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.     

Segmentation of passenger preferences for using digital technologies at airports in Norway

Airports are increasingly focused on implementing digital technologies at key stages of the airport journey to enhance the passenger experience. However, passengers have different preferences. TwoStep Cluster Analysis is used to reveal the presence of distinct segments according to their preferences. The findings are based on a survey of 6082 passengers at airports in Norway. Three distinct segments are identified: those that prefer traditional manual processes, those that prefer automated technology-based processes, and those that prefer more personalised technology-based processes. Significant differences are revealed for each segment according to passenger and trip characteristics and opinions regarding how the use of digital technologies at airports impact on personal privacy and human dignity. The findings contribute to knowledge on passenger preferences at airports and can help to inform airport decision making.     

Relevance of airport accessibility and airport competition

Airport accessibility is an important criterion for airport competition. The relevance of airport accessibility and airport competition was studied in this paper based on the panel data collected from nine large airports in Jiangsu province, China from 2005 to 2014. The results showed that the cost of expense, time and fatigue for the arrival at the airport are proposed to quantify levels of fastness, economy and amenity for the passengers to arrive at airport. The airport accessibility is significantly affected by airport passenger traffic and airline frequency. The passenger traffic can be increased by 2% with 1% increase of airport accessibility based on the analysis results of the nine large airports in Jiangsu province.     

Improving US airport taxicab services through governance arrangements

Most airports internationally have implemented customer satisfaction programs into their operations to increase non-aeronautical revenues. In the US, taxicabs are an essential airport transport mode given the limited public transport options available. Effective airport taxicab planning efforts can increase airport customer satisfaction levels, as well as facilitate handling increased airport passenger volumes. However, little is known on how US airports have adapted their governance practices from a traditional hierarchical to a network approach in their efforts to undertake airport taxicab planning initiatives since the deregulation of the transportation industry. Data acquired from 51 US hub airports is used to examine their existing taxicab planning practices. The findings offer how US airports can modify governance processes in their airport taxicab planning processes to better support increases in the customer satisfaction levels of airport taxicab patrons.     

Assessment of passenger benefits brought about by international airport projects

This study sets forth a method to calculate the passenger benefits of an international airport project and assesses the passenger benefits brought about by two international airport projects.An international airport project mainly increases the number of flights and the possibility of determining convenient timetables. It does not significantly decrease the flight time of international travel. Thus, the user benefits brought about by an international airport project cannot be expressed by the conventional concept of ‘traveling time’, which is the term generally used.In this study, the ‘Expected Value of Traveling Time’ and ‘Expected Value of Generalized Cost’ are presented as indexes to evaluate improvements in convenience brought about by international airport projects. The passenger benefits of two airport projects in Japan are measured by consumer surplus calculated from the demand function using these indexes.These indexes are accurately calculated taking into consideration factors such as scheduling connections between domestic and international transport, and so enable a grasp not only of reductions in flight time, but also of passenger benefits resulting from international airport projects, such as increases in the number of flights and reductions in the time required to make transfers during domestic travel.     

Measuring airport service quality: A multidimensional approach

Currently, airports are expected to be operated as self-sufficient service organizations providing efficient and high-quality services to a variety of customers. In this context, improving airport service quality (ASQ) has become paramount. However, due to the complexity of the airport service environment, an effective process of measuring and analyzing passenger perceptions of ASQ is not easily achieved. Generic scales for perceived service quality might not cover some particularities of the passenger–airport interaction. Furthermore, while some measurement practices have been developed within the airport industry, there has been only limited consideration for validity and reliability. These concerns are certainly relevant to avoid misinterpreting passenger perceptions. In view of these concerns, this paper has a twofold objective. First, to fit a measurement model for perceived ASQ built on typical service measures within the airport industry. Second, to test for the model's equivalence across groups of passengers. Sample data from an extensive survey applied at a major Brazilian airport was used for confirmatory factor analysis. The results suggested that a six-factor structure provides a meaningful multi-item measurement model for perceived ASQ. The model was validated for international and domestic departing passengers with respect to its factorial structure and metric invariance. The proposed measurement model could be considered an alternative for a multidimensional approach in the context of airport performance measurement regarding service quality. Finally, the findings from this research might contribute to the discussion on passenger perceptions of ASQ, particularly concerning its multidimensionality and the need to review current practices for ASQ analysis.     

Queue behavioural patterns for passengers at airport terminals: A machine learning approach

Passengers go through different handling processes inside airport terminal buildings. The quality of these processes is usually measured by the time passengers require and by the level of comfort experienced by them. We present an analysis of behavioural patterns in queues at check-in desks and security controls, which are two of the most critical processes regarding passenger service. The passengers' flow is simulated to obtain queue lengths at one busy European airport between 2014 and 2016, supported by real flight data. Simulation is designed as a store-and forward cell-based system, whose parameters have been tuned and validated with real data from observations and empirical capacity and demand studies within the airport. Random Forest algorithms are then implemented to develop different models for each parameter prediction, after a data analysis stage based on statistical and visualization methods. Feature analysis techniques between dependent variables and the target outputs (queue lengths) determine which are the fundamental elements to explain queue behaviour and to predict target variables. We provide a method to forecast behavioural patterns at check-in desks and security controls, to help airport operators to implement adequate response policies. Queue behavioural patterns are captured by Machine Learning models, which can be used to offer improved passenger services (such as real-time predictions for expected waiting time at queues), or can be considered in a dynamic approach for terminal services design (as the entire progress of terminal handling depends on the stochastic behaviour of passengers). This could be a key tool for managing passengers demand and optimise the infrastructure's capacity through resource allocation.     

