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Negotiation, Auctions, and Market Engineering

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Cover of 'Negotiation, Auctions, and Market Engineering'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Market Engineering: A Research Agenda
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    Chapter 2 On Comparison of Mechanisms of Economic and Social Exchanges: The Times Model
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    Chapter 3 A Decision Support System for Choosing Market Mechanisms in e-Procurement
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    Chapter 4 Applying Auction Theory to Procurement Auctions – An Empirical Study Among German Corporations
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    Chapter 5 On the Design of Simple Multi-unit Online Auctions
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    Chapter 6 A Comparison Between Mechanisms for Sequential Compute Resource Auctions
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    Chapter 7 MACE: A Multi-attribute Combinatorial Exchange
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    Chapter 8 Engineering Grid Markets
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    Chapter 9 Shaman: Software and Human Agents in Multiattribute Auctions and Negotiations
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    Chapter 10 An Experiment on Investor Behavior in Markets with Nonlinear Transaction Fees
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    Chapter 11 Sellers Competing for Buyers in Online Markets
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    Chapter 12 A Bayesian Reputation System for Virtual Organizations
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    Chapter 13 Situated Decision Support Approach for Managing Multiple Negotiations
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    Chapter 14 Optimal Financially Constrained Bidding in Multiple Simultaneous Auctions
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    Chapter 15 Bidding Strategies for Multi-object Auctions
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    Chapter 16 Cognitive Biases in Negotiation Processes
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    Chapter 17 On the Forecast Accuracy of Sports Prediction Markets
Attention for Chapter 16: Cognitive Biases in Negotiation Processes
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Chapter title
Cognitive Biases in Negotiation Processes
Chapter number 16
Book title
Negotiation, Auctions, and Market Engineering
Published by
Springer, Berlin, Heidelberg, January 2008
DOI 10.1007/978-3-540-77554-6_16
Book ISBNs
978-3-54-077553-9, 978-3-54-077554-6
Authors

Henner Gimpel

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 25%
Student > Ph. D. Student 3 19%
Unspecified 1 6%
Other 1 6%
Researcher 1 6%
Other 0 0%
Unknown 6 38%
Readers by discipline Count As %
Computer Science 4 25%
Social Sciences 2 13%
Agricultural and Biological Sciences 1 6%
Unspecified 1 6%
Business, Management and Accounting 1 6%
Other 1 6%
Unknown 6 38%