A deterministic model was developed to study the effects of inefficient scheduling on flight delays at hub airports. The model bases the delay calculation on published schedule data and on user-defined airport capacities. Data from the Official Airline Guide of May, 1977 and May, 1985 was used for the analysis. Twelve large airports were studied in the hopes of finding a correlation between airport delay due to congestion and hubs. Data for both time periods was analyzed for the twelve airports in order to find historical trends in the growth of hubbing. Among the airports studied, those that were hubs had significantly more delays due to inefficient scheduling than the non-hubs, even for an equivalent number of operations. Also, these relative inefficiencies were shown to exist from hub to hub. Delays at hubs of similar size differed by up to 200 percent.

I study delays and congestion patterns in U.S. hub airports during periods of high flight volume. I find that these periods are longer when the share of flights operated by the hub airline is greater, and these longer periods exhibit shorter delays. These results lend support to recent theoretical work on congestion, implying that hub-airlines take into account the impact of their scheduling decisions on the congestion that they bear. The results may suggest that congestion management solutions implemented at hub airports dominated by one airline could have only a limited impact on congestion in general.

This study examines hub-carrier scheduling and hub-airport congestion pricing using a simple hub-spoke network model incorporating both schedule delays and congestion delays. We find that in the short-middle run, where aircraft size is given exogenously, hub-airport congestion tolls are not needed at the social optimum if the (negative) congestion delay effect is more or less offset by the (positive) schedule delay effect. In the long run, where aircraft size is decided endogenously, at the social optimum, it is not necessary to impose congestion tolls via a per-flight charge or via per-passenger charges. This is in stark contrast to the results of existing literature. Interestingly, we further find that when the per-flight charge is weight related, a profit-maximizing (privatized) hub airport imposes schedule and congestion delay costs via per-flight charges, but there are no delay cost terms in the private optimal per-passenger charges. However, when the per-flight charge is movement related, it imposes schedule and congestion delay costs via both per-flight charges and per-passenger charges. These “private” optimal congestion-pricing rules provide useful insights into privatized, or profit-maximizing/emphasizing, hub airports.

"We examine two factors that might explain the extent of air traffic delays in the United States: network benefits due to hubbing and congestion externalities. Airline hubs enable passengers to cross-connect to many destinations, thus creating network benefits that increase in the number of markets served from the hub. Delays are the equilibrium outcome of a hub airline equating high marginal benefits from hubbing with the marginal cost of delays. Congestion externalities are created when airlines do not consider that adding flights may lead to increased delays for other air carriers. In this case, delays represent a market failure. Using data on all domestic flights by major US carriers from 1988-2000, we find that delays are increasing in hubbing activity at an airport and decreasing in market concentration but the hubbing effect dominates empirically. In addition, most delays due to hubbing actually accrue to the hub carrier, primarily because the hub carrier clusters its flights in short spans of time in order to maximize passenger interconnections. Non hub flights at hub airports operate with minimal additional travel time by avoiding the congested peak connecting times of the hub carrier. These results suggest that an optimal congestion tax would have a relatively small impact on air traffic delays since hub carriers already internalize most of the costs of hubbing and a tax that did not take the network benefits of hubbing into account could reduce social welfare"--National Bureau of Economic Research web site.

The U.S. air transportation system is dominated by a network of large hub airports. When airline schedule disruptions occur, as a result of meteorological or technical disturbances, the entire national air transportation system can be substantially delayed. This study evaluated the feasibility of using an alternate or reliever hub to connect transfer passengers who otherwise would have flights delayed or canceled as a result of disturbances at the hub airport. The study developed criteria for selecting an alternate hub and evaluated the feasibility of using an alternate hub for the Dallas-Fort Worth International Airport. This study also developed a genetic algorithm for optimizing an alternate schedule of flights into and out of the alternate hub to minimize direct operating costs and passenger delay. Based upon a case study that used the Austin Bergstrom International Airport as an alternate hub for Dallas-Fort Worth International Airport, the research concluded that it would be feasible and profitable to construct the necessary infrastructure to operate the alternate hub in Austin.