The AdC sought to understand how the specificities of the digital economy shape firms’ incentives, the way they compete and market dynamics, highlighting the risks they may bring for competition.
Among these specificities, the AdC considered, namely, business models based on network effects, the widespread use of data in decision making and to improve products, and the use of different types of algorithms.
The AdC found these specificities have relevant implications for market definition, market power assessment and in competitive analysis in the digital sector, both in antitrust and merger control.
The AdC highlighted the role that access to data may have in the conditions of competition in the market. In this context, the AdC identified the strategies firms may resort to collect data about their users, as well as to restrict competitors’ capacity to have access to data, and their implications for competition.
Regarding algorithms, the AdC paid special attention to monitoring and pricing algorithms. The AdC concluded that the widespread use of these algorithms may make tacit collusion easier in digital markets. Algorithms may also be instrumental to establish and maintain collusive agreements, directly between competitors or through a third-party (hub-and-spoke); or to implement vertical agreements, like resale price maintenance.
The AdC also assessed the search, recommendation and ranking algorithms used by digital platforms, in e-commerce, search engines and digital advertising. These algorithms allow platforms to divert consumers from certain products to others and to exploit users’ behavioural biases. This ability introduces the risk of bottlenecks in the market, namely to leverage market power between products and services.