Streaming Platform and Strategic Recommendation Bias
| Autor: | Germain Gaudin, Marc Bourreau |
|---|---|
| Přispěvatelé: | Département Sciences Economiques et Sociales (SES), Télécom ParisTech, Economie Gestion (ECOGE), Institut interdisciplinaire de l’innovation (I3, une unité mixte de recherche CNRS (UMR 9217)), École polytechnique (X)-Télécom ParisTech-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Télécom ParisTech-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Télécom ParisTech-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) |
| Rok vydání: | 2018 |
| Předmět: |
Upstream (petroleum industry)
Economics and Econometrics Focus (computing) business.industry Computer science Strategy and Management 05 social sciences Recommender system [SHS.ECO]Humanities and Social Sciences/Economics and Finance General Business Management and Accounting Vertical integration Personalization Management of Technology and Innovation 0502 economics and business Market power 050207 economics Robustness (economics) Telecommunications business ComputingMilieux_MISCELLANEOUS 050205 econometrics |
| Zdroj: | Journal of Economics and Management Strategy Journal of Economics and Management Strategy, Wiley, In press, ⟨10.1111/jems.12452⟩ |
| ISSN: | 1556-5068 1058-6407 1530-9134 |
| DOI: | 10.2139/ssrn.3338744 |
| Popis: | We consider a platform that carries content from two upstream content providers and presents personalized recommendations to participating customers. We focus on streaming platforms in media markets, where users pay a subscription fee to join the platform but no usage fee, and consume a mix of content originating from each provider. We characterize the bias in the user-specific recommendations offered by the platform when one content provider charges lower royalties than the other. We establish that if consumers are sufficiently insensitive to bias, the recommendation system allows the platform to credibly threaten upstream providers to steer consumers away from their content, which reduces their market power. We also investigate the effects of vertical integration by the platform and show the robustness of our results to non-linear (personalized) streaming services. |
| Databáze: | OpenAIRE |
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