Solving airside airport congestion: Why peak runway pricing is not working

The paper examines why peak runway pricing has never been effectively implemented. Some of the literature discussing the theory is examined to show the basis for the theory and the potential for flaws in practice. Three cases where airports attempted to implement peak runway pricing are analyzed. The findings indicate that there may be some institutional barriers to peak pricing theory that prevent effective implementation. Airports and others seeking to reduce congestion might consider focusing their efforts on working towards providing alternatives for passengers, rather than attempting to use peak pricing as a congestion-reduction mechanism in isolation.     

Airport location in multiple airport regions (MARs): The role of land and airside accessibility

This paper approaches the airport location problem as a function of accessibility considerations. First, a structural equation model is established to find the relationship between the size of an airport catchment area and its flight network scale. Landside and airside accessibilities are measured by the qualities and costs of surface transportation and flight networks. The two accessibilities are combined to form a regional air transportation accessibility profile, which can be used as a criterion to evaluate airport locations at a macro-planning level. Finally, the scenarios of airport locations in terms of small and large areas are analyzed using two regional case studies in China.     

Modelling of aircraft rotation in a multiple airport environment

The objective of this paper is to develop a simulation model to simulate aircraft rotation in a multiple airport environment. The developed aircraft rotation model (AR model) consists of two sub-models, namely the aircraft turnaround model, which describes the operation of aircraft turnaround activities at an airport and the Enroute model, which simulates the enroute flight time of an aircraft in the airspace between two airports. Delays due to operational disruptions from aircraft turnaround activities are modelled by stochastic variables in the aircraft turnaround model. Uncertainties from schedule punctuality are modelled by probability density functions in the Enroute model. The proposed aircraft rotation model is employed to carry out a case study by using real schedule and punctuality data from a European schedule airline. Simulation results when compared with observation data validate the effectiveness of the aircraft rotation model. The proposed model is also found suitable for airlines to serve as a schedule planning and analysis tool.     

Analyzing tactical control strategies for aircraft arrivals at an airport using a queuing model

This paper proposes to analyze control strategies for arrival air traffic at an airport using a classical queuing model. The parameters of our model are estimated by means of a data-driven analysis of two years of radar tracks and flight plans for arrival flights at Tokyo International Airport from 2016 to 2017. Our results show that increasing the capacity with one or two more aircraft in the airspace up to 60 NM around the airport significantly mitigates arrival delays, even when assuming future, increased arrival traffic volumes. The outcomes of this study provide insights into the effectiveness of arrival control strategies and are seen as a means to recommend scenarios to be further analyzed with human-in-the-loop simulations.     

A market attraction model for predicting the US market share of large civil aircraft

With global annual sales exceeding $65 billion, the large civil aircraft industry is an important economic and strategic element of the European Union and US economies. Here we define large civil aircraft (LCA) as those aircraft with capacities exceeding 121 passengers and dedicated to the air passenger market served by commercial airlines. This paper employs a transformed log-centered market attraction model to forecast the US market share of LCA. This model specification ensures that the predicted market share is in the range [0,1] and that the sum of all predicted market shares is equal to 1.0, both logical process requirements. In this special case, where there are two producers, the market attraction model becomes a logit regression model. Here we specify the logit regression model as an autoregressive distributed lag model in which US market share is predicted by quantitative and qualitative predictor variables, an autoregressive lag operator and a linear trend component.     

Changes in airport operating procedures and implications for airport strategies post-COVID-19

Covid-19 is demanding a lot of changes in the realm of our daily lives. The aviation industry is also facing unprecedented changes in the management environment. Financial tensions across the sector are rising. This study suggests that the airport strategy's direction focusing on commercial revenue management. After Covid-19, safety and hygiene will be the top priority. As a result, changes in airport operating procedures are inevitable. The most noticeable difference will be the strengthening of the verification process for passengers' health conditions. Dwell time increase can be the by-products. This study identifies a dwell time increase has a more significant impact on increasing the existing purchasers' spending than creating new buyers. Airport operators can introduce a service differentiation perspective, such as a dedicated service, to utilize the current buyers' dwell time more faithfully. Also, the rise of online channels requires airport operators to change sales strategies, reinforcing emotional promotion to stimulate impulse buyers' willingness-to-buy. Before Covid-19, there was little effort to reconcile operation policies and commercial revenue despite the growing importance of revenue management. However, now it is time to change. Pre-Covid-19, passengers were advised of using off-airport processes, such as online check-in and mobile boarding passes. Now, getting passengers to the airport quickly and securing their dwell time can be financially more beneficial. It is necessary to incorporate the commercial revenue perspective into operation policies post-Covid-19 actively. Our finding indicates that even a passenger with solid purchasing power may lose the purchasing intention when assigned to an unfavorable gate or terminal. Airport operators need a better understanding of passenger and flight characteristics when determining operation policy, such as gate allocation or membership services.     

