Air and high-speed rail transport integration on profits and welfare: Effects of air-rail connecting time

Air-rail integration has become a popular idea to relieve airport congestion and environmental impact of transport industry, especially amid the fast expansion of high-speed rail network around the world. This study examines the circumstances under which air-rail integration can be better justified, by focusing on the effects of reducing air-rail connecting time on transport operators' profits, consumer surplus, and social welfare. We show that while consumers always benefit from less air-rail connecting time (an integrated hub with seamless transfer between air and rail services is always preferred by passengers), operators of the two modes, air transport and high-speed rail, won't have an incentive to integrate unless the cost of integration is sufficiently low. Nonetheless, reducing air-rail connecting time enhances total surplus when the hub airport suffers from a certain degree of capacity constraint and the cost of air-rail integration is not too high.     

Hub airport slot Re-allocation and subsidy policy to speed up air traffic recovery amid COVID-19 pandemic --- case on the Chinese airline market

With international air travels largely banned around the world amid the global COVID-19 pandemic, many gateway and hub airports have more ideal slots available for reallocation. Airport traffic recovery replaces airport congestion to become the primary challenge of major airports around the world. With the pandemic well controlled domestically in China, the government liberalizes the hub airport slots for those previously forbidden services to the small/regional airports. This paper thus analytically examines the effect of this slot liberalization. The government subsidy to the small airports has also been considered. It is found that the slot liberalization can speed up airport traffic recovery for both hub and small airports. The hub airport slot liberalization leads to a lower level of minimum subsidy to sustain the survival of the small airports. Given any fixed level of subsidy to the small airport, both the total airport traffic and social welfare would improve with the slot liberalization at the hub airport. When the government can adjust the level of subsidy after liberalizing the hub airport slots, the subsidy could be excessive, if the government emphasizes too much on airport traffic recovery. This would, however, harm the overall social welfare.     

A large neighborhood search heuristic to establish an optimal ad-hoc hubbing strategy in the wake of a large-scale airport outage

Abrupt airport outages can cause diversions and fuel-critical situations for flights, leading to costly passenger misconnections. We develop a large neighborhood search heuristic to optimize the rerouting of flights bound for a disrupted airport to a hub airport that is not disrupted, with the goal of accommodating passengers on existing flights departing the non-disrupted hub. The objective of the heuristic is to identify and reroute flights to the ad-hoc hub(s) – non-disrupted hub airport(s) – that minimize the sum of passenger travel time and wait time. We minimize the passenger cost as the sum of passenger travel time to the diversion airport and wait time for a connecting flight at the ad-hoc hub airport, subject to on-board fuel and diversion airport capacity constraints. We use the heuristic to determine how a coordinated traffic management strategy could have diverted flights immediately following a real-world airport outage.     

Long-term route traffic forecasts and flight schedule pattern for a medium-sized European airport

This paper develops a methodology for assessing the future route network and flight schedule at a medium-sized European airport. The starting point is the existing origin and destination demand from the base airport across the world. This is expanded using growth rates by country or region for the period up to year 2015. The future origin and destination demand is then converted into route traffic, subject to a threshold for direct service. Where demand falls below this level, traffic is reallocated via various appropriate hubs. A model of frequency and aircraft size is applied to estimate the future air service on each route and a schedule created, allocating these flights to specific times of day. The scenario where the base airport operates as a hub is then investigated. This involves identifying a suitable hub model, considering geographical and competitive issues. The origin and destination demand is increased, resulting in an enlarged network of routes. Flights are then scheduled within the constraints of an optimal wave pattern. The outputs are of considerable interest in long-term airport planning and also offer an insight into future airline network strategies and opportunities.     

Airline network structure and the gravity model

In this paper, we determine characteristics of the cost-minimizing airline network under economies of density. Airline demand is asymmetric and governed by the gravity model. Airline networks are restricted to those where each spoke city is assigned to a single hub and where hub cities are fully interconnected. The cost-minimizing network is a mixture of a point-to-point and a single hub network. Multi-hub networks where passengers change planes at more than one airport are found to be suboptimal.     

Flight delay impact on airfare and flight frequency: A comprehensive assessment

This paper presents a comprehensive empirical analysis of flight delay impact on airfare and flight frequency in the US air transportation system. We model airfare and flight frequency as functions of cost and demand characteristics, competition effects, and flight delays at origin, destination, and intermediate hub airports. Estimation results confirm that airlines tend to pass delay cost onto passengers through higher fare, whereas delay has an upward effect on flight frequency. We find that proportionate airport delay reduction across the system can result in annual fare reduction in the order of billion dollars.     

Modeling the joint choice of access modes and flight routes with parallel structure and random heterogeneity

This study focuses on the influence of ground access transportation on air travel. The error components logit model with parallel structure is first adopted to formulate the joint choice behavior of access, airports, and flights. The proposed model proves to be effective in exploring interdependence between choice dimensions and travelers heterogeneity. The empirical results indicate that fare discounting should be introduced at the city airport and the frequency of existing flight routes should be increased. To benefit the hub airport, authorities of the new airport mass rapid transit system should reconsider the tradeoff between time and cost for express trains.     

