When does algorithmic pricing result in an intra-platform anticompetitive agreement or concerted practice? : the case of Uber in the framework of EU competition law

dc.contributor.authorBEKISZ, Hubert
dc.date.accessioned2021-04-27T08:31:14Z
dc.date.available2021-04-27T08:31:14Z
dc.date.issued2021
dc.descriptionPublished online on 16 March 2021en
dc.description.abstractThis article raises a research question of when intra-platform algorithmic pricing results in an anticompetitive agreement or concerted practice in the meaning of Article 101 of the Treaty on the functioning of the European Union (TFEU). The taken approach is a combination of an overview of existing types of algorithmic pricing and the case study on the business model of Uber. Selection of Uber is motivated by its great significance on the online platforms’ market. In 2015, Uber has been valued $51 billion and was the only platform next to Facebook to exceed $50 billion threshold.1 Many platforms therefore follow Uber’s business model and the remarks explicitly made on the example of Uber remain relevant to many other Uber-like apps.en
dc.format.mimetypeapplication/pdf
dc.identifier.citationJournal of European competition law & practice, 2021, Vol. 12, No. 3, pp. 217–235en
dc.identifier.doi10.1093/jeclap/lpab017
dc.identifier.endpage235en
dc.identifier.issn2041-7764
dc.identifier.issn2041-7772
dc.identifier.issue3en
dc.identifier.startpage217en
dc.identifier.urihttps://hdl.handle.net/1814/70938
dc.identifier.volume12en
dc.language.isoenen
dc.orcid.uploadtrue*
dc.publisherOxford University Pressen
dc.relation.ispartofJournal of European competition law & practiceen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.titleWhen does algorithmic pricing result in an intra-platform anticompetitive agreement or concerted practice? : the case of Uber in the framework of EU competition lawen
dc.typeArticleen
dspace.entity.typePublication
person.identifier.other45068
relation.isAuthorOfPublicationcb51d9cf-8e66-4c8a-81f9-591119e8380c
relation.isAuthorOfPublication.latestForDiscoverycb51d9cf-8e66-4c8a-81f9-591119e8380c
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