Air travel for private purposes. An analysis of airport access,income and environmental concern in Switzerland

As air travel is considered a relevant area of action to mitigate climate change, it is important to know its determinants. The present study examines socio-demographic, spatial and attitudinal predictors of air travel for private purposes. The analyses are based on the Swiss Environmental Survey 2007 and a subsequent computation of the respondents' environmental impact, as well as spatial data.A lognormal hurdle model indicates that persons with higher environmental concern are less likely to travel by air and if they still do, they travel less. While political orientations do not affect whether a person travels by air, the results indicate that among those who do fly, respondents voting for the Green Party cause lower emissions than those opting for other left or center parties. Furthermore, higher incomes are associated with more air travel whereas living with children is associated with less air travel. Airport access is related to air travel in the sense that living closer to airports, in particular to large ones, is correlated to more air travel. The result is robust to alterations of the accessibility measure and also upholds when population density is controlled for.     

Using analytic network process to measure the determinants of low cost carriers purchase intentions: A comparison of potential and current customers

The goal of this study is to use the analytic network process (ANP) approach to develop an evaluation model which prioritized the relative weights of determinants of low cost carriers (LCCs) purchase intentions between potential and current customers. A field study with 96 potential customers and 84 current customers of LCCs was performed. The results found some similarities and differences between potential and current customers with regard to the determinants of LCCs purchase intentions. With respect to the final weights of these determinants, both customer groups considered “reliability and image” to be the important factor that affects their intentions to purchase LCCs. Additionally, “price and convenience” received a higher weighting by potential customers, while current customers emphasized the importance of “employee services”. The evaluation model and the results obtained using it provide a valuable reference for LCC managers who are seeking to facilitate effective customer relationship management.     

Spatio-temporal fluctuations in the global airport hierarchies

The global air transportation network is responsible for moving millions of domestic and international passengers each year. Not surprisingly, relationships between airports vary widely, due to a myriad of geographic, economic, political and historical determinants. Further, given the dynamic nature of the many influences acting on the air transportation system, inter-airport relationships and the structure of the global air network as a whole are also constantly changing. The purpose of this paper is to explore such spatio-temporal variations in the structure of the global airport hierarchies. Here, we show how the concept of nodal regions can be applied to measure the extent of these variations. To facilitate this analysis, a database of nearly 900 airline carrier schedules and 4650 worldwide origins and destinations, representing a nearly complete record of commercial air travel over a six-year period, is examined. Given this dataset, nodal regions are derived for all airports represented. In general, results suggest that regions associated with individual airports are often relatively dynamic at the yearly as well as quarterly level. Los Angeles International Airport (LAX) is utilized as a local case-study to provide a detailed examination of these dynamics.     

Evolution trends of the network structure of Spring Airlines in China: A temporal and spatial analysis

Both the sustainable development of China's economy and the deregulation of the China air transport market have acted as a spur for the halting development of low-cost carriers (LCCs) in China. To analyze the development trends of LCCs' network in China, this paper took Spring Airlines, the only LCC in China as an example. First, the winter flight plans of Spring Airlines from 2005 to 2013 were collected. Secondly, the development trends of air transport network of Spring Airlines were explored with methods of mathematical statistics and social network analysis. Additionally, the development trends were analyzed from the levels of navigable cities, air routes and air transport networks. The results show that although Spring Airlines actively launched air routes between tourist cities with non-class I airports, its network has been transformed from a star structure into a complex one with multi-hubs. The development process of the Spring Airlines network can be separated into three stages. In addition, the problems and evolution trends of its network are discussed further.     

The impact of progressive liberalization on the spatiality of airline networks: a measurement framework based on the assessment of hierarchical differentiation

There seems to be a renewed trade-off between processes of concentration and dispersal in airline networks. This development calls for a framework that allows for a systematic assessment of the overall evolution of the spatiality of airline networks. To this end, we develop an analytical framework based on a set of spatial interaction indices, which allows measuring the degree of hierarchical differentiation (i.e. dominance and connectivity) in a network. Moreover, a normalization of these indices through a systematic comparison with the corresponding values for a rank size distribution makes it possible to engage in meaningful longitudinal analyses and/or to compare the spatiality of networks with different numbers of nodes and/or links. Our framework is tested by applying it to data on air passenger flows within Europe, and its usefulness is discussed in the context of research on air traffic liberalization.     