US airport financial reform and its implications for airport efficiency: An exploratory investigation

This study investigates the effect on airport productive efficiency of two major funding sources used by US airports, namely the Airport Improvement Program (AIP) grants and the Passenger Facility Charges (PFC). A two-stage Data Envelopment Analysis (DEA) modeling approach is employed for this purpose. In the first stage, we estimate airport productive efficiency using a variable returns-to-scale DEA model with both desirable and undesirable outputs. In the second stage, random effects regression models are estimated with airport efficiency scores from the first stage as the dependent variable and PFC and a proxy for AIP grants as two of the explanatory variables. By applying the two-stage DEA model to 42 primary US airports, it is found that PFC use has a positive impact on airport productive efficiency, whereas the impact of AIP grants is negative. Multiple counterfactual scenarios are examined by altering the mix of the two types of funding sources. The results show that simultaneously raising the PFC ceiling and decreasing AIP grants could lead to greater airport productive efficiency. The US federal aviation authority would also benefit from realizing these scenarios, especially given the budgetary constraints it faces.     

Stochastic optimization models for the airport gate assignment problem

Uncertainties inherent in the airport traffic may lead to the unavailability of gates for accommodating scheduled flights. Incorporating random disruptions is crucial in constructing effective flight-gate assignments. We consider the gate assignment problem under uncertainty in flight arrival and departure times and develop stochastic programming models incorporating robustness measures based on the number of conflicting flights, idle and buffer times. The proposed models are formulated as large-scale mixed-integer programming problems and tabu search algorithms are implemented to obtain assignments of reasonable quality. We conduct a computational study to analyze the proposed alternate models and show the effectiveness of the solution methods.     

A new approach to quantify the benefit to air travelers resulting from airport capacity expansion

This paper proposes a utility-based methodology to quantify passengers’ benefit resulting from airlines’ adaptation and improvement of service after airport expansion. A numerical example is given to demonstrate its applications in practice.     

Designing a new supply chain for competition against an existing supply chain

We develop a bi-level model for designing an entrant supply chain (SC) in the presence of a pre-existing competing SC where demand is elastic with respect to price and distance. The model assumes dynamic competition between the new and pre-existing SCs in retailers’ level and probabilistic customers’ behavior. Strategic facility location and flow decisions are made while considering inventory carrying costs incurred on the operational level. We formulate the problem and propose exact and metaheuristic algorithms to solve it. The model is solved using data from a real-life case and also randomly generated test problems to extract managerial insights.     

Implications of the ageing society and internationalisation for airport services: A perspective on passenger demand for personal space at airport terminals

“Per-passenger-space” has been used as one of the fundamental units of Level of Service (LOS) measurement to evaluate the capacity of airport terminals for passenger comfort and service satisfaction. This study addresses the questions of how air passengers perceive personal space as an airport service attribute, and how the territoriality of passengers is moderated by their age and cultural background. Participants were grouped depending on their age and nationality for a comparative study. The results from the Repertory Grid Technique (RGT) and open-ended questions supported the conclusion that passengers of different age and cultural backgrounds perceive personal space differently, and their service satisfaction would be partially affected by the availability of personal space within the airport terminal. These findings suggest a necessity for alternative LOS standards that are cost-effective and able to reflect changing age structure and cultural composition of air passengers.     

The impact of airport parking fees on the tourist's airport/airline choice behavior

This paper analyzes the airport/airline choice behavior of tourists for Saxony/Germany. We employ flexible parametric choice methods (mixed logit) in order to test the effect of standard attributes on the choice probability. In addition we extend existing literature with the introduction of parking charges in the choice experiment. Our results show a significant and negative impact of parking charges on airport choice probability. Thus, we can compute high elasticities of parking charges for tourists. These results suggest, that airport managers have in form of parking policies a powerful policy instrument as they can directly affect the size of the airport catchment area.     

Building an assessment model for measuring airport resilience

Airports are some of the most important facilities in any country's transportation system. It is important to protect such critical infrastructure from natural and manmade risks. However, it is difficult to build a risk prediction model based only on past statistical data. An experienced expert-based Multiple Criteria Decision-Making (MCDM) approach could be used to measure an airport's resilience and develop feasible protection strategies. This study proposes a novel assessment model for evaluating airport resilience. The model uses the Bayesian Best Worst Method (Bayesian BWM) to determine the optimal group weights of the criteria, and the modified Preference Ranking Organization Method for Enrichment Evaluations (modified PROMETHEE) technique to calculate the gap between each alternative and the aspiration level. The practicality and effectiveness of the model are demonstrated using Taiwan's airports as an example. In addition, sensitivity analysis and model comparisons are conducted to confirm the reliability of the proposed model. The results show that the proposed assessment system can effectively assist policy makers and airport security departments to formulate improvement strategies, thereby enhancing the resilience of this infrastructure.     

