Commodity Flow 商品の流れ


Commodity Flow


 “The sustainability and the survivability of Kyoto’s traditional craft industry revealed from supplier-customer network ”

 Daisuke Sato, Yuichi Ikeda, Shuichi Kawai, Maximilian Schich ,
 PLOS ONE, 15, 11, e0240618-e0240618 ,

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 Due to the changes in consumer demand and generational transformations, Kyoto’s traditional craft industry has suffered substantial revenue losses in recent years. This research aimed to characterize Kyoto’s traditional craft industry by analyzing the supplier-customer network involving individual firms within the Kyoto region. In the process, we clarify the community structure, key firms, network topological characteristics, bow-tie structure, robustness, the vulnerability of the supplier-customer network as crucial factors for sustainable growth. The community and bow-tie structure analysis became clear that the traditional craft industry continues to occupy an important position in Kyoto’s industrial network. Furthermore, we clarify the relationship between modern and traditional craft industries’ network characteristics and their relative profitability and productivity. It became evident that the traditional craft industry has a different network structure from the modern consumer games and electric machinery industries. The modern industries have the strongly coupled component, and the attendant firms there create high value-added and play a significant role in driving the entire industry, while more traditional craft industries, such as the Nishijin silk fabrics and Kyoto doll industries, do not have this strongly coupled component. Moreover, the traditional crafts industry does not have a central firm or a dense network for integrating information, which is presumed to be a factor in the decline of the traditional craft industry. 


 “Testing“efficient supply chain  propositions” using topological characterization of the global supply chain network ”

 Abhijit Chakraborty, Yuichi Ikeda ,
 PLOS ONE, 15, 10, e0239669-e0239669 , 

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 In this paper, we study the topological properties of the global supply chain network in terms of its degree distribution, clustering coefficient, degree-degree correlation, bow-tie structure, and community structure to test the efficient supply chain propositions proposed by E. J.S. Hearnshaw et al. The global supply chain data in the year 2017 are constructed by collecting various company data from the web site of Standard & Poor’s Capital IQ platform. The in- and out-degree distributions are characterized by a power law of the form of γin = 2.42 and γout = 2.11. The clustering coefficient decays  with an exponent βk = 0.46. The nodal degree-degree correlations 〈knn(k)〉 indicates the absence of assortativity. The bow-tie structure of giant weakly connected component (GWCC) reveals that the OUT component is the largest and consists 41.1% of all firms. The giant strong connected component (GSCC) is comprised of 16.4% of all firms. We observe that upstream or downstream firms are located a few steps away from the GSCC. Furthermore, we uncover the community structures of the network and characterize them according to their location and industry classification. We observe that the largest community consists of the consumer discretionary sector based mainly in the United States (US). These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity of Hearnshaw et al.’s efficient supply chain propositions, namely Proposition S1 (short path length), Proposition S2 (power-law degree distribution), Proposition S3 (high clustering coefficient), Proposition S4 (“fit-gets-richer” growth mechanism), Proposition S5 (truncation of power-law degree distribution), and Proposition S7 (community structure with overlapping boundaries) regarding the global supply chain network. While the original propositions S1 just mentioned a short path length, we found the short path from the GSCC to IN and OUT by analyzing the bow-tie structure. Therefore, the short path length in the bow-tie structure is a conceptual addition to the original propositions of Hearnshaw. 

本稿では,E. J.S. Hearnshawらが提案した効率的なサプライチェーンの命題を検証するために,グローバル・サプライチェーン・ネットワークのトポロジー特性を,次数分布,クラスタリング係数,次数相関,ボウタイ構造,コミュニティ構造の観点から研究する。 2017年のグローバル・サプライチェーン・データは,Standard & Poor's Capital IQプラットフォームのWebサイトから様々な企業データを収集して構築した。度数分布は、γin=2.42、γout=2.11のべき乗則で特徴づけられる。クラスタリング係数は、指数βk=0.46で減衰する。また、ノードの度数相関 〈knn(k)〉は、アソータシティがないことを示している。巨大弱結合成分(GWCC)のボウタイ構造を見ると,OUT成分が最も大きく,全企業の41.1%を占めている。また,GSCC(Giant Strong Connected Component)は16.4%である。GSCCから数歩離れたところに上流または下流の企業があることがわかる。さらに、ネットワークのコミュニティ構造を明らかにし、それらを所在地と産業分類に基づいて特徴づけた。最大のコミュニティは、主に米国を拠点とする消費者裁量部門で構成されていることがわかった。これらの企業は、グローバル・サプライ・チェーン・ネットワークのボウタイ構造のOUTコンポーネントに属しています。最後に、Hearnshawらの効率的サプライチェーンに関する命題、すなわち、命題S1(短い経路長)、命題S2(power-law度分布)、命題S3(高いクラスタリング係数)、命題S4("fit-gets-richer "成長メカニズム)、命題S5(power-law度分布の切り捨て)、命題S7(境界が重なったコミュニティ構造)の妥当性を確認した。元々の命題S1では、単にパス長が短いというだけでしたが、ボウタイ構造を分析することで、GSCCからINとOUTへのショートパスを発見しました。したがって、ボウタイ構造における短経路の長さは、ハーンショーの原命題に概念的に追加されたものである。 

