Locational determinants of major US air passenger markets by metropolitan area

The paper examines the influence of metropolitan characteristics in determining the locations of major air traffic markets in the US. In general, the likelihood of a major air passenger market locating in any given metropolitan area is primarily determined by the metropolitan area's population size and overall propensity for air travel. The study shows that on average, a major air passenger market has over 3 million people while a minor market has a population base of about 760,000. The propensity of a population to fly is mainly a function of a number of social and economic indicators, the most important of which was found to be employment in professional–scientific–technical services and management activities.     

On the multi-dimensionality and sampling of air transport networks

Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.     

Robustness of the air transport network

This paper presents a methodology for the detection of critical airports (those whose isolation would cause the largest losses in network connectivity) in the global air transport network (ATN), based on simulating an attack on selected ATN airports using different adaptive selection criteria. The performances of several node selection criteria are compared, together with a new criterion based on Bonacich power centrality. The results show that most critical airports can be detected with an adaptive strategy based on betweenness centrality. The detection of such airports may help the development of contingency plans to develop an appropriate response to any airport closure.     

An analysis of the determinants of air traffic volume for European metropolitan areas

This paper examines the determinants of air traffic volume in the major European urban regions, highlighting those that depend on the metropolitan features of cities. We used homogeneous urban and airline data that make international comparisons possible. We found that GDP, the level of economic decision-power, tourism functions, and the distance from a major air market account for more than two-thirds of the variation in air service. This seems to indicate that air service remains profoundly rooted in the metropolitan features of urban regions (notably size and decision-power), even if low-cost airlines are probably less linked to the latter because they partly focus on niche markets and regional airports. Much of the remainder is probably attributable to the specificities of the urban economy, to actors’ strategies and to competition from high-speed trains.     

Drivers of long-haul air transport route development

An analysis of long-haul routes identifies trends and patterns underlying their development. Five distinct perspectives: geography, regulation, manufacturers, passengers and airlines are taken to investigate the drivers of long-haul route development. From the insights gained it is inferred that the demand for long-haul aircraft is a complex function thereof, whereby long-haul routes are operated between cities with strong business and social connections as influenced by the dynamics of change and underlying geography.     

The geography of air freight: connections to U.S. metropolitan economies

Despite the rapid growth of air freight shipments, much of the existing literature on the geography of air transportation has paid more attention to passenger travel than air freight. The purpose of this paper is to elevate our understanding of air freight by determining which specific variables most influence and shape the geographic distribution of air freight by metropolitan area using stepwise regression analysis. The empirical results suggest a regression model of five independent variables was the most parsimonious solution where the final model accounted for 71.1% of the variation in air freight shipments by metropolitan area (MA). The most important predictor was the traffic shadow effect, where less populated MAs under the traffic shadow of larger MAs tended to generate lower levels of freight. The model also suggested that other key predictors included the employment market share in transportation-shipping-logistics industries, per capita personal income, the number of medical diagnostic and supplier establishments, and above average wages in high technology. Overall, metropolitan markets with diverse and efficient ground support systems, freight forwarders and other transportation services, a more affluent population, an intense agglomeration of medical laboratories and related suppliers, and a well paid skilled workforce engaged in computer systems design and electronic product manufacturing are more likely to ship freight by air.     

A conceptual business model framework applied to air transport

The adoption of business models in different sectors has been disseminated exponentially as a result of organizational strategies, allowing the identification and definition of paths to be followed, and enhancing capture and value creation for consumers and the enterprise. In the case of the air transport sector, specifically the airlines, the proposition of new business models can contribute to creating competitive advantage. This study develops a conceptual business model framework applied to air transport, which prioritizes key components identified in the literature for designing business models for airlines. With the exploration of different aspects of business models and the identification of the main models used by airlines, the results demonstrate the need for the adoption of new models in this sector.     

A multivariate neural forecasting modeling for air transport – Preprocessed by decomposition: A Brazilian application

An artificial neural forecasting model is developed for air transport passenger analysis. It uses a preprocessing method that decomposes information to reveal relevant features from the data. It is found that neural processing outperforms the traditional econometric approach and offers generalization on time series behavior, even where there are only small samples.     

The effects of deregulation, changed customer requirements and new technology on the organisation and spatial patterns of the air freight sector in Europe

Customer requirements, new technologies and the deregulation and liberalisation measures of the last 15 years have had a significant influence on market structures in air freight transport in Europe. The study examines the sector using the concept of global production networks. It describes the reorganisation in various dimensions. Firstly, there is the development from single air freight forwarders to global networks of firms. Secondly, we find a reorganisation of inter-company relations. Thirdly, airlines around the world organise their air traffic as a hub system. This lends added importance to the selected hub airport, and puts pressure on them to enlarge. As spatial consequences there is greater competition among international airports.     

