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.     

The effect of LCCs operations and scheduled services deregulation on air charter business in Japan

Recent aviation deregulation is producing structural changes within leisure industries in many parts of the world. This paper reviews the development of low cost carriers (LCCs) and assesses its effects on both of domestic and international charter markets in Japan since 2007. Furthermore, this paper analyzes the effect of scheduled services deregulation on international tourism to Japanese regional areas in relation to charter services. The results suggest that in the domestic market, LCC operations have seldom impacted charter traffic due to the differences in target markets and routes. In the international market, LCCs launched scheduled services to Japan but mainly on high demand routes. The deregulation of scheduled services led to a passenger shift from charters to newly scheduled flights and a concentration of tourist arrivals in regional centres. It also led to a decline in international tourist arrivals in some remote destinations. This paper indicates a current trend in which charter business is still an important sector in aviation and leisure markets.     

An assessment of delivery changes for UK terminal air navigation services

In order to meet government contestability policy ambitions, the United Kingdom Civil Aviation Authority (CAA) has undertaken a range of initiatives to create a competitive market for terminal air navigation services (TANS). This paper examines the critical dynamics underlying recent TANS service delivery changes at the nine United Kingdom airports that fall within the Single European Sky performance scheme (SES) using industry data and Porter's five forces model. Interviews with CAA, NATS and airport operators, along with publically available material, are used to explore the various elements impacting competition for TANS at these airports. Competition is intense among a very small number of companies. In addition to optimizing service cost, airport operators require greater value for money including alignment to strategic-operational goals, closer integration with other airside functions and payment structures that are performance based. Gatwick and Birmingham airports changed service provisions due to concerns about the value for money proposition offered by NATS Services Ltd (NSL). This paper also illustrates how competition has changed the customer orientation of NSL. It has been forced to evolve quickly from an expensive, perceived as somewhat arrogant, organisation to one that must be capable of aligning to the cost and service requirements of its customers. Importantly for the ATM industry this paper provides evidence that competition drives lower service costs and provides greater value for money for airlines and airport operators.     

Study of emerging air taxi network operation using discrete-event systems simulation approach

This research focuses on understanding the air taxi operations to determine the number of air taxis required to fulfill the demand for urban air mobility in New York City (NYC). We leverage the Define, Measure, Analyze, Design, and Verify (DMADV) framework and integrate it with the systems simulation approach. Upon investigation, we find that all the parameters linearly impact the vehicle utilization, while other measures are robust, specifically with respect to the seating capacity. It is also recommended to operate initially with 70 air taxis in NYC to achieve a trade-off between customer wait time and vehicle utilization. The proposed approach can act as a recommender system for air taxi companies.     

Strategic design of precautionary measures for airport passengers in times of global health crisis Covid 19: Parametric modelling and processing algorithms

Presently, the negative results of a pandemic loom in a threatening manner on an international scale. Facilities such as airports have contributed significantly to the global spread of the COVID-19 virus. Therefore, in order to address this challenge, studies on sanitary risk management and the proper application of countermeasures should be carried out. To measure the consequences over passenger flow, simulation modelling has been set up at Casablanca Mohammed V International Airport. Several scenarios using daily traffic data were run in different circumstances. This allowed the development of some assumptions regarding the overall capacity of the airport. The proposed simulations make it possible to calculate the number of passengers to be processed in accordance with the available check-in counters based on the proposed sanitary measures.     

Exploring characteristics of passengers using traditional and low-cost airlines: A case study of Belgrade Airport

Low cost carriers entered the Serbian air travel market after Serbia joined the European Common Aviation Area (ECAA) in 2006, prompting the development of healthy competition among airlines and resulting in significant traffic increase at Belgrade Airport. The aim of this paper is to examine the characteristics of passengers traveling on low-cost carriers (LCC) in comparison with those traveling on traditional airlines by using cluster analysis, and to provide practical implications to airport management in tailoring their strategies to meet growing demand. A comprehensive passenger survey was recently conducted at Belgrade Airport on the routes where competition between traditional and LCC carrier exists. The results reveal that emigrants, primarily encouraged by favorable fares, constitute a substantial portion of LCC passengers. Affordable service offered by LCC has also been a positive stimulus for emigrants, who purchase tickets for their friends and relatives to visit them in their host countries. On the other hand, passengers using traditional airlines could be generally classified into two segments, those who fly on business and those who fly for leisure purposes, and each had specific needs when choosing their airline.     

