Identification of supply chain disruptions with economic performance of firms using multi-category support vector machines

Abstract

From a practical perspective, a novel method using multi-category support vector machines (MC-SVM) is proposed to identify supply chain disruptions (SCD). With the data related to economic performance from quarter statements and individual announcements published by the listed firms, the variables of MC-SVM are constructed firstly. Secondly, MC-SVM is used for matching the portfolios of firms, which helps the map from economic performance to SCD by applying MC-SVM again. Finally, a case study is given to testify the ability of proposed method with the data from the listed firms in China.

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