Buyer Power In The Big Data And Algorithm Driven World: The Uber & Lyft Example

By Ignacio Herrera Anchustegui & Julian Nowag – 

This article explores how big data and algorithms may create new possibilities for unilateral anticompetitive behavior in the form of overbuying and “reverse rebates,” using as a case study the recent proceedings against Uber concerning its “Hell” program. The analysis provides us with the opportunity to re-explore traditional antitrust concepts, anchored on the purchasing of raw material, in the data and algorithm driven world. Our paper shows how big data and algorithms have the potential to make these exclusionary buying tactics far more targeted and therefore effective and efficient.

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