The relationship between airport image,national identity and passengers delight: A case study of the Malaysian low cost carrier terminal (LCCT)

This study examines the relationship between airport image and passengers delight in the context of a low cost carrier terminal in Malaysia. It also seeks to investigate the moderating effect of the airport's national identity on the predicted relationship between the two main constructs. The research, involving 200 passengers (foreign tourists), employed Hierarchical Moderated Regression as the main method of data analysis. The results revealed that there is a strong positive relationship between the airport image and passengers delight, and that national identity helps strengthen the relationship of the main effect.     

Estimating the impact of COVID-19 on air travel in the medium and long term using neural network and Monte Carlo simulation

The COVID-19 pandemic has had a substantial impact on the airline industry. Air travel in the United States declined in 2020 with significantly lower domestic and international flights. The dynamic change and uncertainty in the trend of COVID-19 have made it difficult to predict future air travel. This paper aims at developing and testing neural network models that predict domestic and international air travel in the medium and long term based on residents' daily trips by distance, economic condition, COVID-19 severity, and travel restrictions. Data in the United States from various sources were used to train and validate the neural network models, and Monte Carlo simulations were constructed to predict air travel under uncertainty of the pandemic and economic growth. The results show that weekly economic index (WEI) is the most important predictor for air travel. Additionally, daily trips by distance play a more important role in the prediction of domestic air travel than the international one, while travel restrictions seem to have an impact on both. Sensitivity analysis results for four different scenarios indicate that air travel in the future is more sensitive to the change in WEI than the changes in COVID-19 variables. Additionally, even in the best-case scenario, when the pandemic is over and the economy is back to normal, it still takes several years for air travel to return to normal, as before the pandemic. The findings have significant contributions to the literature in COVID-19's impact on air transportation and air travel prediction.     

Service quality in a mid-sized air terminal: A SEM-MIMIC ordinal probit accounting for travel,sociodemographic, and user-type heterogeneity

Service quality of the airline industry is still unexplored, if compared to the public transport service quality literature. In this paper, we propose an analysis of the services provided by an Italian airport based on an SEM approach. Specifically, we propose a SEM-MIMIC ordinal Probit capturing the heterogeneity in perceptions of air transport passengers and identify groups of passengers with similar assessments of the services. Results suggest the presence of four constructs affecting the overall satisfaction at the terminal, namely information, control, environment, and food service. Results also suggest that there are two different user-types: accessory user (who uses ticket office, luggage trolleys, and escalator lifts), and technology user (who uses charging stations, airport website, and airport wi-fi).     

Evaluation of the spatial pattern of logistics facilities using urban logistics land-use and traffic simulator

Despite the growing research interests on the spatial restructuring of logistics facilities that occurred in many cities around the world, the relationship between the spatial pattern of logistics land use and the level of externalities is far from being elucidated. We use the Urban Logistics Land-use and Traffic Simulator (ULLTRA-SIM), developed for the Tokyo Metropolitan Area, to evaluate the level of externalities that accompany different spatial distribution patterns of logistics facilities. The ULLTRA-SIM takes a novel approach to analyze the urban freight impacts through the simulations of logistics facility locations, urban logistics chains, and truck flow. The results indicate that, while the moderate concentration and deconcentration of logistics facilities do not significantly affect the level of externalities, scarcity of logistics facilities in or near the high demand locations exacerbates negative externalities. Also, the results of the simulations underscore the need for rigorous analysis in order to reduce negative externalities through logistics land use policies.     