Airport operations and security screening: An examination of social justice

Airports are a crucial part of the United States transportation system and airport officials are continuously challenged to ensure that their operations are secure. A major part of providing airport security is implementing check points where passengers interface with the security screening system. The airlines and airport security administration receive negative publicity when passengers are mistreated at security check points. Further, these organizations spend a lot of time to assess the situation and take corrective actions. This study examines passenger perceived bias and the airport security screening system. Using data from a randomly selected sample of 145 airline passengers, six hypotheses are tested. The hypotheses exam the predictive relationships of control procedures, security personnel training, security personnel professionalism, and security screening systems on passenger perceived bias. Multiple regression analysis is used to test the hypotheses. The research findings indicate that security personnel professionalism is negatively and significantly related to passenger perceived bias. Also, security personnel training and security control procedures are positively and significantly related to security personnel professionalism. Management implications, limitations, and recommendations for future research are offered.     

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.     

The effects of service quality dimensions and passenger characteristics on passenger's overall satisfaction with an airport

The objective of this paper is twofold. First, to identify service quality dimensions related to airports. Second, to examine the effects of those dimensions on passenger's overall satisfaction with an airport together with variables related to passenger characteristics. Data from an extensive survey applied in a main Brazilian international airport were used. Exploratory factor analysis was applied to extract dimensions of airport service quality as perceived by the passengers. The effects on the overall satisfaction level were estimated using a probabilistic approach. Findings underline implications regarding the use of meaningful service dimensions instead of a large set of variables as predictors of passenger satisfaction. Moreover, the study stresses the need for considering how passenger characteristics may be related to different perceived levels of service quality.     

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.     

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.     

Processing passengers efficiently: An analysis of airport processing times for international passengers

With immense and growing pressure on stakeholders in international airport terminals to process passengers faster than previously, there is a great benefit to understanding which factors affect passenger processing times and in which situations. In addition, storing and analysing the collected data in batch is itself a difficult and time consuming task that could be made much simpler with sequential analysis. We aim to present a method for airport managers to discover which variables are important to understanding passenger processing times and identifying problematic passenger profiles without the need for high computational capacity and full historical datasets.In this paper we introduce Bayesian hierarchical models as a method of sequentially processing data, reducing computation time and obviating storage of large amounts of raw data. We use a range of exploratory models to identify which variables are important to predicting passenger processing time using a dataset from a day of operations at an international airport terminal, then compare a range of regression models. A Bayesian hierarchical regression model based on the model of best fit discovered through exploration is then applied to two subsets of data. We demonstrate that sequential updating based on daily data achieves similar results to batch processing based on full historical datasets and can therefore be used as an alternative in appropriate circumstances. Using the presented models, we find that the airline operating a flight is the most important variable to determining passenger processing time, followed by each passenger's age, sex and nationality. We demonstrate that in our dataset, the passenger profiles correlated with higher mean processing times overall were not the same as those passengers most problematic for meeting processing time targets.     

Airport selection criteria of low-cost carriers: A fuzzy analytical hierarchy process

The selection of airport is an important consideration for low-cost carriers (LCCs) to remain cost competitive. The objective of this study is to identify and rank the airport selection criteria of LCCs. Based on reviewing the existing literature, five main factors comprising 16 sub-factors were developed. The factors were first validated by three industry experts from the aviation industry. Thereafter, a survey questionnaire requiring a comparison of the factors was administered on 28 executives who were involved in the strategy planning and formulation of LCCs based in China or Korea. The collected data were analysed using fuzzy analytical hierarchy process (FAHP). In descending order of their importance, the main factors influencing LCCs' selection of airport are (1) airport charges, (2) airport performance, (3) airport growth opportunities, (4) catchment area and (5) airport infrastructure. The top three sub-factors are airport costs, demand for LCC services and passenger throughput. The research contributes to academic research by providing a holistic assessment of the key considerations influencing LCCs' selection of airport. In addition, it implicates policy formulation of LCCs by providing a framework for assessment of airports that are suitable for LCCs’ operations.     

