Evaluation of level of service for transfer passengers at airports

Transfer passengers have quite different needs than those of originating and terminating passengers. For example, they do not make use of airport access roads. Other facilities may or may not be used depending on the type of transfers, the airport's operational configuration and the airline services. Despite the increasing importance of transfer passengers for airport operations, little research has been done to determine their needs. This study analyses transfer passengers’ views on the quality of services at the terminal building, using data collected at Bandaranaike International Airport in Sri Lanka, which aspires along with the airline ‘Sri Lankan’ to be a major hub for South Asia. Regression analysis was used to identify the transfer passenger facilities and services with the strongest effect on the overall perception of level of service. The application of regression analysis to the data collected at Bandaranaike International Airport shows that the courtesy of the security check staff and the quality of the Flight Information Display are among the most valued by transfer passengers at that airport.     

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.     

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.     

Passengers perceptions of airport branding strategies: The case of Tom Jobim International Airport – RIOgaleão,Brazil

This study examines the passengers perceptions of Tom Jobim International Airport – RIOgaleão branding strategies and its impact to their experiences in light of the airport branding elements proposed by the literature. To achieve these aims it was conducted a semi-structured interview with the airport's branding manager and a questionnaire with the passengers (n = 92). The findings showed that the airport's new management company has been employing tourist branding strategies using a mix of elements, but it is possible that these actions have had the main objective of raising the airport to international service standards, whereby the operation of terminals by large companies is a trend. It was also concluded that some of the airport branding elements (i.e. logos and slogans) are well developed and represent a higher impact on passenger experience, while others (i.e. retail pricing strategies) require further attention and new approaches in order to improve passenger experience in the terminal.     

Development of level of service standards for airport facilities: Application to São Paulo International Airport

A methodology for developing level of service (LOS) standards at airport passenger terminals based on user perceptions is developed. The underlying concept is the derivation of quantitative values for passenger perceptions of service based on airport surveys. The check-in counter component is evaluated considering factors that have a bearing on the user perceptions of LOS: processing time, waiting time, and space available per person. The study uses data obtained from a passenger survey conducted at São Paulo/Guarulhos International Airport, Brazil. The results indicate that we can derive quantitative perception scales from qualitative survey data. Finally, a multi-attribute analysis is done to obtain a composite evaluation of LOS at the check-in counter as a function of the waiting time, processing time, and space available.     

An operations research model for the evaluation of an airport terminal: SLAM (simple landside aggregate model)

The Simple Landside Aggregate Model (SLAM) is a model for estimating capacity and delays in airport passenger terminals. SLAM is designed to answer “what if” questions about alternative configurations of the various processing and holding facilities in a terminal. It consists of a network of modules, one for each facility of the terminal. These modules are based on a set of quite simple mathematical formulas to be used for the estimation of the capacity of each facility (in terms of passengers per hour) and the level of service (LOS) associated with it. LOS is quantified both in terms of “space available per facility occupant” and waiting time for being processed.     

Sizing of processing and holding air terminal facilities for charter passengers using simulation tools

Charter passengers represent a category of airport users that imposes uncommon operating conditions to airport terminal facilities, which, if not anticipated, may result in a low level of service. This is usually the case of airports serving areas of tourist attraction where growth in demand of charter flights has made them the dominant passenger flow. This paper presents a simulation model that enables the investigation of charter passenger effects on air terminal facilities and enables the estimation of the level of service offered. Some of the model’s features can be easily implemented by use of spreadsheets. The paper concludes with a critical assessment of the results arisen in the master plan of two Greek airports where the simulation model was implemented.     

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.     

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.     

An airport operations proposal for a pandemic-free air travel

The aviation industry needs to work on the resilience of air travel against health threats and regain passenger trust. This paper proposes a pandemic-free travel concept based on creating an infectious diseases free zone in the airport terminal building through screening of passengers, crews and airport workers. This research shows that infectious disease detection methods applicable at the airport could be available in a short timeframe, at affordable cost and in scale. The potential location of passenger health screening, facilitation requirements, health responsibilities delegation and appropriate usage of industry standards for regulations are key elements to a potential implementation that would be phased and long term.     