A general framework for collecting and analysing the tracking data of cruise passengers at the destination

Cruise passengers’ behaviour at the destination is a rather poorly investigated phenomenon. The single exit/entry point and the relatively brief visiting time, which characterize cruise passengers’ experience at their destinations, make the use of GPS technology particularly suitable for the analysis of such a relevant phenomenon. The aim of this research is to propose a general framework for collecting and analysing GPS tracking data relating to cruise passengers’ behaviour at their destination. The main prerequisites and research stages for the implementation of surveys on cruise passengers will be described and a set of tools and measures for the analysis of GPS tracking data will be proposed, together with their potential applications. As examples of case studies, two surveys performed in the ports of Palermo and Dubrovnik will be described and the main results of the collated information will be presented. Improving our understanding of the behaviour of cruise passengers at their destination is particularly relevant for the management of tourism destinations, given the challenges that this growing phenomenon is posing for many port destinations in the Mediterranean.     

The benefits of codesharing and antitrust immunity for international passengers,with an application to the Star alliance

This paper summarizes and extends the empirical findings of previous research by the author, which analyzed the effect of airline cooperation on the level of interline fares paid by international passengers. The analysis focuses on three measures of cooperation: alliance membership, codesharing, and antitrust immunity. The results show that, together, these three forms of cooperation lead to a substantial 27 percent reduction in interline fares. The paper then computes the aggregate benefits from antitrust immunity and codesharing for the Star Alliance's interline passengers. The immunity enjoyed by the Star partners generated an aggregate benefit of about $80 million per year for interline passengers in 1999. Codesharing among Star partners yielded a further annual benefit of around $20 million. Moreover, if cooperation within the Star Alliance had expanded through an extension of antitrust immunity to those 1999 partners who did not enjoy it, then $20 million of additional benefits would have been generated.     

Short-term forecasting of air passenger by using hybrid seasonal decomposition and least squares support vector regression approaches

In this study, two hybrid approaches based on seasonal decomposition and least squares support vector regression (LSSVR) model are proposed for short-term forecasting of air passenger. In the formulation of the proposed hybrid approaches, the air passenger time series is first decomposed into three components: trend-cycle component, seasonal factor and irregular component. Then the LSSVR model is used to predict the components independently and these prediction results of the components are combined as an aggregated output. Empirical analysis shows that the proposed hybrid approaches are better than other time series models, indicating that they are promising tools to predict complex time series with high volatility and irregularity.     

An analysis of trends in air travel behaviour using four related SP datasets collected between 2000 and 2005

A growing number of studies of air travel behaviour make use of data collected through stated choice surveys. However, while these studies all produce useful results in their own right, they are limited to the context of each specific study. We address this issue by using data from four related surveys carried out between 2000 and 2005. The analysis shows a level of consistency in some of the sensitivities, but also highlights trends such as reduced willingness-to-pay measures, potentially influenced by the growing number of low cost flight options, lack of service differentiation among the carriers, and increased use of online ticketing, which has led to greater fare transparency.     

An investigation of air accidents in Nigeria using the Human Factors Analysis and Classification System (HFACS) framework

Increasing air traffic growth has been achieved along with substantial improvement in safety globally. While air traffic is equally growing in Nigeria, safety levels do not appear to be growing side by side. This was gleaned from the spate of accidents and fatalities recorded in the last couple of decades. The study therefore set out to assess safety performance in Nigeria's air transport industry by comparing accidents and fatality rates with global average levels during the period 1985–2008. A content analysis of the accident reports was done using the Human Factors Analysis Classification System (HFACS) as a conceptual framework; this was augmented with results of industry experts assessment of the Nigerian aviation industry. Their assessments were also discussed in the context of the conceptual framework. Accidents and passenger fatality rates in Nigeria were higher than global average figures for most of the years included in the analysis period. Findings on aircraft ages show that these are also higher than world average levels. The aviation industry experts' assessment presented various challenges which include inadequate airport facilities, absence of timely meteorological information and dearth of skilled personnel in Nigeria's aviation industry. The content analysis of the accident reports using the HFACS shows that skill based errors; physical environment and inadequate supervision are the most frequently occurring categories influencing accident occurrences. The Chi-square and Fishers's test used to analyze significant relationships in the HFACS categories obtained in the accident reports showed five pairs of significant associations between adjacent categories. Based on these associations, Supervisory Violations:-Crew Resource Management:- Decision Errors path is deemed the most potent for accident occurrences. Findings from the research point to the need to address personnel skill, physical environment issues (mostly weather related) and supervisory competence.     

