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Pricing problems in online markets
Descriptive
TitleInfo
Title
Pricing problems in online markets
Name
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(type = family)
Xia
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Chaolun
NamePart
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1985-
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Chaolun Xia
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author
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Muthukrishnan
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Shan
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Shan Muthukrishnan
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Advisory Committee
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chair
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Nath
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Badri
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Badri Nath
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Advisory Committee
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internal member
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(type = family)
Zhang
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Desheng
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Desheng Zhang
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Advisory Committee
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internal member
Name
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Korula
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Nitish
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Nitish Korula
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Advisory Committee
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outside member
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Rutgers University
Role
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degree grantor
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School of Graduate Studies
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school
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Text
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theses
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DateCreated
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2018
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2018-10
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2018
Place
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xx
Language
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eng
Abstract
(type = abstract)
The Internet Economy includes various online markets with billions of transactions. In this dissertation, we study pricing-related problems in both advertising markets and labor markets.
In an online advertising market, the advertiser pays for showing the ads to his target users.
Discovered by previous works, the prices of showing ads to users with different attributes vary a lot. Motivated by this observation, we develop two targeting algorithms to help an advertiser reach more target users when he has a budget. The first algorithm with provable guarantee is for the case when all the user information is completely revealed, and the second one is for the case when the user information is partially present. We also crawled LinkedIn and Facebook price to verify our algorithm. We further point out that these two algorithms are feasible only if the pricing has arbitrage. As price arbitrage may hurt the market revenue, we introduce arbitrage-free pricing for such markets, and finally propose three arbitrage-free pricing algorithms with provable revenue guarantee for the market.
In a labor market with multiple workers and tasks, a worker possibly has several skills and a task requires a worker with a certain skill. To fairly match workers and tasks, we introduce the stable pricing mechanism by extending stable matching. We propose three truthful stable pricing mechanisms with revenue guarantee to ensure the fairness for both workers and tasks.
In an online advertising market, the advertiser pays for showing the ads to his target users.
Discovered by previous works, the prices of showing ads to users with different attributes vary a lot. Motivated by this observation, we develop two targeting algorithms to help an advertiser reach more target users when he has a budget. The first algorithm with provable guarantee is for the case when all the user information is completely revealed, and the second one is for the case when the user information is partially present. We also crawled LinkedIn and Facebook price to verify our algorithm. We further point out that these two algorithms are feasible only if the pricing has arbitrage. As price arbitrage may hurt the market revenue, we introduce arbitrage-free pricing for such markets, and finally propose three arbitrage-free pricing algorithms with provable revenue guarantee for the market.
In a labor market with multiple workers and tasks, a worker possibly has several skills and a task requires a worker with a certain skill. To fairly match workers and tasks, we introduce the stable pricing mechanism by extending stable matching. We propose three truthful stable pricing mechanisms with revenue guarantee to ensure the fairness for both workers and tasks.
Subject
(authority = RUETD)
Topic
Computer Science
Subject
(authority = ETD-LCSH)
Topic
Pricing
Subject
(authority = ETD-LCSH)
Topic
Internet advertising
Subject
(authority = ETD-LCSH)
Topic
Labor markets
RelatedItem
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_9047
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (98 pages : illustrations)
Note
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Ph.D.
Note
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Includes bibliographical references
Note
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by Chaolun Xia
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier
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doi:10.7282/t3-3zq1-0b23
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
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The author owns the copyright to this work.
RightsHolder
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Name
FamilyName
Xia
GivenName
Chaolun
Role
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RightsEvent
Type
Permission or license
DateTime
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2018-05-24 14:53:38
AssociatedEntity
Name
Chaolun Xia
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
License
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
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2018-05-24T14:43:13
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2018-05-24T14:43:13
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