ANALYSIS OF CONTAINERIZED GRAIN, DRIED DISTILLERS’ GRAINS, AND OTHER FEED COMMODITIES EXPORTS AND INLAND MOVEMENT

Abstract

Containerized shipping has become an increasingly important method for transporting bulky products. This research investigates different topic areas associated with containerized grain, Dried Distillated Grain, and other feed (DDG&oF) shipping. It covers both inland movement and exports from the United States. The first part of the research provides a descriptive analysis of U.S. containerized DDG&oF shipping trends, using the PIERS database. This part examines variations by origin, port of departure, commodity type, and destination country. The results are visualized using charts and spatial maps and show the amount of shipped grains, DDG&oF in containers versus bulk shipments. In addition, it shows when the containerized grain started declining, in which commodities, and for which exporting ports. This part of the research aims to provide an understanding of shifts that occurred in recent years. The second part of the research is a prescriptive analysis using a Linear Programming transshipment model to optimize the inland transportation of containerized grain. Using data from the Surface Transportation Board and Freight Analysis Framework, the optimization model minimizes total logistics costs by considering transportation, operational, and freight expenses in both rail and highway modes. It also evaluates potential new inland terminal locations and uses sensitivity analysis to test the robustness of the model under varying conditions. Third, the research explores the mode of choice between container vessels and bulk carriers for exporting DDG and other feed (DDG&oF), a major U.S. agricultural export. A Beta regression model is applied to PIERS data, focusing on shipments to top destination countries. This analysis identifies the most influential key factors that affect transportation mode decisions, such as shipping prices, exchange rate, Index of Industrial Production, and more. The findings address gaps in current literature regarding DDG&oF modal choice and contribute new insights into optimizing international agricultural logistics. In addition, the study applied multicollinearity analysis to ensure the correlation of independent variables. Together, studies provide a comprehensive analysis of containerized grain export trends, logistics optimization strategies, and shipper decision-making in modal selection. The research offers practical implications for improving cost-efficiency, network design, and policy considerations in the evolving landscape of U.S. agricultural exports.