Evolution of Networks and the Diffusion of New Technology
Striking a balance between the costs and benefits of information processing is a fundamental problem in a dynamic system. The point of this analysis is to identify conditions that determine whether that balance actually occurs in an economy, with particular attention to the question of how institutional arrangements determine market outcomes. This paper extends the theoretical framework for exploring the diffusion of new technologies through firms and industries. A useful technique for studying information processing is to construct a network; the links of the network represent channels through which information flows between agents located at the nodes. Two important aspects of networks are particularly relevant to this analysis. One, the structure of a network may be the result of individual agents within the network. Actions that result in better outcomes for agents at the nodes may not result in structures that work best for the entire group. Two, the problem of finding the optimal network for a given situation can be computationally demanding, making it unrealistic to assume that a "manager" could actually solve this problem. Thus, it is not credible to assume that the networks that form in an economy will necessarily be the ones that optimize the flow of information. This analysis will rely on an alternate presumption: an evolutionary process drives the development of networks. The focus of this paper is to identify how these evolutionary outcomes compare with optimal solutions. An important innovation in this analysis is to show how the institutional environment shapes the evolutionary outcome. In the network model, different institutional regimes correspond to different distributions of the costs and benefits of information processing. The analysis of evolutionary outcomes hinges on the relevant institutional regime. This leads directly to the identification of institutional changes that can improve outcomes, free the flow of information, and encourage the diffusion of profitable new technologies.
Year of publication: |
1999-03-01
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Authors: | Mitchell, Glenn T. |
Institutions: | Society for Computational Economics - SCE |
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