We assess the value of a marginal change in the number of slots at congested airports from the perspective of the different stakeholders including airports, airlines and passengers. We analyze the trade-off between the benefits, in the form of revenues for airlines and airports as well as greater variety for passengers and the costs that arise from delays. Utilizing a non-parametric structural equation modeling approach, we compare a set of US airports with their first-come first-served policy to those of Europe in which slots are allocated according to grandfather rights. Delays in Europe are much lower than their US counterparts, suggesting that regulation in Europe could be relaxed leading to increased movements and relatively minor increases in delays hence higher overall social welfare. Perhaps surprisingly, we also find that the introduction of slots in the US (or reduction in slots allocated at the four currently constrained airports) would not necessarily increase overall social welfare. In summation, European regulation prevents optimal use of current infrastructure whereas the US system is better able to capitalize on their existing infrastructure.

The existence of positive and negative externalities ought to be considered in a productivity analysis in order to obtain unbiased measures of efficiency. In this research we present an additive style, data envelopment analysis model that considers the production of both negative and positive externalities and permits a limited increase in input utilisation where relevant. The directional economic environmental distance (DEED) function is a unified approach based on a linear program that evaluates the relative inefficiency of the units under examination with respect to a unique reference technology. We discuss the impact of disposability assumptions in depth and demonstrate how different versions of the DEED model improve on models presented in the literature to date.

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%.