Modeling aggregate air-travel itinerary shares: logit model development at a major US airline

This study reports the results of aggregate air-travel itinerary share models estimated at the city-pair level for all city-pairs in the US. These models determine the factors that influence airline ridership at the itinerary level and support carrier decision-making. The models are estimated using aggregate multinomial logit methodology and use comprehensive data. Independent variables for the models measure various itinerary service characteristics: level-of-service, connection quality, carrier, carrier market presence, fares, aircraft size and type, and time of day. The results are intuitive, and validation tests indicate that the models outperform existing methods. Finally, the impacts of changing various itinerary service attributes on carrier market share are discussed.     

Analyzing air cargo flows of international routes: an empirical study of Taiwan Taoyuan International Airport

Air cargo demand is an important aspect of the operation and planning of private and public agencies responsible for airports. While most existing studies in this field include only geo-economic characteristics of airports and their hinterlands as explanatory variables, this study develops a gravity model of air cargo flows by trying to incorporate more factors that might influence international air cargo flows of an airport. The model is developed based on the panel data of air cargo services on scheduled routes at Taiwan Taoyuan International Airport during the years 2004-2007. The results indicate that population, air freight rate and three dummy variables, including the regional economic bloc of the “Chinese Circle”(an informal partnership between Hong Kong, Macao, Taiwan and mainland China), the Open Sky Agreements and long established colonial links, are key determinants of international air cargo flows from/to Taiwan. These results suggest a wider array of factors needs to be considered in policy.     

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.     

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.     

Analysis of ground access modes choice King Khaled International Airport, Riyadh, Saudi Arabia

Airports are vital to the transportation system because air travel is the fastest means of transporting people and goods around the world. Airports also connect aviation systems with other modes of transportation.As a result, access modes to airports are critical to the aviation system, and studying air passenger decisions regarding mode choice is an essential part of airport management and system planning.Though there has been systematic analysis of car use to access airports, there has been less systematic attention to the use of the public transport system, especially the taxi service. The aim of this study is to identify King Khaled International Airport (KKIA) access mode characteristics and users, which has not been investigated previously concentrating on the mix between car and taxi using data collected specifically for this research.More than half (55.5%) of the travelers surveyed arrived at KKIA by private car; taxi and limousine passengers accounted for 42.2% of the sample. The Saudi Public Transit Company (SAPTCO), transported only 2.3% of the air passengers surveyed. These results are similar to findings for an airport in the United States and very different from findings for an airports in the East (e.g., Hong Kong).A binary logit model was developed to evaluate the access mode choice. It was found that income, luggage, travel access time, and nationality significantly affect mode choice.Results provide insight for improved planning of access to KKIA.     

Analyzing airlines market service using panel data

Quarterly panel data covering the largest 10,000 city-pairs in the domestic US from 1998 are used to investigate airlines market entry and exit decisions. Several models are estimated looking at changes in the number of carriers serving in a market. The influence of a number of markets characteristics is examined, including number of passengers, average fare, average yield, service concentration, great circle distance, and seasonality. The results suggest that airlines are more likely to enter a market when market concentration is high and there are high average fares. Also airlines tend to enter new markets in the second quarter, then in the fourth quarter, and then in the third quarter of the year.     

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.     

An AHP analysis of air traffic management with target windows

The main operational concept of Single European Sky ATM Research Programme is the notion of business trajectory. One possible implementation is based on the notion of a contract of objectives; an agreement among the main air traffic management actors on spatial and temporal intervals called target windows. These 4D windows are defined prior to flight departure by the airlines, airports and air navigation service providers to increase punctuality. We use an analytic hierarchy process to assess the opportunity of implementing this concept by considering the views of experts. The findings indicate that there are net benefits for airlines and air navigation service providers but not for airports     

Is increasing aircraft size common practice of airlines at congested airports?

