In supply chain management, existing studies have primarily focused on classifying and managing suppliers on value and risk of supply to purchasing companies. In particular, the value of the Supplier was valued at the attributes of the supplier's data, such as turnover, assets, liabilities, production levels. Recent studies are underway to evaluate suppliers from a new point of view using network analytics, but they are still deficient. This study differs from the traditional vendor evaluation method by using social networking analysis to interpret the implications of each vendor's status in the network and to identify potential values they previously failed to recognize. Social network analysis was applied to 641 automobile makers and component companies in Korea based on the data of the automobile industry manual in 2016. As a result, Degree and closeness centrality showed similar results to that of traditional enterprise assessment methods. The highly evaluated companies were the automakers and their affiliates of larger conglomerates. However, the results of the Betweeness centrality were derived entirely differently. Smaller companies were found that could not be recognized by traditional assessment methods for highly Betweeness centrality firms. The study provides a key indicator to identify potential critical suppliers by presenting new criteria for evaluating vendors.


Network analysis, Social network analysis, Supply chain management, Automotive industry, Supplier assessment method