Analyzing passenger behavior in airport terminals based on activity preferences

Airport terminals are facilities that provide a variety of activities related to both the preparation of the passengers for their air trip (aeronautical) and their free time inside the terminal (non-aeronautical). In the last years, the number of non-aeronautical activities has substantially increased and significantly diversified both before and after the security checkpoint. The established role of non-aeronautical activities forces planners and managers to better understand passenger behavior. The potential of discrete choice models for the exploration of passenger behavior is analyzed in this paper. For the demonstration of the methodology, Lisbon Humberto Delgado International airport is used as a case study. Data is collected through a revealed and stated preference survey inside the terminal at the area before the security checkpoint. Activity-choice models are developed to identify the factors that affect the choices of the passengers over the area where they conduct non-aeronautical activities. Forecasts show that when increasing the percentage of passengers who conduct the check-in online and have planned their activities before arriving at the airport, the passengers’ preferences to conduct non-aeronautical activities only after the security checkpoint increase. This paper shows the contribution of developing discrete choice models in the better comprehension of passenger decisions over the activities they perform in an airport terminal.     

Measuring connectivity in the air freight industry

In this paper, we present an air transport connectivity model for air freight. For the purposes of this paper, connectivity is defined as all possible direct and indirect connections to or from an airport operated by wide-body aircraft, weighted for the quality of the connection in terms of transhipment and in-flight times. Using this model, we analyse the networks of seven European airports. Europe’s largest hub airports carry most air freight thanks to their extensive intercontinental passenger networks, while smaller airports with a strong focus on air freight carry large amounts of cargo on dedicated freighter aircraft. For air freight operations, the catchment area of an airport is much larger than it is for passenger services, as shipments are being trucked to their departure airport throughout all of mainland Europe. Since there are many airports sharing the same catchment area, potential competition for air freight is fierce. We found that well located regions between the four large European airports have access to large air freight networks, whilst regional air freight connectivity in northern and southern parts of Europe is substantially lower.     

The impact of terminal re-organisation on belly-hold freight operation chains at airports

While it is widely acknowledged that airport re-organisation from destination to dedicated airline group terminals makes passenger travel more seamless, more efficient and also more profitable for both airlines and airports, there is little known about the impacts of such change on freight and in particular belly-hold cargo chains. Our analysis includes data from all airports in Australia but focuses primarily on the proposed re-organisation of Sydney Kingsford Smith airport. This paper reveals a significant relationship between international freight volumes, terminal organisation and freighter operations. However, our interview results only confirm the volume/aircraft type relationship. The paper aims to contribute to the general discussion on the impact of passenger terminal organisation on belly-hold freight operations and more specifically to the consultation process around airport master planning.     

Does the nature of airport terminal service activities matter? Processing and non-processing service quality,passenger affective image and satisfaction

The surge in air transport demand and the increasingly competitive and volatile market dynamics due to airline deregulation are rapidly transforming airports’ character into multi-service firms and destinations. As a result, service performance measurement of significant systems and their consequent impact on airport users are crucial in creating better airport service design, operation and management for sustainable competitive advantage. The present study 1) assesses the applicability of the Airport Indicators of Passenger Experience (AIPEX) model on Shanghai Pudong International Airport (PVG), and 2) tests a theoretical model that explores the direct and indirect relationships among airport service quality, passenger affective image and satisfaction, as well as the moderating mechanism of passenger type (travel purpose) in these associations. The results indicate that, the AIPEX model fits the PVG context for airport service performance assessment. Also, the theoretical model suggests robust direct associations among processing/non-processing domains and passenger satisfaction, as well as the processing domain and passenger affective image, except non-processing domain and passenger affective image relation. Moreover, significant mediating and moderating effects of passenger affective image and travel purpose on the significant positive direct associations are found. Further, implications for theory and practice are discussed.     

The impact of low-cost carriers on airport choice in the US: A case study of the Washington–Baltimore region

Previous research has shown that low-cost carriers (LCCs) may stimulate traffic at an airport by offering low fares. Using passenger survey data from the Washington–Baltimore region’s three airports, we find that the benefits of LCCs to airports extend beyond the traffic generated directly by the LCCs through their low fares. In addition, we find that the mere presence of an LCC at an airport can attract passengers, even to competing carriers. These “halo effects” from LCC presence increase the significance to airport managers of attracting LCCs in order to generate passenger demand.     

Analysing passenger network changes: The case of Hong Kong

Passenger throughput at Hong Kong International Airport (HKIA) has shown steady growth since its opening. Various aspects relating to HKIA have been studied in prior literature. This paper investigated changes in HKIA's passenger network for the period of 2001–2012 and used the gravity model to examine the key factors explaining its passenger traffic flows. The findings suggested that HKIA's passenger network has changed significantly and expanded to many new different destinations. Two regions (East Asia and Southeast Asia) were the most important markets for HKIA, and most key destinations connected by Hong Kong showed healthy growth. Nine factors could explain passenger traffic flows between Hong Kong and its key destinations: Hong Kong GDP per capita, GDP per capita of destinations connected by HKIA, distance, airport hub status of the destination airport, tourist destinations connected by HKIA, numbers of passenger airlines in service, bilateral trade flows, speaking a common language and having strong cultural/colonial links with Hong Kong, and the route presence of Cathay Pacific.