An airline's management strategies in a competitive air transport market

Over the last decade, the demand for domestic and international flights in Korea has increased substantially. To meet the strong flight demands, several low cost carriers have begun to offer flight services. In addition, full service carriers have been motivated to establish their own subsidiary low cost carriers to maintain their market share against rival low cost carriers. This paper studies the management strategies of three kinds of airlines - full service carrier, its subsidiary low cost carrier and rival low cost carrier - based on game theory in the competitive air transport market. Each airline is assumed to act as a player and chooses strategies regarding airfare, flight frequency, and the number of operating aircrafts for specific routes while maximizing its own profits. Demand leakages between the airlines are considered in the flight demand function according to the selected strategies of all airlines. Through various game situations reflecting realistic features, this study provides managerial insights that can be applied in the competitive air transport market.     

CO2 emissions associated with hubbing activities in air transport: an international comparison

Hubbing is an important operational practice in air transport. Many studies have been conducted to examine the benefits and impacts of hubbing from an economic perspective. However, its impact on CO₂ emissions, especially across different air spaces, is not well understood. This paper explores the impact of hubbing activities in air transport from an environmental perspective. With a detailed methodology and data from the Greek and Hong Kong/Sanya flight information regions (FIRs), three levels of CO₂ emissions are estimated: airport-based, airspace-based and flight-based. After contrasting the CO₂ emission efficiencies of Athens International Airport (AIA) and the Hong Kong International Airport (HKIA), aircraft type and flight distance are examined to explain their emission efficiency differences. It is found that HKIA is associated with poorer CO₂ emission efficiency at the airport and airspace levels because of the larger aircraft and longer flight distance. However, when CO₂ emission efficiency at the flight level is considered, HKIA, with a higher passenger load factor, performs better. Major international hub airports should implement additional environmental measures to minimize the impact of hubbing activities on CO₂ emissions at the airport and airspace levels.     

Investigations on the distribution of air transport traffic and CO2 emissions within the European Union

This study analyses the structure of air traffic and its distribution among the different countries in the European Union, as well as traffic with an origin or destination in non-EU countries. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The segmentation of air traffic in terms of distance permits an assessment of air transport competition with surface transport modes.The results show a clear concentration of traffic in the five larger countries (France, Germany, Italy, Spain and UK), in terms of RPKs. In terms of distance the segment between 500 and 1000 km in the EU, has more flights, passengers, RTKs and CO₂ emissions than larger distances. On the environmental side, the distribution of CO₂ emissions within the EU Member States is presented, together with fuel efficiency parameters. In general, a direct relationship between RPKs and CO₂ emissions is observed for all countries and all distance bands. Consideration is given to the uptake of alternative fuels. Segmenting CO₂ emissions per distance band and aircraft type reveals which flights contribute the most the overall EU CO₂ emissions. Finally, projections for future CO₂ emissions are estimated, according to three different air traffic growth and biofuel introduction scenarios.     

Increasing the resilience of air traffic networks using a network graph theory approach

Air traffic networks are essential to today’s global society. They are the fastest means of transporting physical goods and people and are a major contributor to the globalisation of the world’s economy. This increasing reliance requires these networks to have high resilience; however, previous events show that they can be susceptible to natural hazards. We assess two strategies to improve the resilience of air traffic networks and show an adaptive reconfiguration strategy is superior to a permanent re-routing solution. We find that, if traffic networks have fixed air routes, the geographical location of airports leaves them vulnerable to spatial hazard.     

Differential pricing strategies of air freight transport carriers in the spot market

The single pricing approach fails to reflect different demand changes in response to its cargo space prices at different sales periods. This might be an obstacle to maximize the cargo space revenue of air freight carriers. This paper conducts the empirical analysis on pricing strategies in the spot market for two competitive air freight transport carriers operating on the same segment. It concludes that two carriers gain more revenues with the optimized differential pricing approach than with the single pricing approach. In theory, the research enriches the current literature in terms of pricing strategy optimization under the competition of two parties. In practice, it provides references for air freight transport carriers in their decision-making of applying the differential pricing strategy.     

Forecasting temporal world recovery in air transport markets in the presence of large economic shocks: The case of COVID-19

This paper estimates the relationship between the strength of economic shocks and temporal recovery in the world air transport industry. Our results show that world recovery of passenger demand to pre-COVID-19 levels is estimated to take 2.4 years (recovery by late-2022), with the most optimistic estimate being 2 years (recovery by mid-2022), and the most pessimistic estimate 6 years (recovery in 2026). Large regional differences are detected, Asia Pacific has the shortest estimated average recovery time 2.2 years, followed by North America 2.5 years and Europe 2.7 years. For air freight the results show a shorter average world recovery time of 2.2 years compared to passenger demand. At the regional level, Europe and Asia Pacific are comparable with average recovery times of 2.2 years while North America is predicted to recover faster in 1.5 years. The results show that the strength of economic shocks of various origins impacts the linear growth of passenger and freight traffic and the temporal recovery of the industry in a predictable transitory way. Hence, the impact of the COVID-19 recession will represent a temporary, although long-lasting, correction to previous growth levels.     

Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach

This paper uses a complex network approach to examine the network structure and nodal centrality of individual cities in the air transport network of China (ATNC). Measures for overall network structure include degree distribution, average path length and clustering coefficient. Centrality metrics for individual cities are degree, closeness and betweenness, representing a node’s location advantage as being directly connected to others, being accessible to others, and being the intermediary between others, respectively. Results indicate that the ATNC has a cumulative degree distribution captured by an exponential function, and displays some small-world (SW) network properties with an average path length of 2.23 and a clustering coefficient of 0.69. All three centrality indices are highly correlated with socio-economic indicators of cities such as air passenger volume, population, and gross regional domestic product (GRDP). This confirms that centrality captures a crucial aspect of location advantage in the ATNC and has important implications in shaping the spatial pattern of economic activities. Most small and low-degree airports are directly connected to the largest cities with the best centrality and bypass their regional centers, and therefore sub-networks in the ATNC are less developed except for Kunming in the southwest and Urumchi in the northwest because of their strategic locations for geographic and political reasons. The ANTC is relatively young, and not as efficient and well-developed as that of the US.     

How did COVID-19 impact air transportation? A first peek through the lens of complex networks

The current outbreak of COVID-19 is an unprecedented event in air transportation. This is probably the first time that global aviation contributed to the planet-wide spread of a pandemic, with casualties in over two hundred countries. As of August 23rd, 2020, the number of infected cases has topped 23 million, reportedly relating to more than 800,000 deaths worldwide. However, there is also a second side of the pandemic: it has led to an unmatched singularity in the global air transportation system. In what could be considered a highly uncoordinated, almost chaotic manner, countries have closed their borders, and people are reluctant/unable to travel due to country-specific lock-down measures. Accordingly, aviation is one of the industries that has been suffering most due to the consequences of the pandemic outbreak, despite probably being one of its largest initial drivers. In this study, we investigate the impact of COVID-19 on global air transportation at different scales, ranging from worldwide airport networks where airports are nodes and links between airports exist when direct flights exist, to international country networks where countries are contracted as nodes, and to domestic airport networks for representative countries/regions. We focus on the spatial-temporal evolutionary dynamics of COVID-19 in air transportation networks. Our study provides a comprehensive empirical analysis on the impact of the COVID-19 pandemic on aviation from a complex system perspective using network science tools.     

A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting

Air transport demand forecasting is receiving increasing attention, especially because of intrinsic difficulties and practical applications. Total passengers are used as a proxy for air transport demand. However, the air passenger time series usually has a complex behavior due to their irregularity, high volatility and seasonality. This paper proposes a new hybrid approach, combining singular spectrum analysis (SSA), adaptive-network-based fuzzy inference system (ANFIS) and improved particle swarm optimization (IPSO), for short-term air passenger traffic prediction. The SSA is used for identifying and extracting the trend and seasonality of air transport demand and the artificial intelligence technologies, including ANFIS and IPSO, are utilized to deal with the irregularity and volatility of the demand. The HK air passenger data are collected to establish and validate the forecasting model. Empirical results clearly points to the enormous potential that the proposed approach possesses in air transport demand forecasting and can be considered as a viable alternative.     

Mode choice behavior analysis of air transport on the introduction of remotely piloted passenger aircraft

Remotely piloted aircraft (RPA) are expected to be applied to passenger aircraft; however there is a lack of research which analyzes choice behavior for RPA compared to conventionally piloted aircraft (CPA), in terms of socio-demographic characteristics. The purpose of this paper is to present a model for air travelers’ mode choice behaviors under the assumption that RPAs are introduced to the market. Results show that the fare of RPA should be lowered by a certain amount (i.e., discount factor of RPA) to compete with CPA, and the discount factor should be higher for older, female, and frequent travelers. The results also show that there are still concerns about RPA, and pilot on board is preferred. Through this study, it will be possible to predict the acceptance of newly introduced technology in consideration of socio-demographic characteristics of potential customers.     

The competitive landscape of air transport in Europe

Competition between airlines and airports increased significantly since the deregulation of the intra-European air transport market in 1997. The passenger has a wider choice in terms of routings and departure airports than twenty-five years ago and pays a lower price. In this paper we investigate in which parts of Europe airline and airport competition are most intense and how the competitive landscape has changed since the liberalisation of the intra-European market.Competition levels are modelled for all air transport markets available to consumers in each western-European municipality using a Multinomial Logit (MNL) model. This allows us to determine how competitive the air transport product available to consumers in each of those municipalities truly is and how competition levels have changed. As opposed to most other competition studies we take all viable direct and indirect flight alternatives into account, as well as competing alternatives from nearby (adjacent) airports. This makes it the most extensive analysis of competition in the European aviation industry performed to date.As expected the results show that airline competition, allowing for grouping of the airlines belonging to the same alliance together, has in general increased since the liberalisation of the intra-European market. This can mainly be ascribed to the rise of the low cost business model. The spatial analysis however shows an uneven outcome. Changes in airline competition are most pronounced in areas that were previously not well served, such as the more remote regions in the United Kingdom, Spain and Italy. In Germany airline competition is lagging behind due to the strong dominance of the STAR alliance. In large parts of Scandinavia, but also in parts of France and Spain, airline competition is considerably less. These areas are often served only by a handful of airports and/or airlines, limiting airline choice and therefore competition.