Economic recommendation with surplus maximization
Abstract: A prime function of many major World Wide Web applications is Online Service Allocation (OSA), the function of matching individual consumers with particular services/goods (which may include loans or jobs as well as products) each with its own producer. In the applications of interest, consumers are free to choose, so OSA usually takes the form of personalized recommendation or search in practice. The performance metrics of recommender and search systems currently tend to focus on just one side of the match, in some cases the consumers (e.g. satisfaction) and in other cases the producers (e.g., profit). However, a sustainable OSA platform needs benefit both consumers and producers; otherwise the neglected party eventually may stop using it. In this paper, we show how to adapt economists' traditional idea of maximizing total surplus (the sum of consumer net benefit and producer profit) to the heterogeneous world of online service allocation, in an effort to promote the web intellige
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource, 16 S.
- Sprache
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Englisch
- Anmerkungen
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Veröffentlichungsversion
begutachtet
- Erschienen in
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Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Markt und Entscheidung, Forschungsprofessur Market Design: Theory and Pragmatics ; Bd. SP II 2016-502
- Klassifikation
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Wirtschaft
- Ereignis
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Veröffentlichung
- (wo)
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Mannheim
- (wer)
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SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
- (wann)
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2016
- Ereignis
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Veröffentlichung
- (wo)
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Berlin
- (wer)
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Wissenschaftszentrum Berlin für Sozialforschung gGmbH
- (wann)
-
2016
- Beteiligte Personen und Organisationen
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Wissenschaftszentrum Berlin für Sozialforschung gGmbH
- URN
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urn:nbn:de:101:1-2021101108464517746502
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
25.03.2025, 13:52 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Zhang, Yongfeng
- Zhao, Qi
- Zhang, Yi
- Friedman, Daniel
- Zhang, Min
- Liu, Yiqun
- Ma, Shaoping
- Wissenschaftszentrum Berlin für Sozialforschung gGmbH
- SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
Entstanden
- 2016
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