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.     

The opening of direct flights across the Taiwan Strait: the impact on the global role of Taiwan’s international airport

Scheduled direct flights between Taiwan and Mainland China were halted for six decades and restarted in December 2008. The Taiwan’s government has a policy of developing Taoyuan International Airport (TPE), the major international airport in Taiwan, as one of main hubs in East Asia, based on the airport’s access to Mainland China. To assess whether the airport is progressing toward meeting the set expectation, this study evaluates the changes in airline networks of the TPE after the opening of direct flights across the Taiwan Strait. The time-dependent earliest arrival time algorithm is applied to global flights in 2004, 2008, and 2012. Empirical evidence demonstrates that providing direct flights across the Taiwan Strait has significantly increased accessibility from TPE to airports in China, but did not improve the centrality of TPE. Additionally, the transfer dependency of TPE on other airports is increasing significantly. This result was based on two major reasons: the first involves the Chinese government’s refusal to allow Chinese citizens to use airports in Taiwan as transfer points to and from other countries and the second reflects the competitiveness among airports and airlines in the region. The key finding is that political exclusion of airline use by external governments via travel regulations adversely influences the development of an airport as a global hub.     

Characterization of delay propagation in the air traffic network

We build a delay propagation network based on Bayesian Network approach to study the complex phenomenon of delay propagation within a large network consisting of the 100 busiest airports in the United States. Through topological analysis and probability analysis, we investigate the characterization of delay propagation among airports and the impact of different types of airports on delay propagation. Results indicate that the cumulative degree distribution of the delay propagation network follows an exponential function and flight delays take at most one transhipment to go from each airport to any other airports on average. For each individual airport, the effects of delay propagation are associated with airports size (traffic flow), small airports are easily affected by other airports while large airports are more affecting downstream airports but fewer affected by upstream airports. Finally, we show how the number of affected airports changes as a function of the delayed airports based on different simulation strategies.     

Cargo market competition among Asia Pacific's major airports

Globalization and the ensuing changes in the supply chain network have strengthened competition among airports. For this study, we selected 13 primary airports in Asia Pacific, and investigated their competition, airport hierarchy, and competitive potential in cargo markets in terms of demand and supply. Specifically, we examined indicators including flight frequency, route distributions, composition of flag carriers, international trade, and centrality of the selected airports. The results revealed that Taiwan Taoyuan International Airport (TPE), Hong Kong International Airport (HKG), Shanghai Pudong International Airport (PVG), and Incheon International Airport (ICN) had the greatest competitive advantage of distinct developmental patterns. Compared with TPE and ICN, which are national-carrier-oriented airports, HKG and PVG have been developed efficiently in the network of both national and foreign carriers. Although TPE and ICN perform well in the networks of conventional carriers, PVG is competitive in the network of all-freight carriers, and HKG performs efficiently in both the networks of the conventional and all-freight carriers. Overall, Hong Kong International Airport has been prominent in the Asia–Pacific air-cargo market. Nevertheless, considering the networks of the integrator carriers, Chinese airports have the most potential in this region.     

What is the busiest time at an airport? Clustering U.S. hub airports based on passenger movements

Accurate clustering of airports enables airport authorities and operators to precisely position themselves in the competitive market, facilitates airlines to efficiently allocate resources, and empowers the research community with credible data for new discoveries. Existing clustering studies largely use traffic volume, network connectivity, or operational efficiency to group airports into hierarchical clusters or parallel partitions. Developing a different perspective, this study focuses upon a key bottleneck of outbound passenger movements in airport terminals, the security checkpoints, and uses the Transportation Security Administration (TSA) Customer Throughput/Wait Times Reports to cluster hub airports of the United States. With the input data structured as univariate time-series, k-shape, a clustering algorithm that is robust to time axis distortion and computationally efficient, is selected to analyze the similarity of time-series using shape-based distance. The clustering results are validated by examining the raw and z-normalized data of selected airport clusters on six sampled dates. Analysis results indicate that k-shape is competent and efficient to process and cluster time-series data used for this specific research. This study offers a fresh perspective to cluster commercial airports using an infrequently employed dataset. The clustering results reveal how the geographical location, hub status in airlines' operational network, and destination type of an airport affect the movement of outbound passengers through terminals     