Whether low-cost-carrier passengers spend more on duty-free goods at the airport? Evidence from Incheon International Airport

With a dramatic growth in the low-cost carrier (LCC) traffic around the world, many airports have built budget terminals to accommodate the LCC flights with cheaper airport charge to the airlines but inferior shopping environment and service quality to the passengers. This study aims to answer the following research questions: i). Whether the LCC passengers have higher purchasing power than FSC (full-service carrier) passengers for the airport concessions, particularly the duty-free goods? ii). Would the budget terminal design contribute to or jeopardize the LCC passengers' airport concession expenditure? iii). How could the airport operator maximize its concession revenue by re-designing terminal or re-allocating flight slots? We collect the actual airport duty-free transaction data from Incheon International Airport (ICN) for an empirical investigation. Our empirical evidence first suggests that LCC passengers could have comparable or even higher purchasing power than FSC passengers in consuming duty-free goods at the airport. Among all the LCC passengers, Chinese have the highest purchasing power. Second, the inferior shopping environment and service quality of budget terminal seriously jeopardize the duty-free sales from the LCC passengers. Third, counterfactual analyses show that, if ICN could convert its budget terminal into a conventional terminal, 44 million USD more duty-free sales can be generated per year. Even keeping the current terminal design, re-allocating the LCC flights between the budget terminal and conventional terminal could bring approximately 4.9 million USD more duty-free sales per year. The findings provide managerial implications to ICN and other airports for effective airport revenue management. First, the budget terminal design may not be ideal to accommodate LCC traffic as it damages the concession revenue from particular LCC passengers with high purchasing power. Second, exploring the concession revenue from the growing LCC traffic could help maintain an airport's advantage in aeronautical charge under single-till regulation.     

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.     

Key drivers of passengers' overall satisfaction at klia2 terminal

The purpose of this study is to examine the airport service quality dimensions based on the ASQ survey and investigate the best predictor for overall satisfaction. The context of this study is the klia2 terminal passengers, which are predominantly users of the low-cost carriers at Kuala Lumpur International Airport. Secondary data obtained from the airport operator on the 2016 ASQ survey for the klia2 terminal was analysed using the PLS-SEM method. The grouping and impact of the thirty-three service quality elements from the ASQ survey were tested against the overall satisfaction element. The findings indicated that twenty-two out of the thirty-three elements were valid measures for the klia2 terminal users which forms the eight dimensions i.e. access, airport environment, airport facilities, arrival services, check-in, finding your way, passport and security. Airport environment was found as the best predictor in determining passengers’ overall satisfaction at klia2 terminal and should be given particular focus by the airport operator for continuous improvements.     

Passenger perceptions of service quality: Korean and Australian case studies

This paper investigates air passengers’ perceptions of 11 factors that may influence their buying behaviour namely, in-flight service, reservation-related service, airport service, reliability, employee service, flight availability, perceived price, passenger satisfaction, perceived value, airline image, and overall service quality. Analysis of variance and an independent sample t-test are applied to data collected from Korean and Australian international air passengers. The results reveal that passenger perceptions are significantly different across airlines, seat classes, and usage frequencies.     

Offsite passenger service facilities: A viable option for airport access?

Offsite passenger service facilities transfer passengers from a common location to an airport and may provide additional services such as baggage handling and passenger check-in. Although they are conceptually promising, there is a lack of modern methods specifically tailored to forecast their demand. This paper reports on the development of two sequential models that forecast demand for an offsite facility. Models were calibrated based on data collected at six airports in California, Maryland, Massachusetts, and Virginia. The results showed that likely candidates for an offsite facility are airports that are not easily accessible, and departing air passengers with early morning flight departure times and high variability in ground travel times to the airport. A case study demonstrates the application of the models to Virginia’s Richmond International Airport.     

An application of the airport service quality model in South Africa

Passengers’ expectations of service quality at airports are becoming increasingly important as air traffic grows. This research investigated passengers’ perceptions of airport service quality at O.R. Tambo International Airport, South Africa. An existing model placing the concept of passenger expectations central to measuring an airport’s specific level of performance was applied. The results proved significant in terms of the investment made by the airport in staff training and highlighted areas for improvement. The results show that business travellers and leisure travellers have different opinions regarding the importance of services offered by airports and of the level of performance at ORTIA in particular. Significant differences also occur in the perceptions of frequent travellers and infrequent travellers.     

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.     

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.     

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.     

Access mode choice for relocated airports: the new Athens International Airport

To estimate the capacity requirements for all access related facilities of a new airport and to set pricing or operational policies it is necessary to forecast the share of each transport mode that airport passengers use. The development of these forecasts cannot be based on mere transfer of experience from other airports, particularly in the modern era of wide regulatory reforms, liberalization of the aviation market and increasing airport competition. First access modal split at the existing airport is determined via passenger classification and discrete choice modeling. Both are conducted via a passenger survey study specifically designed for this purpose. The resulting models are then employed to forecast access modal splits for the relocated airport by proper adjustment of the attribute values. The method is applied to the new Athens International Airport.