1998
DOI: 10.1103/physrevlett.80.1385
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Power Law Scaling for a System of Interacting Units with Complex Internal Structure

Abstract: We study the dynamics of a system composed of interacting units each with a complex internal structure comprising many subunits. We consider the case in which each subunit grows in a multiplicative manner. We propose a model for such systems in which the interaction among the units is treated in a mean field approximation and the interaction among subunits is nonlinear. To test the model, we identify a large data base spanning 20 years, and find that the model correctly predicts a variety of empirical results.… Show more

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Cited by 229 publications
(185 citation statements)
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“…It has been argued the tent-shaped distributions of growth rates in complex systems may emerge if the units composing the system evolve according to a random multiplicative growth process (e.g., a mixture of lognormal distributions with different variances) (37,38). However, for this explanation to hold in our system, the amount of oxygen consumed by the units composing the system (i.e., cells, tissues or organs) would need to be independent, with similar mean and different variances.…”
Section: Discussionmentioning
confidence: 99%
“…It has been argued the tent-shaped distributions of growth rates in complex systems may emerge if the units composing the system evolve according to a random multiplicative growth process (e.g., a mixture of lognormal distributions with different variances) (37,38). However, for this explanation to hold in our system, the amount of oxygen consumed by the units composing the system (i.e., cells, tissues or organs) would need to be independent, with similar mean and different variances.…”
Section: Discussionmentioning
confidence: 99%
“…The resulting distributions are roughly triangular in shape with the width depending on S ( gure 1a). (The triangular shape may result from summing over a large number of time-series with different local variances; see Amaral et al (1998).) If the distributions are 'self-similar' (i.e.…”
Section: Scaling Of Species Growth Ratesmentioning
confidence: 99%
“…Recent generative models are quite dominated by physically inspired concepts and techniques, a field known as econophysics (Mantegna and Stanley 2000;Chakrabarti et al 2006). Econophysical generative models like (Amaral et al 1998) reproduce aggregated statistical patterns from stochastic processes at the organization or subunit level. However, econophysics generative models are typically not calibrated with empirical data.…”
Section: Models Of Organizational Growth Processesmentioning
confidence: 99%
“…A Gaussian distribution arises from the aggregation of many independent units, in our case organizations. Heavy-tailed distributions on the other hand hint at the existence of dependencies and interactions between organizations (Amaral et al 1998) and can therefore be useful in the study of organizational dynamics.…”
Section: Size and Growth-rate Distributionsmentioning
confidence: 99%