The determinants of aeronautical charges of U.S. airports: A spatial analysis

Using U.S. airport data from 2009 through 2016, this study examines the determinants of aeronautical charges of large and medium hub airports and accounts for the spatial dependence of neighboring airports in a spatial panel regression model. Our results show that U.S. airports' aeronautical charges are spatially dependent, and neighboring airport charges are positively correlated, implying that U.S. airports are in price competition with each other even though they are government-owned infrastructure. Additionally, we find evidence of airport cost recovery through non-aeronautical revenues. This may be indicative of the airport's cross-subsidizing aeronautical operations with non-aeronautical revenues. In addition, we found the airports that share revenues with airlines charge lower aeronautical fees than those that do not share revenues. We also found that more congested airports charge higher aeronautical fees.     

Airline delay management problem with airport capacity constraints and priority decisions

This paper deals with the Airline Delay Management Problem (ADMP), which can be described as the task of dealing with daily airline operational delays and deciding whether to delay subsequent flights at a hub airport or to have them departing on time. An innovative integer linear programming approach is presented to the capacitated case of the ADMP and airport limitations in terms of bay availability, taxiway capacity and runway separation are incorporated to represent capacity constraints. Fuel cost, passenger compensation, and passenger inconvenience costs are included in the objective function. The decision variables include the re-timing of flight departures and arrivals, the use of the airport capacity over time and the rebooking of passengers in case of missed connections. To guarantee the linearity of the optimization model and fast computational times, a receding horizon modeling framework is adopted. The approach is applied to a case study using real operational and passenger data from an international hub-and-spoke carrier. The case study shows the capability of the linear model to deal with a complete day of operations within a few minutes. The results suggest that the proposed approach can lead to cost reductions of almost 30% during recovery, when compared with the solution from the airline. In addition, a sensitivity analysis is provided to investigate the impact of not including passenger inconvenience costs and of reducing runway capacity.     

The impact of airport fees on fares for the leisure air travel market: The case of Spain

Panel data is used to determine the incidence of airport fees on fares in the Spanish leisure market airlines. We also study its structure through an empirical specification of a pricing and demand equation system. The results show the existence of market power, strategic behavior and density economics. We also demonstrate that airlines pass all the airport fees onto customers by increasing fares. Furthermore, we find that the behavior of airlines in routes with the presence of low cost carriers do not differ from other routes.     

The role of schedule delays on passengers’ choice of access modes: A case study of Japan’s international hub airports

We empirically study passenger modal-choice behavior to access an international hub airport, by using stated preference (SP) data and by constructing a binomial logit model. We found that passenger modal choice is affected by the service level of the access modes: travel time, travel cost, waiting time, and delay cost. The results also indicate that if passengers choose access mode in advance they consider service frequency: departure timing from home, and the arrival timing at the airport. Moreover, our results indicate that travelers’ willingness to pay for saving time differs by time of a day. They are apt to pay more in the morning than in the afternoon. These outcomes must contribute to improve the access flight service from local to hub airports to handle the needs of passengers.     

Hierarchical multimodal hub location problem with time-definite deliveries

Hierarchical multimodal hub location problem is a cost-minimizing hub covering problem where two types of hubs and hub links, accounting for ground and air transportation, are to be established, while ensuring time-definite deliveries. We propose a mixed-integer programming formulation and perform a comprehensive sensitivity analysis on the Turkish network. We show that the locations of airport hubs are less sensitive to the cost parameters compared to the locations of ground hubs and it is possible to improve the service quality at not much additional cost in the resulting multimodal networks. Our methodology provides the means for a detailed trade-off analysis.     

Hierarchical multimodal hub location problem with time-definite deliveries

Hierarchical multimodal hub location problem is a cost-minimizing hub covering problem where two types of hubs and hub links, accounting for ground and air transportation, are to be established, while ensuring time-definite deliveries. We propose a mixed-integer programming formulation and perform a comprehensive sensitivity analysis on the Turkish network. We show that the locations of airport hubs are less sensitive to the cost parameters compared to the locations of ground hubs and it is possible to improve the service quality at not much additional cost in the resulting multimodal networks. Our methodology provides the means for a detailed trade-off analysis.     

Estimating the sensitivity of small airport catchments to competition from larger airports: A case study in Indiana

An accurate estimation of airport catchment area enables airlines and airport operators to make informed decisions and to target potential markets precisely. This study uses the state of Indiana as a case study to estimate traffic leakage from the local airport, Indianapolis International Airport (IND), to two large hub airports in Illinois, the neighboring state of Indiana, namely Chicago O'Hare International Airport (ORD) and Chicago Midway International Airport (MDW). By using a decision making model that considers flying cost and access cost, this study simulates from local passengers' perspective which origin airport delivers the most cost effective flight itinerary. Using the top 20 routes of IND in 2018 as model inputs, the catchment area of two Chicago based airports in Indiana with variable coverage is plotted for different traveling scenarios. The analysis shows that an airport catchment area is sensitive to location, service level and traffic volume of competing airports nearby, as well as purpose of travel (business or leisure), number of travelers in a group (single, couple, family or multiple), length of trip, destination (domestic or international), preference of airlines (network carrier or budget carrier), and frequent flyer program status (premier member or general member). These findings could be valuable to all three aforementioned airports as well as airlines serving these airports when allocating operational and marketing resources. More importantly, this study creates a generic model that could be used by virtually any airport to estimate scenario-based catchment area using readily available itinerary and spatial data without resorting to expensive passenger surveys.     

