Opening the “Black Box” of Network Externalities in Network Adoption

TLDR

Network externalities are theorized to drive network adoption, yet empirical evidence on their influence remains scarce and largely unknown. This study empirically investigates how network externalities and other factors determine membership in electronic banking networks. The authors employ hazard modeling within an electronic banking context to analyze adoption dynamics. Results confirm the network externalities hypothesis, showing that banks in markets with larger effective network sizes and stronger externalities adopt early, while larger own branch networks reduce early adoption probability.

Abstract

Recent theoretical work suggests that network externalities are a determinant of network adoption. However, few empirical studies have reported the impact of network externalities on the adoption of networks. As a result, little is known about the extent to which network externalities may influence network adoption and diffusion. Using electronic banking as a context and an econometric technique called hazard modeling, this research examines empirically the impact of network externalities and other influences that combine to determine network membership. The results support the network externalities hypothesis. We find that banks in markets that can generate a larger effective network size and a higher level of externalities tend to adopt early, while the size of a bank's own branch network (a proxy for the opportunity cost of adoption)decreases the probability of early adoption.