Mean field approximation for biased diffusion on Japanese inter-firm trading network.

By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be...

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Main Author: Hayafumi Watanabe
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3953512?pdf=render
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spelling doaj-31a238bac641425e80048923838112022020-11-25T01:46:39ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0193e9170410.1371/journal.pone.0091704Mean field approximation for biased diffusion on Japanese inter-firm trading network.Hayafumi WatanabeBy analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.http://europepmc.org/articles/PMC3953512?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Hayafumi Watanabe
spellingShingle Hayafumi Watanabe
Mean field approximation for biased diffusion on Japanese inter-firm trading network.
PLoS ONE
author_facet Hayafumi Watanabe
author_sort Hayafumi Watanabe
title Mean field approximation for biased diffusion on Japanese inter-firm trading network.
title_short Mean field approximation for biased diffusion on Japanese inter-firm trading network.
title_full Mean field approximation for biased diffusion on Japanese inter-firm trading network.
title_fullStr Mean field approximation for biased diffusion on Japanese inter-firm trading network.
title_full_unstemmed Mean field approximation for biased diffusion on Japanese inter-firm trading network.
title_sort mean field approximation for biased diffusion on japanese inter-firm trading network.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description By analysing the financial data of firms across Japan, a nonlinear power law with an exponent of 1.3 was observed between the number of business partners (i.e. the degree of the inter-firm trading network) and sales. In a previous study using numerical simulations, we found that this scaling can be explained by both the money-transport model, where a firm (i.e. customer) distributes money to its out-edges (suppliers) in proportion to the in-degree of destinations, and by the correlations among the Japanese inter-firm trading network. However, in this previous study, we could not specifically identify what types of structure properties (or correlations) of the network determine the 1.3 exponent. In the present study, we more clearly elucidate the relationship between this nonlinear scaling and the network structure by applying mean-field approximation of the diffusion in a complex network to this money-transport model. Using theoretical analysis, we obtained the mean-field solution of the model and found that, in the case of the Japanese firms, the scaling exponent of 1.3 can be determined from the power law of the average degree of the nearest neighbours of the network with an exponent of -0.7.
url http://europepmc.org/articles/PMC3953512?pdf=render
work_keys_str_mv AT hayafumiwatanabe meanfieldapproximationforbiaseddiffusiononjapaneseinterfirmtradingnetwork
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