Is spatial dispersal the dominant trend in air transport development? A global analysis for 2006–2015

The economic performance of a city or region is considered to be intertwined with its air travel capability. It is thus important for planners and stakeholders to understand the changes in the global aviation network. This study investigates the global aviation network, taking 10 years worth's OAG data from the years 2006–2015 and examines whether a spatial dispersal trend dominates the development of the aviation industry. It considers the aviation network at the airport level, and the airport–city level, which may consist of one or more airports. After clarification of the various definitions of concentration, we find that there appears a trend toward a dispersal pattern in the global aviation network at the airport level. On the other hand, there appears a slight concentration at the airport–city level. Besides, there have been some major capacity expansions at airports in the Middle East and East Asia, while the capacities of some traditional hubs in Europe and North America have become increasingly constrained since the 2008 global financial crisis. Furthermore, our study provides further observations consistent with the phenomenon of bypassing of traditional hubs, especially mega-hubs. Competition for passengers among hubs and secondary airports, especially in multi-airport cities, is discussed.     

Evolution of air transport network of China 1930–2012

This paper analyzes the evolution process of the air transport network of China (ATNC) since 1930. Based on the network analysis results, the ATNC has significantly improved in connectivity based on (1) rising alpha, beta and gamma indices, (2) declining diameter and centre index and (3) decreasing average path length and increasing clustering coefficient. The network centralization index reveals a fluctuation phase before 1952, a pre-1980 centralization phase before the economic reform era, a centralization phase after the mid-1990s deregulation, and a decentralization phase between. The k-core decomposition method helps identify the evolution of core network and hierarchy of the ATNC over time. The spatial development model characterizes its structure change in six stages: (1) scattered development, (2) trunk line connection, (3) circular linkage, (4) hub formation, (5) a complex network structure, and (6) emerging multi-airport systems.     

Spatial structure and network behaviour of strategic airline groups: A comparison between Europe and the United States

The Gini-index has gained in legitimacy when measuring traffic distributions of air traffic as compared to other more established measures, such as Herfindahl's. In order to render the index more meaningful for policy-makers, a partial decomposition into strategic groups of airlines along distinct geopolitical scopes of air traffic is suggested. Air traffic across airports is considered an aggregate of complex networks that are subject to multiple constraints, such as geopolitics or technology. A multi-layered analytic approach accounts for network operators as economic agents that behave in strategic ways within these constraints. Our approach allows for comparing traffic distributions in Europe with that of the US and, in particular, introduces a normative component by isolating patterns in airlines’ strategies that are likely to induce different degrees of spatial concentration and balanced traffic distributions within these common markets.     

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.     

Introduction to the special issue: Air transport in the Global South

Research on the development and impacts of air transport has hitherto focused mainly on developed countries in the Global North, and relatively little on less developed countries in the Global South. The seven papers of this Special Issue of the Journal of Transport Geography aim to address this imbalance and encourage further research on air transport development in the Global South. In recent years, the Global South has witnessed significant changes in air transport networks and policies, with implications for economic growth, spatial development and airline business models. This Special Issue explores some challenges to air transport development in the Global South for countries in Africa, South America, the Middle East and Asia, including links between air transport and economic development, the evolution and key drivers of air transport growth and the spatial distribution of passenger airline networks, and the development and impact of low-cost carriers. It also identifies opportunities for future research in this growing area.     

Simulation analysis of factors affecting air route connection in China

In order to explore the impacts of various factors on air route connection, a probability model is constructed to simulate the Chinese airline network (CAN) in 2010, and the influences of tertiary industry output, degree and the spatial distance between two navigable cities on the analog results are discussed. Our research shows that, the opening of an air route is not completely determined by the potential air passenger flow of it, although the latter is playing a leading role. In addition, the connection probability of an air route is significantly affected by the tertiary industry outputs and degrees of corresponding two navigable cities, but little influenced by the spatial distance between them. Moreover, scale economies effect obtained from the increasing of degree is apparently greater than that brought by the developing of social economy, so CAN is more inclined to evolve into a hub-and-spoke network.     

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.     

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.     

Network concentration and airport congestion in a post de-regulation context: A case study of Brazil 2000–2010

This paper empirically investigates the main drivers of airline network concentration in an air transport market subject to rapid growth. We consider the Brazilian air transport industry of the 2000s, in which network concentration rapidly increased and was followed by a period of massive flight delays and cancelations, which resulted in the “big blackout” of 2006–2007. We develop an econometric model of network concentration, accounting for demand, cost and competition variables that may affect the propensity of carriers to concentrate flights and passenger connections on a few airports of a network. The main focus of the paper is on the relation between networks leading to the problems of the blackout episode. We investigate the dynamic pattern of the evolution of concentration before and after the abnormal period of operations and find that concentration began to rise at least six quarters before, and persisted at a high level until two quarters after the blackout – and then plunged steeply toward the end of the decade. We believe that our analysis contributes to an improved understanding of the behavior of air transport systems subject to network concentration and congestion. With respect to methodology, we suggest and employ the use of alternative measures of network concentration to check the robustness and validity of our results.     

