Mandated data-sharing in hybrid marketplaces - Federico Navarra; Flavio Pino; Luca Sandrini (ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, 2024)
We study a hybrid marketplace where a vertically integrated platform competes with a seller in a horizontally differentiated downstream market. The platform has a data advantage and can price discriminate consumers, whereas the seller cannot. Our analysis shows that, by properly setting the per-unit transaction fee, the platform can always avoid head-to-head competition with the seller, regardless of the level of horizontal differentiation. Mandating data-sharing, which allows the seller to also price discriminate, does not seem to solve this problem and, in fact, aggravates it further, generally benefiting the platform. The seller is better off only if it is less efficient than the platform, whereas consumers are worse off. We propose that preventing the platform from adjusting the fee after the data-sharing mandate is not enough to reinstate competition in the downstream market. We then show that banning the hybrid business model and forbidding the use of data for price discrimination increase consumer surplus, even if the seller becomes a monopolist. In other words, we propose that the harm to competition comes from the platform's business model rather than from its information advantage.
Keywords: D42; L12; L41; 330; hybrid platforms; data-sharing; vertical integration; price discrimination