 “Multilayer network analysis of the drugs development cycle in the global pharmaceutical industry ”

 Hiromitsu Goto, Mari Jibu, Wataru Souma, Yuichi Ikeda , 
 Applied Network Science ,5 , 1

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 Drug development is a time-consuming process from the start of research to obtaining approval, and the probability of success with a candidate compound is extremely low. We aim to understand the characteristics of the flow and localization of knowledge during drug development in the global pharmaceutical industry. We analyze the multilayer network constructed with the drug pipeline layer, global supply chain layer, and global ownership layer. First, we identify the bow-tie structure and the community structure of each network layer. The obtained bow-tie structure shows the large strongly connected component and suggests that the knowledge flow in drug pipelines has similar characteristics as the supply chain network. The communities in each layer are characterized by country, category of the company, and bow tie component. We then study the multilayer network’s knowledge flow, conduct a statistical test, and verify the significance of the overlapping links between the drug pipeline and supply chain layers. Our results suggest a strong connection between open innovation in the pharmaceutical industry and firms’ economic activities in the supply chain. 


 “Trade network reconstruction and simulation with changes in trade policy”

Y. Ikeda, H. Iyetomi, 
Evolutionary and Institutional Economics Review, 15, 2, 495-513, 2018/12 

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The interdependent nature of the global economy has become stronger with increases in international trade and investment. We propose a new model to reconstruct the international trade network and associated cost network by maximizing entropy based on local information about inward and outward trade. We show that the trade network can be successfully reconstructed using the proposed model. In addition to this reconstruction, we simulated structural changes in the international trade network caused by changing trade tariffs in the context of the government’s trade policy. The simulation for the FOOD category shows that import of FOOD from the US to Japan increase drastically by halving the import cost. Meanwhile, the simulation for the MACHINERY category shows that exports from Japan to the US decrease drastically by doubling the export cost, while exports to the EU increased. 


 “Who buys what, where: Reconstruction of the international trade flows by commodity and industry”,

Y. Ikeda,

Complex Networks & Their Applications V (Studies in Computational Intelligence Volume 693)

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We developed a model to reconstruct the international trade network by considering both commodities and industry sectors in order to study the effects of reduced trade costs. First, we estimated trade costs to reproduce WIOD and NBERUN data. Using these costs, we estimated the trade costs of sector specific trade by types of commodities. We successfully reconstructed sector-specific trade for each types of commodities by maximizing the configuration entropy with the estimated costs. In WIOD, trade is actively conducted between the same industry sectors. On the other hand, in NBER-UN, trade is actively conducted between neighboring countries. This seems like a contradiction. We conducted community analysis for the reconstructed sector-specific trade network by type of commodities. The community analysis showed that products are actively traded among same industry sectors in neighboring countries. Therefore the observed features of the community structure for WIOD and NBER-UN are complementary.


“Community Dynamics and Controllability of G7 Global Production Network”

Y. Ikeda, 
11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 391-397, 

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We study G7 Global Production Network constructed using production index time series from January 1998to January 2015 for G7 countries. Collective motion of G7Global Production Network is analyzed using complex Hilbert principal component analysis, community analysis for single layer network and multiplex networks, and structural controllability. Through tout this analysis we characterize features of collective motion for G7 Global Production Network during economic crisis in 2008.


“Community Structure and Dynamics of the Industry Sector-Specific International-Trade-Network”
Y. Ikeda, H. Iyetomi, T. Mizuno, T. Ohnishi, T. Watanabe,

“Correlated performance of firms in a transaction network”
Y. Ikeda, H. Aoyama, H. Iyetomi, Y. Fujiwara, W. Souma, 
Journal of Economic Interaction and Coordination, 3, 1, 73-80, 2008/06 


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