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In this paper, we empirically test the relationship between the delay of containerships and the scheduled operations in a terminal, based on a dataset containing information on 352 containership arrivals during a 9-month period at seven terminals of three North American ports. We find that a vessel is less likely to be delayed when there are more operations scheduled shortly (up to 3 days) after the vessel’s berthing window in the terminal. Moreover, we also find that the more containers a vessel needs to unload in the terminal, the less likely that it would be delayed. Both findings support the hypothesis that liners strategically balance the trade-off between delay cost and schedule recovery cost.

In this paper we introduce an analytical framework based on discrete Likelihood Maximization techniques that provides estimates of operational level data of Queuing models and Transportation networks based on snapshots of data on movements of commodities in a network. We apply our methodology to detailed data on movements of containers imported from S.E. Asian ports to marine ports on the west coast of Canada, unloaded at these ports, moved to rail cars, and transported by rail to destinations in U.S. and Canada. We show how one can estimate operational level parameters such as the number of servers at the ports, schedules of departure and capacity of trains, and even speed of trains based on only snapshots of container movements in the network. Subsequently, we were able to calibrate the entire inter-continental transportation network, were able to identify the sources of variability in the network and were able to measure the reliability of the network to shocks.

In this paper we propose a framework for shift-level container scheduling and resource allocation decisions at a cross-dock facility. The Multi-Mode Resource-Constrained Cross-Dock Scheduling Problem (MRCDSP) approach minimizes material flow and schedules inbound and outbound containers to dock-doors such that the total processing time is minimized subject to the resource constraints at the cross-dock. While container scheduling and resource allocation problems at cross-dock facilities have been studied previously in isolation, our work is the first to consider a complete view of cross-dock operations providing optimal container to dock-door allocation, and a makespan minimizing schedule of containers to the cross-dock. We present a comprehensive framework that includes identification of container clusters to reduce the problem size, a container-to-dock-door assignment algorithm, and a container clusters scheduling model that is solvable for practically sized problems. In a comparative numeric study based on data simulating a cross-dock facility, our approach is shown to outperform current practice, reducing the average time required for processing a set of containers by 37% and reducing the weighted-distance material traveled within the cross-dock by 45%.

The paper examines the strategic vertical relationship between network and regional airlines. We develop a model to illustrate how network airlines can use the contractual relationship with regional airlines as an efficient tool to simultaneously drive out inefficient network airlines and also accommodate other cost efficient network airlines in any specific market. The model is tested on U.S. data using simultaneous and sequential choice models. We find that market size, cost differences between network airlines, as well as cost differences between network and regional airlines, are the chief determinants of the network airlines’ decisions on whether or not to serve a market with their own fleet, as well as how many regional airlines to contract with.

We empirically test the relationship between containership delay and expected terminal congestion, based on information on 352 containership arrivals during a 9 months period at 7 terminals of 3 North American ports. We find that containership delay is negatively correlated with the scheduled operation volumes in a terminal in the immediate future after its scheduled berthing window. Moreover, we find that the more containers a ship needs to unload in the terminal, the less likely that it would delay. These results confirm that liners make strategic adjustment when facing the trade-off between delay cost and cost of schedule recovery.