Industrial Management & Data Systems
This study aims to clarify the risk management practices of banks as supply chain finance (SCF) service providers. Design/methodology/approach Using 4,014 evaluation and approval reports, this study constructed five risk management factors and examined their functions with secondary data. Two text-mining techniques (i.e. word sense induction, TF-IDF) were used to equip the classic routine of dictionary-based content analysis. This research successfully identified four important risk management factors: relationship-based assessment, asset monitoring, cash flow monitoring and supply chain collaboration. The default-preventing effect of these factors are different and contingent on the type of financing contexts (i.e. preshipment, postshipment).
Computer-aided text analysis
Supply chain finance