If the overall demand for air transport grows, but additional airport capacity is not available at congested airports, we could assume that airlines will offer flights with more seats in order to cope with the demand. An analysis of frequency and average seat capacity developments at congested, and not yet congested airports, has shown that the hypothesis of bigger aircraft being used in congested situations is valid in most instances, although not at all airports. The objective of this paper is to report on an analysis of the development of average seat capacity at congested airports, in contrast to the situation at not yet congested airports, and to find out the reasons for airlines increasing the number of seats at congested airports, by means of a statistical model using variables including the degree of airport congestion and average flight distance.     

Evidence of passenger preferences for specific types of airports

Studies of air travel choice behaviour increasingly make use of data collected through stated choice surveys. Here, we put forward the hypothesis that when making their choices in such surveys, respondents may complement the information presented to them by additional attributes. Specifically, we look at characteristics linked to airport size and breadth of service, as well as the proximity to a respondent's home. Our findings in a discrete choice analysis suggest that, all else being equal, respondents prefer larger to smaller airports while having a preference for the airport closest to their home. This could suggest that even though respondents associate a higher likelihood of delay and other inconveniences with larger airports, there is a perception that if things go wrong (e.g. flight cancellations), the backup options at larger airports (e.g. replacement aircraft) are superior to those at small or regional ones.     

Applying deep learning models to twitter data to detect airport service quality

Measuring airport service quality (ASQ) is an important process for identifying shortages and suggesting improvements that guide management decisions. This research, introduces a general framework for measuring ASQ using passengers’ tweets about airports. The proposed framework considers tweets in any language, not just in English, to support ASQ evaluation in non-speaking English countries where passengers communicate with other languages. Accordingly, this work uses a large dataset that includes tweets in two languages (English and Arabic) and from four airports. Additionally, to extract passenger evaluations from tweets, our framework applies two different deep learning models (CNN and LSTM) and compares their results. The two models are trained with both general data and data from the aviation domain in order to clarify the effect of data type on model performance. Results show that better performance is achieved with the LSTM model when trained with domain specific data. This study has clear implications for researchers and airport managers aiming to use alternative methods to measure ASQ.     

Small community airport choice behavior analysis: A case study of GTR

The issue of airport selection attracts considerable attention. However, most studies focus on using advanced discrete choice models to analyze airport choice behavior in metropolitan areas with several closely located, competing airports. This paper addresses passengers’ choice behavior in selecting between local small community airports and more distant major commercial airport. It looks at factors affecting air travelers’ airport choice behavior in cities with small community air service. Data relating to the Golden Triangle Regional Airport in Mississippi is used in logistic regressions to identify the key factors that influence air travelers’ airport choices. Ticket price, experience with Golden Triangle Regional Airport and flight schedule were found to be the strongest effects.     

The geographical efficiency of Spain's regional airports: A quantitative analysis

Previous studies of the role of regional airports in the Spanish economy have focused on calculating efficiency using air traffic as the output and airport infrastructure data as the input. We present an alternative quantitative analysis based upon the geographical structure within the airport's market basin. We formulate a ‘geographical efficiency’ model that considers territorial variables within the airport hinterland. Input data for our model include the socio-economic structure of the population, intermodal transport links, industrial and tourism potential and existing leisure-related services. The output is the annual number of passengers associated with such constraints. The result is a relative efficiency estimate that shows uneven patterns of geographical efficiency amongst Spain's regional airports and also provides insights into opportunities for expanding some of these critical items of infrastructure. They suggest that some of Spain's regional airports may be better placed than others to compete in a liberalized market that exhibits a clear tendency in favor of coastal, tourism-based airports.     

A time–space network model for unit load device stock planning in international airline services

Unit load devices (pallets, containers, etc.) are used to move luggage and air cargo on wide-bodied aircraft. This paper examines a case study of the number of devices needed by an airline for international scheduled services. Unit load device movements between airports require planes to load and deliver. The stock of the unit load devices is thus influenced by the airline’s scheduled services. Based on a recurring weekly schedule, this study develops a time–space network to formulate mathematical programming models for minimizing device quantities. This model is applied to assess the preparation level of unit load devices for the various service networks for a Taiwanese airline.     

