为深入分析中国汽车行业成本传导机理,以广州市汽车行业为例,将汽车行业生产链条上的成本传导转化为相应上中下游价格指数同步变化,将2001年1月—2012年11月历年各月原油价格（上游)、石棉瓦刹车片和汽车配件价格（中游)、汽车销售价格（下游)4种价格指数符号化,建立了广州汽车行业成本同步传导网络。研究了该网络的度分布、加权集聚系数、平均最短路径长度、中介中心性以及社团结构等网络动力学性质。研究发现,模态顶点强度服从广延指数分布,网络平均最短路的距离为3.48,模态之间转换出现短程关联性,17个主导节点在网络模态转化中发挥关键性的控制作用,主次模态均有向主模态转换的倾向。采用Newman等的社团算法,把网络分为3个社团,社团内部结构表明价格上涨和下降趋势在形成社团中发挥十分重要的作用。
In order to study the automobile cost transmission mechanism and strengthen cost forecasting and controlling of automotive industry, the paper transformed respectively the January 2001-November 2012 monthly price of crude oil （upstream), asbestos brake pads and auto parts（midstream), automobile sales （downstream) into symbolic sequences consisting of three characters （R, e, D) with symbolic dynamics. Monthly Symbol group is treated as nodes, connected nodes in chronological order, established automobile cost transmission synchronization complex networks of Guangzhou. The paper studied the degree distribution, the weighted clustering coefficient, average shortest path length, and community structure of network. The study found that peak intensity distribution followed the extension of exponential distribution. The average path length was 3.48, the conduction between nodes showed short-range correlation. The top 17 nodes in centrality measure play a key role of controlling the mode conversion, Major and minor nodes have a tendency to the normal node. The network is divided into three communities using Newman algorithms. The rise and decline trend play a very important role in the formation of associations.
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