Real-Time Decentralized Information Processing and Returns to Scale
We use a model of real-time decentralized information processing to understand how constraints on human information processing affect the returns to scale of organizations. We identify three informational (dis)economies of scale: diversification of heterogeneous risks (positive), sharing of information and of costs (positive), and crowding out of recent information due to information processing delay (negative). Because decision rules are endogenous, delay does not inexorably lead to decreasing returns to scale. However, returns are more likely to be decreasing when computation constraints, rather than sampling costs, limit the information upon which decisions are conditioned. The results illustrate how information processing constraints together with the requirement of informaitonal integration cause a breakdown of the replication arguments that have been used to establish nondecreasing technological returns to scale.
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| Date of creation: | Nov 1998 |
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| Handle: | RePEc:nwu:cmsems:1233 |
| Contact details of provider: | Postal: Center for Mathematical Studies in Economics and Management Science, Northwestern University, 580 Jacobs Center, 2001 Sheridan Road, Evanston, IL 60208-2014 Phone: 847/491-3527 Fax: 847/491-2530 Web page: http://www.kellogg.northwestern.edu/research/math/ Email: More information through EDIRC
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