The literature on networks suggests that the value of a network is positively affected by the number of geographically dispersed locations it serves (the “network effect”) and the number of its users (the “production scale effect”). We show that as a result a firm’s expected time until adoption of technologies with network effects declines in both users and locations. We provide empirical evidence on the adoption of automated teller machines by banks that is consistent with this prediction. Using standard duration models, we find that a bank’s date of adoption is decreasing in the number of its branches (a proxy for the number of locations and hence for the network effect) and the value of its deposits (a proxy for number of users and hence for production scale economies). The network effect is the larger of the two effects.