"Container transportation service demand simulation model for United St" by Meifeng Luo

Date of Award

2002

Degree Type

Dissertation

First Advisor

Thomas A. Grigalunas

Abstract

Investment in container ports and associated multimodal facilities raise difficult economic issues and present major societal challenges. Attempts to resolve these issues require development of new methods and extensions of existing approaches drawing upon advances in simulation techniques and their integration with economic theory. Demand for container port services is a critical factor for the economic analysis of, and decision making for, container port development. However, practical methods for demand estimation often are not convincing, while formal research in transportation demand estimation has not been extended to the practical use of container port demand estimation. This dissertation designed, developed, and implemented a multimodal container transportation simulation model. It takes as given, the quantity of international containerized trade and the existing multimodal transportation system, and assumes the containers be transported along a least-cost route from source to market. The cost includes the fees paid to the transportation services, and the inventory cost. The estimated demand separates the effect of the supply side, and measures only the substitution effect of the existing ports. The simulation efforts in this research included the national and state highway system, and the railway system. It includes 14 existing major US ports, with 6 in East Coast, 4 in West Coast and 4 in Gulf Coast. Foreign countries are grouped into continents, with Asia divided into West Asia and East Asia by Singapore. The developed software was applied to the demand analysis for a hypothetical port at Quonset Point, Rhode Island, USA. The application includes the estimated demand under existing conditions, demand changes with rail improvement, and with competition by the eastern Canadian ports of Halifax and Montreal. This dissertation contributes to the container port demand estimation literature, and provides a new tool for decision makers and business operators concerned with multimodal container transportation facility development.

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