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Designing aggregation mechanisms for reputation systems in online marketplaces

Designing aggregation mechanisms for reputation systems in online marketplaces Designing Aggregation Mechanisms for Reputation Systems in Online Marketplaces CHRISTINA APERJIS Hewlett Packard Labs and RAMESH JOHARI Stanford University A seller in an online marketplace with an e €ective reputation mechanism should expect that dishonest behavior results in higher payments now, while honest behavior results in higher reputation ” and thus higher payments ”in the future. We brie ‚y survey recent results on the Window Aggregation Mechanism, a widely used class of mechanisms that shows the average value of the seller ™s ratings within some xed window of past transactions. We suggest approaches for choosing the window size that maximizes the range of parameters for which it is optimal for the seller to be truthful. We show that mechanisms that use information from a larger number of past transactions tend to provide incentives for patient sellers to be more truthful, but for higher quality sellers to be less truthful. We then discuss a broader class of aggregation mechanisms that weight recent ratings more heavily and show that the same insight applies. Categories and Subject Descriptors: K.4.4 [Computers and Society]: Electronic Commerce General Terms: Economics; Theory Additional Key Words and Phrases: Aggregation mechanisms, reputation systems, electronic marketplaces 1. INTRODUCTION http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Designing aggregation mechanisms for reputation systems in online marketplaces

Aperjis, Christina; Johari, Ramesh
ACM SIGecom Exchanges , Volume 9 (1) – Jun 1, 2010
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Publisher
Association for Computing Machinery
Copyright
Copyright © 2010 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/1980534.1980537
Publisher site
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Abstract

Designing Aggregation Mechanisms for Reputation Systems in Online Marketplaces CHRISTINA APERJIS Hewlett Packard Labs and RAMESH JOHARI Stanford University A seller in an online marketplace with an e €ective reputation mechanism should expect that dishonest behavior results in higher payments now, while honest behavior results in higher reputation ” and thus higher payments ”in the future. We brie ‚y survey recent results on the Window Aggregation Mechanism, a widely used class of mechanisms that shows the average value of the seller ™s ratings within some xed window of past transactions. We suggest approaches for choosing the window size that maximizes the range of parameters for which it is optimal for the seller to be truthful. We show that mechanisms that use information from a larger number of past transactions tend to provide incentives for patient sellers to be more truthful, but for higher quality sellers to be less truthful. We then discuss a broader class of aggregation mechanisms that weight recent ratings more heavily and show that the same insight applies. Categories and Subject Descriptors: K.4.4 [Computers and Society]: Electronic Commerce General Terms: Economics; Theory Additional Key Words and Phrases: Aggregation mechanisms, reputation systems, electronic marketplaces 1. INTRODUCTION

Journal

ACM SIGecom Exchanges – Association for Computing Machinery

Published: Jun 1, 2010

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