Towards an objective decision-making framework for regional airport site selection

Airport site selection requires consideration of several criteria constrained by complicated trade-offs. Airport literature and practice provide valuable insights in terms of influencing factors and multicriteria assessment methods, at the pace that reported siting processes follow non uniform decision-making structures. Current developments in geoinformation unveil a valuable opportunity of development of a structured methodology in the field of airport siting. Brazilian public sector decision-makers recognize that such methodology has the potential to improve the allocation of federal budget for new regional airports, in terms of implementation time and political friction. This research proposes a methodology termed MESA - Metodologia de Escolha de Sítios Aeroportuários (in Portuguese, Airport Site Selection Methodology). The purpose of MESA is to be sound under technical grounds and at the same time provide a more objective decision-making process. The proposed methodology consists of 4 phases: i) literature review of airport site selection criteria; ii) criteria systematization; iii) setting up of eliminatory criteria and their thresholds; and iv) setting up of scoring criteria and of an approach for their quantification. Eliminatory criteria reduce the original screening area, while scoring criteria are used for ranking purposes. MESA combines GIS (Geographic Information System) and classic AHP (Analytic Hierarchy Process) with direct assessment of alternatives through specific techniques. So far, the methodology has been applied to two real cases in the Brazilian context. In addition to effectively reducing subjectivity in airport site location decision, MESA has been demonstrating to be a powerful tool for mitigating environmental and social impacts associated to airport site selection. MESA is designed in such a way that simplifies improvements and adaptations, making it widely applicable.     

Spatial and operational factors behind passenger yield of U.S. nonhub primary airports

Nonhub airports are an essential component in the National Plan of Integrated Airport Systems (NPIAS) of the United States in that they connect regional towns and small communities to the air transportation network. Understanding the interplay of operational and spatial factors in determining average passenger yield of nonhub airports provides airlines with valuable information for network planning and revenue management. This study examines factors contributing to the yield variation among nonhub airports in the U.S. Using ordinary least squares (OLS) based econometric models, this study captures the spatial dependence of passenger yield of nonhub airports, which tends to increase with a corresponding increase in distance to the nearest large hub airport. Nonhub airports surrounding large hub airports with higher passenger enplanements and higher average yields also have higher yields than other nonhub airports. In addition, this study finds the effect of Allegiant Airlines in lowering the average passenger yield of the nonhub airports served directly by the airline, which can be termed as ‘Allegiant Effect’. Findings of this study could provide valuable guidance for airlines to analyze network planning strategies and to identify future markets for growth and for policymakers when allocating resources to communities relying on these nonhub airports.     

The role of London airports in providing connectivity for the UK: regional dependence on foreign hubs

In a context of ongoing debate about the future UK aviation policy and its implications for regional economic development, this paper discusses the role of London Heathrow and the South East airports in providing connectivity for the UK, with particular focus on the international markets that originate from regional UK airports. Using an MIDT dataset of worldwide passenger itineraries served by the European airport network during May 2013, we first establish whether London Heathrow can currently be considered the most important hub for the UK, in terms of traffic generation, connectivity, and centrality, while also measuring the dependence of UK regions on foreign airports and airlines to remain connected with the rest of the world. Results show that, despite the competition, London Heathrow benefits from its massive traffic generation to remain the most central gateway for overall UK air transport markets. However, when only regional markets are considered, significant dependence on foreign hubs appears in many destinations, particularly to Asia–Pacific or the BRIC countries where above 80% of passengers use transfer flights. These results fit nicely with the observed trends of seat de-concentration and hub-bypassing in the airline industry. While dependence on foreign hubs can be interpreted as a sign of vulnerability, there is also the argument that bypassing Heathrow allows regional airports to develop new markets and reduce the level of congestion in the London airport system.     

An analysis for the competitive strength of Asian major airports

This paper presents an analysis of the competitive status of major airports in the East Asia region. The analysis assesses these airports based on five factors: service, demand, managerial, facility, and spatial qualities. In order to analyze the competitive status of the selected airports, this study has applied a multi-decision criteria approach and is based on a comparison of qualitative data. The competitive status of each airport can be categorized as one of the following levels: most, more, less, or least competitive.     

