Platform aggregation in two-sided markets

Platform aggregation, where large-scale platforms (LPs) integrate services from multiple small-scale platforms (SPs), is becoming increasingly popular in markets such as ride-hailing. On the aggregated platform, consumers can access multiple services within a single app and even send service requests to multiple providers simultaneously, a concept referred to as one-click ride-hailing (OCAR). This paper develops a model to examine the impacts of platform aggregation on prices, wages, and profits in two-sided markets. Our findings indicate that in the aggregation scenario, when consumer preference is strong and the OCAR allocation ratio is low, the LP tends to lower prices, while the SP initially reduces prices before increasing them subsequently. In addition, at a moderate OCAR allocation ratio, aggregation can result in a win-win outcome, boosting profits for both the LP and SP. However, a lower OCAR allocation ratio particularly benefits the LP. Notably, the LP should emphasize its intermediary role under weak network effects and transition to a service provider role under strong network effects. We further analyze two OCAR order allocation approaches: the indirect approach, which depends on the number of drivers, and the direct approach, which is determined by the LP. We find that the indirect approach promotes balanced partnerships, while the direct approach often leads to the LP capturing all the profits. Finally, to verify the robustness of our key results and gain additional insights, we extend our model by considering an endogenous commission rate and a partially covered market.