Optimizing flight equencing and gate assignment considering terminal configuration and walking time

Operating airline hub-and-spoke networks (HSN) rather than direct flights among city pairs may significantly reduce supplier cost; however, passengers' travel time may significantly increase due to increased transfer and in-flight time. The costs considered in this study are hub-related and incurred by passengers and aircraft (i.e., passenger transfer, flight dwelling, and gate occupancy). The objective is to minimize the total cost by optimizing flight sequence (i.e., arrivals and departures) and gate assignment, while considering transfer speed, transfer demand, flight size, gate size and terminal configuration. A real-world HSN whose hub airport (HA) is located at Xianyang International Airport (XIY) in Xi'an, China is analyzed. The optimized solutions and their relations to various model parameters are explored.     

Expanding airport capacity of cities under uncertainty: Strategies to mitigate congestion

Airport capacity constraints are increasingly challenging the growth of air traffic. At the same time, decision-making about airport capacity investments is extremely complex, involving trade-offs. This paper’s objective is to optimise a privately owned airport system’s capacity investment decision in a city under demand uncertainty. Next to the investment size, our real options model incorporates the timing of the investment, as well as the cost of congestion. The results reveal that the larger a city’s initial airport capacity, the smaller its investment will relatively be and the lower the occupancy rate threshold at which investment will take place. We also show that, in case of a higher demand growth combined with more demand uncertainty, the city will benefit from a significantly larger investment, but made later at a higher occupancy rate. In this case, cities with a small initial capacity will sometimes even more than double current capacity. Higher airport charges and an increase in non-aeronautical revenues both lead to a later investment in more capacity, due to the increased project attractiveness. An increase in congestion costs results in a larger investment made earlier, in order to eliminate delays. Airport operational cost and capacity holding cost increases both lead to smaller investments.     

Supply-and-demand models for exploring relationships between smaller airports and neighboring hub airports in the U.S.

Airport passenger leakage is the phenomenon of air passengers choosing to travel longer distances to access more extensive air services offered by airlines at an out-of-region hub (or, substitute) airport, instead of using their local airports. Airport leakage can cause further reduction in services offered by airlines at a local airport, thereby causing even further leakage, and so on, which can significantly impact an airport's role in the growth of the local economy. This paper explores the geographic and operational attributes of local-and-substitute airport pairs in the United States, explicitly accounting for the interactive feedback relationship between passenger volumes and air service characteristics that contribute to the onset, persistence, and exacerbation of airport passenger leakage. A two-stage least squares regression model of air passenger demand at small- and medium-sized airports is first presented, where local passengers may travel by vehicle to larger, out-of-region hub airports. The results confirm that airfare and passenger volume relationships exist between the local and substitute airport pairs included in the dataset, and that lower airfares at the substitute airport have a greater impact on airport choices made by larger travel groups. They also suggest the existence of positive feedback in that if an airport attracts increasingly smaller passenger numbers with fewer air services and fewer air services with fewer passengers, without external intervention airport leakage impacts may be irreversible and exacerbate over time. A conceptual market share equilibrium analysis is used to illustrate the mechanisms of a direct two-way feedback relationship between passenger volumes at a local airport and air service characteristics at both the local and substitute airports. With data, this quantitative framework can help guide airport planners in further assessing and verifying suspected passenger leakage issues at their airport. The results suggest that without intervention, airport leakage impacts may be difficult to reverse; further exacerbating the trend are technological advancements that make driving cheaper and easier (connected and autonomous vehicles). However, the results can also guide planners in choosing the types and degrees of infrastructure investments and airline incentives that may be used to expand or retain air services to attract passengers.     

The effect of de-hubbing on airfares

This paper studies the price effect of de-hubbing, which occurs when an airline ceases hub operations at an airport. We develop a simple theoretical model to study the impact of de-hubbing on prices and quantities of direct flights at the hub airport. Using an event study of seven cases of de-hubbing between 1993 and 2009, we analyze how average airfares change following de-hubbing. Consistent with the theoretical implications, the empirical results suggest that airfares decrease when there is a low-cost carrier presence at the de-hubbed airport, whereas airfares increase when the de-hubbed airport is not serviced by a low-cost carrier.     

Airport pricing systems in europe and an application of Ramsey pricing to Spanish airports

This paper describes the landing fee structures which are prevalent at most European airports: a mix of weight-based landing fees, passenger fees, and other charges. The paper describes alternative pricing systems which emphasize economic efficiency rather than airport finance considerations. Finally the paper calculates the structure of landing fees for a hypothetical uncongested airport using a Ramsey pricing formulation with data representative of uncongested Spanish airports. Further research is necessary before recommending implementation because the elasticities of demand and operating costs with distance are borrowed from North American studies.