A clustering technique for detecting communities in supply chain network

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.