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A clustering technique for detecting communities in supply chain network

机译:一种在供应链网络中检测社区的聚类技术

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Currently, network perspective is rapidly becoming trends for representing and analyzing problems across all of the domains from natural science to engineering and management, with no exception in supply chain management. Treating supply chain system as a network give a good advantages since there are a lot of method in network theory that can be applied to give a quantitative measurement. In turns, by applying network theory in supply chain, analyst can come up with better description and representation of their supply chain. This study tried explore a concept of community structure in network theory to identify the groups of suppliers, manufactures, distributors, retailers and customer which is highly connected each other and at the same time get a valuable representation of the large supply chain network. We argued that supply chain network is differ from the common network in which the network analysis commonly works onto, thus the method for detecting community will also became different. Hence, in this paper we addressing a method for detecting community of highly connected firms in supply chain/supply chain network by grouping the node/firm based on their complete flow/chain or commodity flow for short.
机译:当前,从自然科学到工程和管理的整个领域,网络观点正迅速成为代表和分析问题的趋势,供应链管理中也不例外。将供应链系统视为网络具有良好的优势,因为网络理论中有许多方法可用于进行定量测量。反过来,通过在供应链中应用网络理论,分析师可以对供应链进行更好的描述和表示。这项研究试图探索网络理论中的社区结构概念,以识别相互联系紧密的供应商,制造商,分销商,零售商和客户的群体,同时获得大型供应链网络的宝贵代表。我们认为,供应链网络不同于通常进行网络分析的普通网络,因此,社区发现的方法也将有所不同。因此,在本文中,我们提出一种方法,通过根据节点/公司的完整流/链或简短的商品流对节点/公司进行分组,来检测供应链/供应链网络中高度关联的公司的社区。

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