Chile
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    Chapter 6 Information Feedback and Efficiency in Multiattribute Double Auctions
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    Chapter 7 Impact of Misalignment of Trading Agent Strategy across Multiple Markets
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    Chapter 8 Market Design for a P2P Backup System
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    Chapter 9 School Choice: The Case for the Boston Mechanism
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    Chapter 10 Turing Trade: A Hybrid of a Turing Test and a Prediction Market
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    Chapter 11 A Market-Based Approach to Multi-factory Scheduling
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    Chapter 12 Auctions with Dynamic Populations: Efficiency and Revenue Maximization
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    Chapter 13 Revenue Submodularity
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    Chapter 14 Fair Package Assignment
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    Chapter 15 Solving Winner Determination Problems for Auctions with Economies of Scope and Scale
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    Chapter 16 Running Out of Numbers: Scarcity of IP Addresses and What to Do about It
Attention for Chapter 12: Auctions with Dynamic Populations: Efficiency and Revenue Maximization
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Citations

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Chapter title
Auctions with Dynamic Populations: Efficiency and Revenue Maximization
Chapter number 12
Book title
Auctions, Market Mechanisms and Their Applications
Published in
ADS, May 2009
DOI 10.1007/978-3-642-03821-1_12
Book ISBNs
978-3-64-203820-4, 978-3-64-203821-1
Authors

Maher Said, Said, Maher

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 100%
Readers by discipline Count As %
Economics, Econometrics and Finance 1 100%

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