论文标题
全球供应链网络的领结结构和社区识别
Bow-tie structure and community identification of global supply chain network
论文作者
论文摘要
我们在全球供应链网络中研究全球供应链网络的拓扑特性和程度度相关性。全球供应链数据是通过从2018年从标准普尔的Capital IQ平台网站收集各种公司数据来构建的。内部和级别的分布的特征在于具有级计数的功率法= 2.42且高度指数= 2.11。聚类系数作为功率定律衰减，指数= 0.46。节点度度相关性表明缺乏分类性。 GWCC的领结结构表明，OUT组件是最大的，占公司总公司的41.1％。 GSCC组件占公司总公司的16.4％。我们观察到上游或下游侧的公司大多位于距GSCC几步之遥。此外，我们发现网络的社区结构，并根据其位置和行业分类来表征它们。我们观察到，最大的社区由主要基于美国的消费者酌处部门组成。这些公司属于全球供应链网络领结结构中的OUT组件。最后，我们确认了命题S1（短路径长度），S2（幂律学位分布），S3（高聚类系数），S4（“ Fit-Gets-Richer-Richer”生长机制），S5（幂律分布分布的截断）和S7（在全球供应链网络中的社区结构）（社区结构）。
We study on topological properties of global supply chain network in terms of degree distribution, hierarchical structure, and degree-degree correlation in the global supply chain network. The global supply chain data is constructed by collecting various company data from the web site of Standard & Poor's Capital IQ platform in 2018. The in- and out-degree distributions are characterized by a power law with in-degree exponent = 2.42 and out-degree exponent = 2.11. The clustering coefficient decays as power law with an exponent = 0.46. The nodal degree-degree correlation indicates the absence of assortativity. The Bow-tie structure of GWCC reveals that the OUT component is the largest and it consists 41.1% of total firms. The GSCC component comprises 16.4% of total firms. We observe that the firms in the upstream or downstream sides are mostly located a few steps away from the GSCC. Furthermore, we uncover the community structure of the network and characterize them according to their location and industry classification. We observe that the largest community consists of consumer discretionary sector mainly based in the US. These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity for propositions S1 (short path length), S2 (power-law degree distribution), S3 (high clustering coefficient), S4 ("fit-gets-richer" growth mechanism), S5 (truncation of power-law degree distribution), and S7 (community structure with overlapping boundaries) in the global supply chain network.
