Data Driven Freight Performance Analysis: A Case of Logistics Cluster

The shift of the U.S. economy towards services and the expanded trade with North America, Europe, and the Asian Pacific Rim have resulted in a significant increase of goods movement through our freight logistics clusters and modes connecting those. These freight logistics clusters face unique operational, tactical and strategic planning challenges which will threaten the U.S. economic competitiveness if adequate measures and solutions are not pursued. In many cases, these freight logistics clusters and their connecting network perform inefficiently and hence impacting freight movement negatively. This research focused on performance analysis of the port of Gulfport, a logistics cluster in Mississippi based on data analytics using GPS data. The port of Gulfport and the potential for increased truck freight volume with the expansion of the Panama Canal could create a serious problem in moving truck freight away from the port to the Interstate system. The excess of truck traffic along non-interstate roads throughout the state increases the need for road repair and perhaps reveal areas for future improvement of roads. The techniques used in this paper would be useful for any state survey of logistics clusters that can acquire GPS data and help policy makers to make the right decisions