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, we 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. We 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.

中文翻译：

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人工智能和数据网络效应对创造用户价值的作用

一些世界上最赚钱的公司拥有展示网络效应的平台。一个平台表现出网络效应，如果人们使用它的次数越多，它对每个用户的价值就越大。关于展示网络效应的平台用户感知价值的理论化传统上侧重于直接和间接的网络效应。在本文中，我们对一种新的网络效应类别——数据网络效应——进行了理论分析，这种效应源于人工智能的进步和数据可用性的不断提高。如果平台从其收集的用户数据中学到的越多，平台对每个用户的价值就越大，那么平台就会表现出数据网络效应。