The impact of the great recession on Irish air travel: An intermodal accessibility analysis

This paper quantifies the changes in accessibility at small area scale arising from the combined effects of dramatic air traffic declines and a greatly expanded motorway network in Ireland during the period of the great recession. The subsequent policy decisions by government are assessed in light of the intermodal accessibility changes identified. The Irish Government engaged in an extensive motorway construction programme throughout the 2000s, greatly increasing the overall length of the inter-urban motorway network. The essential air transport services programme put in place in the 1990s to guarantee a minimum level of air access to disadvantaged regions was significantly reduced at the end of the 2008–2011 period, with only two of the six regional airports continuing to have any form of subsidised public service obligation for the period 2011–2014. In this study, small area datasets are used to measure the net impact of these changes on air transport accessibility in Ireland and the potential spatial inequalities that arise as a result of these changes. An inter-modal accessibility approach is used where the physical characteristics of the road transport network to airports and the network structure characteristics of the air transport system are taken into account to evaluate the levels of air transport accessibility at the small-area district level. Results from the analysis show that the improved surface access to the larger Irish airports (Dublin and Belfast) has enhanced the range of European and global locations directly accessible by air for many communities in Ireland. The net effect of these changes has been to concentrate air traffic at the largest Irish airports.     

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.     

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.     

Spillover effects of the development constraints in London Heathrow Airport

In this article we assess the growth impact of London Heathrow’s development constraints on other airports in the UK. To test the relationship we use a two-stage methodology yielding an estimate of a congestion spillover effect. Our data are passenger traffic from 1990 to 2012 containing both intercontinental and European air traffic. For intercontinental air traffic, our results show high congestion spillover effect between Heathrow and Gatwick airports, and significant but lesser effect to Stansted airport. We also find significant congestion spillover effects from Heathrow to the spatially more distant Manchester and Birmingham airports, showing the extensive spatial impact of Heathrow’s development constraints. For European air traffic, controlling for low-cost air carrier growth, only two airports show significant congestion spillover effects: Gatwick and London City Airports. Illustrating that low-cost carriers do not operate from Heathrow, so its limitations cannot affect the predominant low-cost air traffic in other airports. The novel methodology we present in this paper can be applied to congestion research in general to assess regional and modal spills within networks.     

The impact of national macro-environment exogenous variables on airport efficiency

Our paper tests the extent to which airport efficiency is affected by national macro-environmental factors. The literature on airport performance measurement is extensive but has tended to focus mainly on estimating the effects on efficiency from what are mostly endogenous variables. We undertake a two-stage analysis of 59 international airports observations in the Europe and Asia-Pacific regions. The first stage involves the use of Data Envelopment Analysis (DEA) to measure the efficiency of these airports. This is followed by a second stage, where we use a Truncated Regression model that incorporates the Simar and Wilson bootstrapping technique to test the extent to which a set of macro-environmental factors affect airport efficiency. Results reveal that a state's air transport sector output, institutional quality and robustness, the macro-economic environment, safety and security, and human development, all have a significant influence on the performance of airports. The result of this study fills the gap in the literature related to the non-discretionary variables affecting the performance of airports. It also suggests that policymakers and airport managers consider the identified factors when benchmarking airports.     

The implications of environmental costs on air passenger demand for different airline business models

Various environmental measures, including both regulations and fiscal instruments, have been used at airports globally to reduce the impacts of aircraft noise as well as aircraft engine emissions. Internationally, it is recognized that the costs of environmental and social externalities of air transport must be internalized and paid for by the aviation industry and its users. The use of noise related charges or taxes, which theoretically should be based on their respective social costs, has been proved to be effective at some European airports. This research aims to investigate the impacts of environmental costs, through environmental charges, on air passenger demand for different airline business models. The paper presents the mathematical models measuring the social costs of aircraft noise and engine emissions as a basis for setting up environmental charges. Six intra-European short-haul routes in two city pairs, namely London–Amsterdam and London–Paris, are selected for the empirical analysis. The environmental charges are then hypothetically applied to airlines with two different business models, full service carriers (British Airways and Air France-KLM) and low cost airlines (EasyJet). The results show that the potential percentages of demand reduction for both leisure and business passengers would be higher for Easyjet's markets, although with less environmental cost per passenger.