THE ROLE OF ARTIFICIAL INTELLIGENCE AND DATA NETWORK EFFECTS FOR CREATING USER VALUE

• 成果类型: Article
• 署名作者: Gregory, Robert Wayne; Henfridsson, Ola; Kaganer, Evgeny; Kyriakou, Skolkovo Harris
• 署名单位: University of Virginia; University of Miami; ESSEC Business School
• 刊物名称: ACADEMY OF MANAGEMENT REVIEW
• ISSN/ISSBN: 0363-7425
• DOI: 10.5465/amr.2019.0178
• 发表日期: 2021
• 页码: 534-551
• 关键词: big data; TECHNOLOGY; MARKETS; INNOVATION; strategy; COMPETITION; platforms; privacy; ORGANIZATIONS; compatibility

摘要

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.