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Correlations, hierarchies and networks of the world's automotive companies

机译：世界汽车公司的关联性，层次结构和网络

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We investigate, within the scope of econophysics, the correlations, hierarchies and networks of the world's automotive companies over the 2003-2010 period by using the concept of a minimal spanning tree (MST) and hierarchical tree (HT). We derive a hierarchical organization and construct the MSTs and HTs for the 2003-2010 period and illustrate how the MSTs and their associated HTs developed over time. These periods are divided into two subperiods, such as 2003-2006 and 2007-2010, in order to test various time-windows and understand the temporal evolution of the correlation structure over time. We perform the bootstrap techniques to investigate a value of the statistical reliability to the links of the MSTs. We also use average linkage cluster analysis (ALCA) to observe the cluster structure more clearly in HTs. From the structural topologies of these trees, we identify different clusters of companies according to their geographical proximity and economic ties. Our results show that some companies are more important within the network, due to a tighter connection with other companies. We also find that these important companies play a predominant role in the world's automotive industry.
机译：在经济物理学的范围内，我们使用最小生成树（MST）和层次树（HT）的概念，研究了全球汽车公司在2003-2010年期间的相关性，层次结构和网络。我们得出一个层次化的组织并构建2003-2010年期间的MST和HT，并说明了MST及其关联的HT如何随着时间的发展。这些时段分为两个子时段，例如2003-2006和2007-2010，以测试各种时间窗口并了解相关结构随时间的演变。我们执行自举技术来调​​查MST链接的统计可靠性值。我们还使用平均连锁聚类分析（ALCA）来更清楚地观察HT中的聚类结构。从这些树的结构拓扑中，我们根据其地理位置和经济联系来识别不同的公司集群。我们的结果表明，由于与其他公司的联系更加紧密，一些公司在网络中更重要。我们还发现，这些重要的公司在世界汽车行业中起着主导作用。

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