A trip-level multi-dimensional approach for the operational efficiency analysis of container vessel trips based on automatic identification system data

Understanding the operational efficiency of container vessel trips defined as voyages between two ports is important for the key container shipping stakeholders such as shippers, ship operators, port operators, and port authorities. This study, thus, aims to comprehensively and critically analyze the operation efficiency of container vessel trips by developing a tailored trip-level multi-dimensional approach based on Automatic Identification System (AIS) data, with four novel ratio-based efficiency indicators proposed to critically analyze the efficiency performance of container vessel trips. This approach first extracts container vessel trips from AIS data, and calculates the stage-level container vessel states and the efficiency indicators. We then conduct behavior clustering on container vessel trips using the proposed indicators. We successfully utilize the AIS data between the China–Singapore maritime trade corridor as a case study, where container vessel trips from the ports of Shanghai, Guangzhou, Shenzhen, and Qinzhou to the port of Singapore are studied, and the major findings are identified. Based on the findings, we provide managerial suggestions for the relevant stakeholders, e.g. port Shenzhen presents the highest operation efficiency when transporting containerized commodities from China to Singapore, indicating shippers should increase their business share in port Shenzhen. Some potential future research directions are provided.