공급사슬 네트워크에서 노드 수준 척도의 측정에 관한 연구

초록

Purpose: Today, supply chains are becoming bigger, more complex, and are termed as supply chain networks. This paper explores how social network analysis (SNA) methods can be applied to understand supply chain networks. We match the network perspective topological measures with supply network characteristics. Moreover, the study aims to identify the factors or real-life supply networks reflected in the metrics and how well they can role as indicators leading to effective management. Composition/Logic: The network we investigated is composed of 802 nodes and 1255 links based on survey responses from firms in the Gyeongsangnamdo region. Using open source software Gephi 0.9.2, we visualize the network and measure node-level metrics to analyze the supply network context. Findings: The results show that closeness centrality requires additional data on network structure to utilize the measures and nodes that satisfy certain conditions tend to have high betweenness centrality. Based on the observations of the network, we suggested some potential and possible use of the centrality concepts for understanding the supply chain network. Originality/Value: This study contributes by investigating a real supply network using the SNA approach. Throughout the research, we propose discussion points to approach a better managerial implication of the centralities for future research.

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