Arbeitspapier | Working paper

Economic recommendation based on pareto efficient resource allocation

A fundamentally important role of the Web economy is Online Resource Allocation (ORA) from producers to consumers, such as product allocation in E-commerce, job allocation in freelancing platforms, and driver resource allocation in P2P riding services. Since users have the freedom to choose, such allocations are not provided in a forced manner, but usually in forms of personalized recommendation, where users have the right to refuse. Current recommendation approaches mostly provide allocations to match the preference of each individual user, instead of treating the Web application as a whole economic system where users therein are mutually correlated on the allocations. This lack of global view leads to Pareto inefficiency, i.e., we can actually improve the recommendations by bettering some users while not hurting the others, and it means that the system did not achieve its best possible allocation. This problem is especially severe when the total amount of each resource is limited, so that its allocation to one (set of) user means that other users are left out. In this paper, we propose Pareto Efficient Economic Recommendation (PEER) - that the system provides the best possible (i.e., Pareto optimal) recommendations, where no user can gain further benefits without hurting the others. To this end, we propose a Multi-Objective Optimization (MOO) framework to maximize the surplus of each user simultaneously, and provide recommendations based on the resulting Pareto optima. To benefit the many existing recommendation algorithms, we further propose a Pareto Improvement Process (PIP) to turn their recommendations into Pareto efficient ones. Experiments on real-world datasets verify that PIP improves existing algorithms on recommendation performance and consumer surplus, while the direct PEER approach gains the best performance on both aspects.

Economic recommendation based on pareto efficient resource allocation

Urheber*in: Zhang, Yongfeng; Zhang, Yi; Friedman, Daniel

Rechte vorbehalten - Freier Zugang

0
/
0

Umfang
Seite(n): 10
Sprache
Englisch
Anmerkungen
Status: Veröffentlichungsversion

Erschienen in
Discussion Papers / Wissenschaftszentrum Berlin für Sozialforschung, Forschungsschwerpunkt Markt und Entscheidung, Forschungsprofessur Market Design: Theory and Pragmatics (SP II 2017-503)

Thema
Wirtschaft
Allgemeines, spezielle Theorien und Schulen, Methoden, Entwicklung und Geschichte der Wirtschaftswissenschaften

Ereignis
Geistige Schöpfung
(wer)
Zhang, Yongfeng
Zhang, Yi
Friedman, Daniel
Ereignis
Veröffentlichung
(wer)
Wissenschaftszentrum Berlin für Sozialforschung gGmbH
(wo)
Deutschland, Berlin
(wann)
2017

Handle
Rechteinformation
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln
Letzte Aktualisierung
21.06.2024, 16:26 MESZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
GESIS - Leibniz-Institut für Sozialwissenschaften. Bibliothek Köln. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Zhang, Yongfeng
  • Zhang, Yi
  • Friedman, Daniel
  • Wissenschaftszentrum Berlin für Sozialforschung gGmbH

Entstanden

  • 2017

Ähnliche Objekte (12)