Real-Time Decentralization Information Processing and Returns to Scale

We use a model of real-time decentralized information processing to understand howconstraints on human information processing affect the returns to scale of organizations.We identify three informational (dis)economies of scale: diversification of heterogeneousrisks (positive), sharing of information and of costs (positive), and crowding out ofrecent information due to information processing delay (negative). Because decisionrules are endogenous, delay does not inexorably lead to decreasing returns to scale.However, returns are more likely to be decreasing when computation constraints, ratherthan sampling costs, limit the information upon which decisions are conditioned. Theresults illustrate how information processing constraints together with the requirementof informational integration cause a breakdown of the replication arguments that havebeen used to establish nondecreasing technological returns to scale