Artificial neural network models for airport capacity prediction

This paper proposes artificial neural network models to predict the arrival/departure capacity of airports. Multilayer perceptron (MLP), recurrent neural networks (RNN), and long short-term memory (LSTM) models have been trained using capacity and meteorological data from Hartsfield–Jackson Atlanta International Airport (ATL) from 2013 to 2017. The models’ predictive performances were validated against the observed capacity of ATL in 2018. The qualitative and quantitative analysis of the trained models confirmed that the artificial neural networks approach is effective in predicting airport capacity. In addition, the transferability of the models for Boston Logan International Airport (BOS) is examined. Capacity prediction performance for BOS measures the transferability of the models trained with the ATL data. MLP showed good transferability without taking any other measures, and RNN and LSTM were able to predict the BOS capacity well after fine-tuning.     

A decision framework for successful private participation in the airport sector

As private participation in public airports becomes a global trend, there are a number of concerns and debates over the conflicting interests of the private and public sectors. For instance, the private sector's interest in maximizing profits often opposes the public sector's interest in protecting the public interest and social welfare. In this paper, we reframe the conflict in terms of principal-agent theory, and inform policymakers to understand public-private management problems in a broader context. Firstly, we demonstrate how various ownership and governance structures shape the private participation based on (1) ownership-type, (2) mode of ownership shift, and (3) ex-post government control. Secondly, we then highlight that this process should be context-based, and examine the recent case of Incheon International Airport (IIA) in South Korea to illustrate the importance of contextual factors. Lastly, we provide comprehensive recommendations to policymakers involved in bringing private partners into the airport sector, which include setting a clear agenda, exercising a reasonable level of control, understanding the sharing of risk and responsibility under different structures, and assessing technical, economic and political factors that may affect the policy outcome.     

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.     

Competition and efficiency in the Italian airport system: new insights from a conditional nonparametric frontier analysis

We analyse the effect of competition on technical efficiency of Italian airports by applying a novel conditional nonparametric frontier analysis for the first time to the airport industry. We find that competition affects mostly the frontier of best performers, whilst airports that are lagging behind are less influenced. A novel two stage approach shows that, on average, competition has a negative impact on technical efficiency. We estimate a measure of pure efficiency, whitened from the main effect of the competition, whose distribution has a bi-modal shape, indicating the existence of two differently managed groups of airports.     

Spatio-temporal fluctuations in the global airport hierarchies

The global air transportation network is responsible for moving millions of domestic and international passengers each year. Not surprisingly, relationships between airports vary widely, due to a myriad of geographic, economic, political and historical determinants. Further, given the dynamic nature of the many influences acting on the air transportation system, inter-airport relationships and the structure of the global air network as a whole are also constantly changing. The purpose of this paper is to explore such spatio-temporal variations in the structure of the global airport hierarchies. Here, we show how the concept of nodal regions can be applied to measure the extent of these variations. To facilitate this analysis, a database of nearly 900 airline carrier schedules and 4650 worldwide origins and destinations, representing a nearly complete record of commercial air travel over a six-year period, is examined. Given this dataset, nodal regions are derived for all airports represented. In general, results suggest that regions associated with individual airports are often relatively dynamic at the yearly as well as quarterly level. Los Angeles International Airport (LAX) is utilized as a local case-study to provide a detailed examination of these dynamics.     

Ratio-based design hour determination for airport passenger terminal facilities

To avoid both over-design and under-sizing of airport passenger terminal facilities such as security checkpoints, the infrastructure is designed for a specifically determined design load. As such, the design load is considered for a short period of time, usually an hour of operation, during which peak, though not necessarily maximum, demand occurs. For strategic planning applications, future design loads can be determined by either fictitious flight schedules or ratio-based models which forecast the relationship between design load and annual demand. This study presents two ratio-based methods which allow the direct determination of design hour loads (DHL) for passenger terminal facilities. The unsaturated DHL model considers the relationship between observed passenger flows in the terminal and aggregated annual demand data. The saturated DHL model includes several operational constraints which limit the actual DHL, such as limitations in the runway system or the fleet mix operating at an airport. Both models are applied to two real-world airports, for which the DHL of the security checkpoint facilities is estimated from large datasets covering multiple years. Results are significant at the 5 % level and suggest that the proposed ratio-based methods are appropriate for airport strategic planning applications.     

The importance of spatial economics for assessing airport competition

This paper explores the relevance of spatial effects on airport competition. Drawing concentric circles of travel distances around it is the most commonly way to define an airport’s catchment area. The characteristics of the catchment area and available substitutes are compared, and assessments of market power made. It is generally recognized that the existence of spatial competition among airports, lies within one market, although sometimes, overlapping circles are examined on the premise that competition lies within these common areas. We look at economic models of spatial competition where there is no overlapping and argue that the stylized facts inferred from economic models of spatial competition have been overlooked. After a short review of airport competition, we introduce economic models for spatial competition and look at the implications of these in the context of airport competition.