Examining the spatial–temporal dynamics of bus passenger travel behaviour using smart card data and the flow-comap

Over the past two decades, smart card data have received increasing interest from transport researchers as a new source of data for travel behaviour investigation. Collected by smart card systems, smart card data surpass traditional travel survey data in providing more comprehensive spatial–temporal information about urban public transport-based (UPT) trips. However, the utility of smart card data has arguably yet to be exploited fully in terms of extracting and exploring the spatial–temporal dynamics of UPT passenger travel behaviour. To advance previous work in this area, this paper demonstrates a multi-step methodology in order to render more insightful spatial–temporal patterns of UPT passenger travel behaviour. Drawing on the Brisbane, Australia, bus network as the case study, a smart card dataset was first processed in combination with General Transit Specification Feed (GTFS) data to reconstruct travel trajectories of bus passengers at bus stop level of spatial granularity. By applying geographical information system-based (GIS) techniques, this dataset was used to create flow-comaps to visualise the aggregate flow patterns at a network level. The flow-comaps uncovered the major pathways of bus passengers and its variations over a one-day period. The differences within the flow-comaps were also quantified to produce weighted flow-comaps that highlighted the major temporal changes of passenger flow patterns along a number of stop-to-stop linkages of the bus network. The proposed methodology visually unveiled the spatial–temporal travel behaviour dynamics of UPT passengers and, in doing so, showed the potential to contribute to a new evidence base with the capacity to inform local public transport policy.     

An analysis of European low-cost airlines and their networks

The growth of low-cost carriers (LCCs) is currently focused on the Western European market, where they represent the most determining factor in the evolution of airline networks. In this area, they stand for 18% of the total air transport supply according to seats. Limited to short and medium haul flights, networks are not too concentrated (no hubs). They are North–South, and compete with—when they have not replaced—some charter routes. The use of air freedoms beyond the fourth is still limited, but exclusive routes are a frequent phenomenon linked to the option for secondary (urban or regional) airports and/or niches.Finally, low-cost carriers give fresh impetus to point-to-point routes by drawing new networks complementing those of full service network carriers (FSNCs). If no hubs as such can be found in these new networks, significant concentrations characterize the major bases.The geography of low-cost networks is to a large extent the geography of EU air transport liberalization.     

The underlying drivers and future development of air cargo

Air cargo plays a crucial role in the air transport chain and in the globalized economy. As for other modes of transport, the demand for air cargo is a derived demand. Previous studies showed that the main determinants of air cargo demand are merchandise trade and the share of manufactures in merchandise trade. This paper aims to fill a gap in the existing literature by additionally taking the influence of air freight yields and oil prices into account when modelling the global air cargo development. Furthermore, it provides an insight into the future development of air cargo. Forecasts until 2023 are made based on a number of scenarios for the main determinants of air cargo demand. Moreover, an insight is provided into the current air cargo market, including traffic levels and different types of actors and traffic flows. The results are useful not only for academics but also for industry stakeholders for which air cargo is an important contributor to profit and/or cash levels.     

Comparing spatial concentration and assessing relative market structure in air traffic

Traffic distributions of air traffic and their concentration have been measured through Gini, an index that contrasts in many ways with other more established ones, such as Herfindahl's. This research is extended in the sense that it perceives spatial concentration in air transport as an aggregate of complex networks that are subject to multiple constraints, such as geopolitics or technology. We propose a multi-layered analytic approach where network operators are economic agents that behave in strategic ways. It allows for comparing air traffic between airports in Europe with that of the US and, in particular, introduces a normative component by isolating patterns in airlines' strategies that coincide with more or less welfare-oriented degrees of spatial concentration in light of the above constraints.     

The determinants of air passenger traffic at Turkish airports

Investigating the determinants of air passenger traffic has become commonplace. In contrast with most previous publications, this paper investigates these determinants in an emerging country, Turkey, at the provincial level between 2004 and 2014. We find that GDP/capita, population, distance to alternative airports, tourism, leading cities, and international migrations all support more air traffic. Furthermore, market concentration is associated with less traffic, and the presence of academics with more traffic. Mapping models' residuals suggest catchment areas, surface transport options, domestic migrations and (geo)politics could also matter. Accordingly, it appears the determinants of Turkey's air passenger traffic do not differ from those of developed economies. The results also suggest new airports should be built based on the aforementioned factors.