Analyzing Cargo Loss Severity of Electronics Products with Decision Tree

Abstract

Supply chain risk management has been an essential issue in recent years. Cargo loss in supply chain and logistics activities has been the major cause of delays and supply chain disruption; however, rarely do studies provide comprehensive studies focusing on cargo loss analysis and prevention in various modes of transportation. Hence, this study aims to investigate the cargo loss severity of an electronics company. Decision tree analysis is adapted to develop classification models for cargo loss severity of electronics products. The empirical results with the classification rules can be utilized as a cargo loss prediction tool to help managers to make an effective plan on cargo loss prevention.