Some of the world’s most profitable firms own platforms that exhibit network effects. A platform exhibits network effects if, the more that people use it, the more valuable it becomes to each user. Theorizing about the value perceived by users of a platform that exhibits network effects has traditionally focused on direct and indirect network effects. In this paper, the authors theorize about a new category of network effects — data network effects — that has emerged from advances in artificial intelligence and the growing availability of data. A platform exhibits data network effects if, the more that the platform learns from the data it collects on users, the more valuable the platform becomes to each user.
They argue that there is a positive direct relationship between the artificial intelligence capability of a platform and the value perceived in the platform by its users — a relationship that is moderated by platform legitimation, data stewardship, and user-centric design.