Performance requirements of future Trajectory Prediction and Conflict Detection and Resolution tools within SESAR and NextGen: Framework for the derivation and discussion

Future Air Traffic Management will increasingly be based on a strategic, collaborative and automated concept of operations. A key prerequisite is the capability to guarantee common situational awareness amongst relevant stakeholders as a function of time, extrapolated into the future in order to strategically optimise safe air traffic flow. This is achieved with Decision Support Tools (DSTs), including Trajectory Prediction (TP) and Conflict Detection and Resolution (CDR) tools. The functions and requirements which these tools must fulfil are dependent upon the application within the concept of operations. In order to optimise the development of the DSTs, it is important to understand the requirements for each of the applications. This paper reviews the key functions of the TP and CDR elements of DSTs in relation to these applications. It discusses the key performance drivers, derives performance metrics and develops a framework for the derivation of TP and CDR performance requirements, to support industry and standardisation bodies in the harmonisation process. A mapping exercise is undertaken to identify which of the functionalities are supported by state-of-the-art TP and CDR tools (in the public domain) and establishes those that require further research and development, highlighting some of the key challenges.     

A model for time of day and mode choice using error components logit

The severity of road congestion not only depends on the relation between traffic volumes and network capacity, but also on the distribution of car traffic among different time periods during the day. A new error components logit model for the joint choice of time of day and mode is presented, estimated on stated preference data for car and train travellers in The Netherlands. The results indicate that time of day choice in The Netherlands is sensitive to changes in peak travel time and cost and that policies that increase these peak attributes will lead to peak spreading.     

Istanbul Airport (IGA) and quest of best competitive strategy for air cargo carriers in new competition environment: A fuzzy multi-criteria approach

Our paper determines the best competitive strategy that can be implemented by existing and potential air cargo carriers in the Turkish Air Cargo Industry with the operationalization of Istanbul Airport (IGA) and reveals the competitiveness level of the industry for four bases. We look at the competitiveness levels by analyzing the competitive environment of the industry nationally and internationally both before and post IGA (estimated). We use fuzzy TOPSIS (FTOPSIS) based on the Fuzzy AHP (FAHP) to handle vagueness, which is inherent in the nature of new competition conditions integrating the framework of Porter's five forces analysis. In our study, we use the five forces as our main criteria (with a total of 19 sub-criteria) and the competitive strategies as our alternatives. Our results reveal that the cost-focused strategy is the best competitive strategy that can be implemented by existing and potential carriers in the industry. Another significant result underscores the fact that IGA increases the competitiveness level of the Turkish Air Cargo Industry both nationally and internationally to a fairly high level. Also, the threat of potential competitors is first among the five forces in the industry's new conditions. Our study fills the gap in the literature on the effects of major structural changes in an air cargo industry on the competition among carriers.     

Calculating load factors for the transatlantic airline market using supply and demand data – A note on the identification of gaps in the available airline statistics

This paper takes a critical view of the verification of load factors for the direct transatlantic airline market by combining supply and demand-data. The supply-related data originate from the Official Airline Guide, a well-known data source that contains information on scheduled flights. The demand-related data originate from the Marketing Information Data Transfer database, a data set containing information on actual airline bookings. Combining both data sets enables us to calculate the seat occupancy of direct flights between North-West Europe and the US for 2001. Based on the results, we assess the utility of the joint use of these data sources for aviation economic research, and identify various gaps in the available airline statistics.