Empirical Analysis of Firm-Dynamics on Japanese Interfirm Trade Network

Goto, Hayato; Takayasu, Hideki; Takayasu, Misako

doi:10.1007/978-3-319-20591-5_18

Cited by 11 publications

(7 citation statements)

References 12 publications

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“…Business and trade networks provide well-studied economic examples of directed networks that allow for detailed investigations of the aforementioned questions. In business networks, individual firms are interpreted as nodes [12]. If a business or trade relationship between two firms is reported, a link between the involved nodes is drawn.…”

Section: J Stat Mech (2017) 053404mentioning

confidence: 99%

“…Equation (7) accounts for the assumption that more common business relations make a reconnection to node l more likely. Models G • that include the relinking process are denoted with the additional subscript l. https://doi.org/10.1088/1742-5468/aa6ddb approximately reproduces the scale-free degree distribution from the real-world network, following a power law ∝ k −α with an exponent of α ≈ 1.4 [12]. Despite changes in the number of firms and links, it has been concluded that some basic characteristics such as the degree distribution are robust in the business firm network of Japan from 1994 to 2014 [12].…”

Section: Substitution Of Trading Partnersmentioning

confidence: 99%

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Motif formation and industry specific topologies in the Japanese business firm network

et al. 2017

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Motifs and roles are basic quantities for the characterization of interactions among 3-node subsets in complex networks. In this work, we investigate how the distribution of 3-node motifs can be influenced by modifying the rules of an evolving network model while keeping the statistics of simpler network characteristics, such as the link density and the degree distribution, invariant. We exemplify this problem for the special case of the Japanese Business Firm Network, where a well-studied and relatively simple yet realistic evolving network model is available, and compare the resulting motif distribution in the real-world and simulated networks. To better approximate the motif distribution of the real-world network in the model, we introduce both subgraph dependent and global additional rules. We find that a specific rule that allows only for the merging process between nodes with similar link directionality patterns reduces the observed excess of densely connected motifs with bidirectional links. Our study improves the mechanistic understanding of motif formation in evolving network models to better describe the characteristic features of real-world networks with a scale-free topology.

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Section: J Stat Mech (2017) 053404mentioning

confidence: 99%

Section: Substitution Of Trading Partnersmentioning

confidence: 99%

Motif formation and industry specific topologies in the Japanese business firm network

et al. 2017

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“…Nevertheless, different scaling exponents might also be relevant to differences in actual dynamics of companies. For example, the number of companies having 5-10 trading partners are more than expected from the powerlaw tail of the distribution in our dataset (as seen in [54]). This might suggest that there is a 'barrier' that prevents those in the small-company regime from entering the large-company regime.…”

Section: Discussionmentioning

confidence: 66%

Time evolution of companies towards a stable scaling curve obtained from flow diagrams in three-dimensional phase space

et al. 2019

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Although scaling relations of power law forms have been revealed in a wide variety of complex systems, the origin of scaling relations in real systems remains mostly unsolved. Based on a long tradition in physics, we here explore the phase space dynamics of business companies, whose different measures of size have been found to exhibit multiple scaling relations. Using a large scale dataset of Japanese companies covering over two million companies for over two decades , we compile the data of three measures of size, namely, annual sales, number of employee and number of trading partners. Tracking the historical time evolution of companies, we first show that there exists a stable region that attracts most of the data points in the long time scale, although the company dynamics in the three-dimensional phase space looks random in a shorter time scale. We then elaborate on 'evolving flow diagrams' of the averaged motion in the 3D space. Remarkably, the flow diagrams indicate that a 3D curve which represents the scaling relations between the three size measures can be regarded as an approximate attractor of the averaged flows. The results could serve for better modeling and understanding of companies dynamics and our method can be applied to other dynamics such as social and biological phenomena.

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“…In addition, although not covered in this paper, the analysis of such network structures as inter-firm transactions and corporate shareholding has increased the understanding of the microstructures of corporate connections (See Refs. Goto et al [13]; Mizuno et al [14]).…”

Section: Introductionmentioning

confidence: 99%

Statistical Properties of Labor Productivity Distributions

2022

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We employed the latest version of the world’s largest corporate financial database and identified the following three statistical properties of the physical labor productivity of firms: 1) The probability density function (PDF) of labor productivity follows power-law and log-normal distributions in the large- and mid-scale ranges. 2) Time-reversal symmetry was observed in the correlation of labor productivities in two consecutive years, and the initial-value dependence of the growth-rate distribution has regularity. These two properties accurately derive the above two kinds of PDFs. 3) The dependence of labor productivity distribution is negligible on the number of employees. This indicates a slight difference in the distribution of labor productivity among large-, mid-, and small-sized firms.

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Empirical Analysis of Firm-Dynamics on Japanese Interfirm Trade Network

Cited by 11 publications

References 12 publications

Motif formation and industry specific topologies in the Japanese business firm network

Motif formation and industry specific topologies in the Japanese business firm network

Time evolution of companies towards a stable scaling curve obtained from flow diagrams in three-dimensional phase space

Statistical Properties of Labor Productivity Distributions

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