Real-Time Decentralized Information Processing and Returns to Scale

41 Pages Posted: 13 Oct 2008

See all articles by Timothy Van Zandt

Timothy Van Zandt

affiliation not provided to SSRN

Roy Radner

Leonard N. Stern School of Business - Department of Economics

Date Written: May 1996

Abstract

We study the properties of real-time decentralized information processing, as a model of human information processing in organizations, and use the model to understand how constraints on human information processing affect the returns to scale of firms. With real-time processing, decentralization does not unambiguously reduce delay, because processing a subordinate's report precludes processing current data. Because decision rules are endogenous, delay does not inexorably lead to eventually decreasing returns to scale; however, returns are more likely to be decreasing when computation constraints, rat her than sampling costs, limit the information upon which decisions are conditioned. The results illustrate that the requirement of informational integration causes a breakdown of the replication arguments that are often used to establish non-decreasing returns.

Suggested Citation

Van Zandt, Timothy and Radner, Roy, Real-Time Decentralized Information Processing and Returns to Scale (May 1996). NYU Working Paper No. 2451/14134, Available at SSRN: https://ssrn.com/abstract=1282986

Timothy Van Zandt (Contact Author)

affiliation not provided to SSRN

No Address Available

Roy Radner

Leonard N. Stern School of Business - Department of Economics ( email )

44 West Fourth Street, 7-180
New York, NY 10012
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
40
Abstract Views
484
PlumX Metrics