Document Type


Date of Award


Degree Name

Doctor of Philosophy in Transportation - (Ph.D.)


Civil and Environmental Engineering

First Advisor

RongFang Liu

Second Advisor

Athanassios K. Bladikas

Third Advisor

I-Jy Steven Chien

Fourth Advisor

Janice Rhoda Daniel

Fifth Advisor

Shmuel Yahalom


Seaports play a crucial role in the container industry, where they act as important nodes in the transport chain to facilitate international trade. In a competitive market, port capacity plays a significant role in defining its competitive position to attract demand and avoid congestion. Failing to provide suitable capacity results in the loss of market share. Therefore, port decision-makers face the challenge of maintaining and developing suitable port facilities to provide efficient services to port users. One of the aspects that decision-makers consider in the planning and development process is analyzing container demand. The analysis of container demand can be challenging due to the dynamic changes in international trade, port location and accessibility, competition from other ports in the same geographic region, and port selection behavior of shippers and liner companies.

This dissertation focuses on analyzing container demand; specifically, it has two main objectives: Forecasting short-term container demand and assessing the competitiveness position of the port. To forecast demand, the univariate time series stochastic approach is applied based on the methodology of Box-Jenkin, and because it only requires the historical container throughput. The developed model is used to forecast container demand of Jeddah port. The proposed model provides accurate forecasts with a confidence interval of 93 Percent. The systematic forecasting approach provides the ability to update and apply the methodology continuously in the future.

To assess port competitiveness, spatial interaction models (SIM) are applied to estimate the impact of port performance, hinterland accessibility, and geographic location on the container flow. Both temporal and spatial data are collected for the four major ports in Saudi Arabia, which are analyzed in the case studies and SIM calibrations. The analyses performed in this study revealed that port users, as the results of modernization and privatization of the transport sector of the country, are provided with feasible port alternatives to efficiently transport freight, leading to fierce inter-port competition. The analysis also reveals that maritime connectivity of ports located in the Red Sea have a competitive advantage that allow them to attract more container flow and reach further hinterland regions when freight rates increase. This is due to their strategic location in the major maritime shipping routes. However, the availability of railway connectivity provides cheaper inland alternative that restricts the importance of maritime accessibility.

This dissertation should be of interest to policy and port-decision makers. The applied forecast model is important in the planning phase of resource allocation and facility improvements because it provides a reliable instrument to obtain insight into the future demand. The assessment of port competition helps decision-makers in evaluating the impact of port strategies by understanding the competitive position of the ports. Recognizing the scarcity of systematic research on Saudi Arabian seaports suggests that these forms of forecast analysis and competitive assessment will benefit the port sector in the country.



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