Airports in their urban settings: towards a conceptual model of interfaces in the Australian context

In Australia, airports have emerged as important sub-regional activity centres and now pose challenges for both airport operation and planning in the surrounding urban and regional environment. The changing nature of airports in their metropolitan context and the emergence of new pressures and problems require the introduction of a fresh conceptual framework to assist the better understanding of these complex roles and spatial interactions. The approach draws upon the meta-concept of interfaces of an ‘airport metropolis’ as an organising device consisting of four main domains: economic development, land use, infrastructure, and governance. The paper uses the framework to further discuss airport and regional interactions and highlights the use of sustainability criteria to operationalise the model. The approach aims to move research and practice beyond the traditionally compartmentalised analysis of airport issues and policy-making by highlighting interdependencies between airports and regions.     

Hub competition and travel times in the world-wide airport network

The aim of this work is to measure the competition between airport hubs based on an analysis of travel times in the world-wide airport network. By considering the minimum travel time required to connect each pair of airports, it is possible to create new measures of hub competition, separating the effects of hub position and temporal coordination. This analysis was carried out at the global level, considering all 232 airports with more than 3 million seats yearly offered in departure flights in 2008, and also in relevant geographic markets. The results show a high level of competition among the most important world airports, but the major airports of Europe have a geographical advantage in relation to world markets over the major American and Asian airports. We also show that airports located in different continents often compete for the same origin–destination markets. Geographical position appears to be the most important variable explaining hub performance. Secondary hubs show a higher degree of specialization towards specific markets.     

An integrated performance evaluation approach for the Indian international airports

This paper deals with the applications of best worst method (BWM) and multi-attributive border approximation area comparison (MABAC) method to assess the performance of 32 major Indian international airports based on eight evaluation criteria. The BWM is applied to derive the criteria weights based on the opinions of four decision makers, while MABAC method is employed to rank the considered airports from the best to the worst along with the identification of their relative strengths and weaknesses. The advantages of these methodologies are also enumerated. It is observed that annual revenue is the most important evaluation criterion, followed by the total number of passengers. Based on this integrated analysis, Indira Gandhi International Airport and Surat International Airport respectively emerge out as the best and the worst performing international airports in India.     

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.     

Cascading failures in airport networks

Cascading failure phenomena can appear in complex networks that distribute flows of information, people or goods, when flow going through nodes or edges exceeds the capacity of network nodes or edges. Cascading failure models from previous research are not adequate for airport networks, as flow is not continuous, and load has to be redistributed among close airports, rather than previously existing connections. With these constraints in mind, we have defined an algorithm to simulate the management of cascading failures in airport networks. We use the algorithm to evaluate the effectiveness of several selection rules of alternative departure and arrival airports to affected flights to reduce the impact of the cascading failure. We have applied the algorithm to the Oceanic Airport Network to assess the impact of several incidents. Results show that selection rules of arriving airports have significant impact in reducing the effect of incidents affecting central airports.     

Airport selection criteria of low-cost carriers: A fuzzy analytical hierarchy process

The selection of airport is an important consideration for low-cost carriers (LCCs) to remain cost competitive. The objective of this study is to identify and rank the airport selection criteria of LCCs. Based on reviewing the existing literature, five main factors comprising 16 sub-factors were developed. The factors were first validated by three industry experts from the aviation industry. Thereafter, a survey questionnaire requiring a comparison of the factors was administered on 28 executives who were involved in the strategy planning and formulation of LCCs based in China or Korea. The collected data were analysed using fuzzy analytical hierarchy process (FAHP). In descending order of their importance, the main factors influencing LCCs' selection of airport are (1) airport charges, (2) airport performance, (3) airport growth opportunities, (4) catchment area and (5) airport infrastructure. The top three sub-factors are airport costs, demand for LCC services and passenger throughput. The research contributes to academic research by providing a holistic assessment of the key considerations influencing LCCs' selection of airport. In addition, it implicates policy formulation of LCCs by providing a framework for assessment of airports that are suitable for LCCs’ operations.     

