Economics of Recommender Systems

This tutorial dives into the economics of recommender systems (RSs), presenting existing and ongoing research on how they influence consumer choices, shape market outcomes, and change the incentives of those who interact with them, whether by designing, catering to, or using these systems. The tutorial also touches on the broader implications of this research for antitrust and competition policy. By fostering a collaborative and interdisciplinary research community, this tutorial aims to deepen the understanding of the economic effects of recommender systems and inform the development of policies to mitigate potential risks associated with their diffusion.

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Publication Details

Published
2024-10-08
DOI
https://doi.org/10.1145/3640457.3687093
Citations
2
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
1.56

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article

Economics of Recommender Systems

Sergio Pastorello, Vincenzo Denicolò, Emilio Calvano, Giacomo Calzolari
2 citations
Recommender Systems and Techniques
1.56
article

Economics of Recommender Systems

Sergio Pastorello, Vincenzo Denicolò, Emilio Calvano, Giacomo Calzolari
article en
2 citations

Abstract

This tutorial dives into the economics of recommender systems (RSs), presenting existing and ongoing research on how they influence consumer choices, shape market outcomes, and change the incentives of those who interact with them, whether by designing, catering to, or using these systems. The tutorial also touches on the broader implications of this research for antitrust and competition policy. By fostering a collaborative and interdisciplinary research community, this tutorial aims to deepen the understanding of the economic effects of recommender systems and inform the development of policies to mitigate potential risks associated with their diffusion.

Libera Università Internazionale degli Studi Sociali Guido Carli (IT), European University Institute (IT), University of Bologna (IT)
European Commission
Openalex Percentile: Top 12%
Recommender Systems and Techniques
1.56
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