Vessel Speed Analytics Using Satellite-Based Ship Position Data

In the maritime supply chain, sailing speed is a key variable governing ship-to-air emissions and the profitability of vessels. While there can be substantial economic gains to be had from dynamic speed optimization, real-life constraints such as weather conditions, contractual limitations and supply chain considerations may govern the speed choice in practice. The increasing availability of high frequency ship positions and vessel speeds reported by the terrestrial and satellite-based Automated Identification System (AIS) enables formal empirical testing of the determinants of vessel speed. We use a panel data set of nearly 62,000 weekly average speed observations for a fleet of 607 Very Large Crude oil Carriers (VLCCs) during 2013 - 2015 to estimate a multiple regression model with technical, operational and macro-economic variables. We find that macroeconomic variables have a marginal influence only on ballast speeds, while laden speeds are influenced mainly by whether the operator is also the cargo owner.