Health screening strategies for international air travelers during an epidemic or pandemic

Air travelers can carry an infectious disease's pathogenic microorganism in their bodies and spread the disease from one country to another in a few days. To delay the spread, health screening stations may be set up at airport terminals to screen travelers. This research tested three different health screening strategies, each with a different combination of screening stations at trip origins, destinations and connecting airports. Discrete event simulations were performed, based on the 2014 to 2016 Ebola virus epidemic, with special focus on travelers from the West African countries traveling to the United States, including travelers who transferred flights at airports in European Union member states. The effectiveness of the screening strategies was analyzed in terms of correct detection, missed detection and false alarm rate. The results showed that exit screening at trip origins brought big improvements in the performance measurements compared to no screening. However, additional screening at the destinations and connecting airports contributed marginal benefits.     

Analysis of the Chinese Airline Network as multi-layer networks

This paper encapsulates the Chinese Airline Network (CAN) into multi-layer infrastructures via the “k-core decomposition” method. The network is divided into three layers: Core layer, containing airports of provincial capital cities, is densely connected and sustains most flight flow; Bridge layer, consisting of airports in Tier 2 and Tier 3 cities, mainly connects two other layers; and Periphery layer, comprising airports of remote areas, sustains little flight flow. Moreover, it is unveiled that CAN stays the most robust when low-degree nodes or high flight flow links are removed, which is similar to the Worldwide Airline Network (WAN), albeit less redundant.     

Impacts of high-speed rail lines on the city network in China

China's large-scale HSR network has a significant influence on both accessibility and connectivity, but little attention has been paid to its impacts on connectivity. Changes in connectivity largely affect the external relations among cities, thus influencing the structure of the city network. This paper examines the impacts of China's HSR network on the overall connectivity and nodal centrality of the city network, as evaluated by passenger trains from 2003 to 2014. This paper employs the graph index, average path length, clustering coefficient and three indicators of centrality, namely weighted degree centrality (WDC), weighted closeness centrality (WCC) and weighted betweenness centrality (WBC). The results show that the HSR network largely increased overall connectivity according to the increasing Beta index and clustering coefficient, and decreasing average path length. The HSR lines also increased the average centrality of the city network and the inequality of nodal centrality according to the WCC indicator, but they decreased the inequality of nodal centrality with regard to the WDC and WBC indicators. Meanwhile, the growing HSR network led to the centrality tended to intensify in large cities in terms of the WCC indicator, but intensify in small cities according to the WDC and WBC indicators. Spatially, the cities with HSR stations, population over 3 million and GDP over 100 billion RMB saw higher increases in centrality than the others; the cities with high values of WDC and WCC, especially the top 20 cities, tended to concentrate in the populous areas with well-developed economies (e.g., Yangtze River Delta), whereas the cities with high WBC values in 2014 were coupled with the hub cities of regional railway management administration.     

A Multi-Objective Goal Programming airport selection model for low-cost carriers’ networks

This paper examines the practicability and validity of the Multi-Objective Goal Programming (MOGP) model in designing a point-to-point airline network. The MOGP mathematical model is used in this study to identify and select a best central airport and its connecting airports providing the best overall optimal performance. By using the proposed model in the selection process, one can expect to achieve the following objectives: (1) an airline network designed at less cost, (2) an airline network that generates more revenues, and (3) an airline network that serves more passengers. Route data from Taipei to the Southeast Asian region were selected for this experiment to validate the model’s practicability.     

RISK assessment in airport maintenance runway condition using MCDA-C

This paper proposed the initial development of a multicriteria methodology for a runway maintenance monitoring using risk perception at airports with the MCDA-C methodology. To support morphological structuring and semantic judgments eight specialists in airport maintenance and operations were interviewed and the model was built based in their perceptions and deep technical knowledge on the subject. We found that the 7 most representative criteria were able to deal with approximately 80% of the perceived risk by the experts, indicating that a considerable part of the resources of the Brazilian airport infrastructure operations could be being redirected towards a more rational application. Finally, we applied the method in a real scenario situation by analyzing real data from the 29 the busiest Brazilian airports. Data showed objectively that 18 airports presented scores that clearly indicated being in a favorable (safer) or unfavorable (risky) condition regarding the criteria analyzed, guiding where the state can spend the resources with the best benefit.