Airport Competition Research Articles

Freight forwarder satisfaction, airport customer loyalty, and competitiveness

The Middle East represents 18% of the world’s air cargo revenue, and the region’s air cargo revenues have been growing three times faster than worldwide air cargo, making the Dubai airport an appropriate and novel focus for the operations management study on air cargo. The study provides a synthesized measure of freight forwarder satisfaction and tests the measure in an empirical model. The data collected from a population of freight forwarders, identified through the National Association of Freight and Logistics (NAFL), who use the Dubai International Airport, the world’s busiest airport, yielded a sample of 187 respondents surveyed during the fourth quarter of 2019. The results of the study provide evidence that freight forwarder customer satisfaction is positively associated with airport competitiveness (performance) through a mediator—customer loyalty.

Multi-product airport competition and optimal airport charges

This paper examines the importance of commercial revenue on optimal airport charges in a Hotelling-type duopoly airports competition. Each airport offers multi-products to heterogeneous consumers (airlines and passengers) and sets commercial and landing charges and serves. The airport-airline bundle competes for leisure and business passengers. The setting of landing charges under different regulatory regimes is investigated. We demonstrate that in the leisure travel market, which ignores schedule delay cost, the optimal landing fee is invariant to the regulatory scheme, and concession revenue is determined by an airport’s home market size. In the business travel market, the optimal landing charge is smaller if concession revenue is included in setting the landing fee than if it is not included. In the former case, increasing passenger volume does not guarantee increases in airports’ aeronautical revenue, and a negative impact may exist if the weight of concession profit out of total profit is small.

Use mobile location data to infer airport catchment areas and calibrate Huff gravity model in the New York metropolitan area

Mobile location data have emerged as a pivotal asset for analyzing travelers' spatial behaviors and movement patterns. In the context of air travel, the data empower researchers to gain empirical insights into travelers' choices of airports. This study employs mobile location data to scrutinize the market shares and infer catchment areas of three primary hub airports within the New York Metropolitan Area. Our study, together with Teixeira and Derudder (2021), helps contribute to a better understanding of competitive airport dynamics in the New York Metropolitan Area. In addition, the mobile location data allow us to calibrate the two key components of the Huff Gravity Model, which is frequently used in existing studies focusing on airport competition and catchment areas in Multiple Airport Regions (MARs). Our investigation underscores that the application of the Huff Model should not follow a uniform approach across different scenarios. The dynamics of airport competition and ground access alternatives exhibit unique characteristics within each MAR. Furthermore, our study unveils inherent quality challenges associated with mobile location data. Future studies intending to incorporate mobile location data are advised to conduct preliminary assessments of data quality before embarking on empirical analyses.

Cross-subsidization and U.S. airports

Airports serve as a two-sided market where aeronautical and non-aeronautical operations are complementary. This interdependence means that an increase in aeronautical operations output results in a corresponding increase in non-aeronautical revenues. To retain existing airlines and attract new airline clients, airports should offer reasonable aeronautical fees, which can be subsidized by lucrative non-aeronautical revenues. This raises questions about whether cross-subsidization pricing strategies are used in the U.S. airport industry. To examine this issue, we analyzed data from 59 large and medium hub airports between 2009 and 2019, focusing on the relationship between marginal costs and fees of aeronautical and non-aeronautical operations. The marginal cost was estimated from a translog variable cost function by utilizing a seemingly unrelated regression model. Our study highlights the importance of considering the complex interplay between aeronautical and non-aeronautical operations at airports and the potential for cross-subsidization. We also examined the factors influencing cross-subsidization at airports. The results reveal that large airports are less likely to engage in cross-subsidization compared to their counterpart airports. On the other hand, given that the FAA's airport classification diverges from that in the hub-spoke system, we incorporated airports that serve as hubs for legacy airlines (American, United, and Delta) into our model to account for the influence of hub status. Our findings indicate that hub status does not influence cross-subsidization decisions. In addition, airports governed by local authorities place less emphasis on cross-subsidization whereas the presence of airport competition often incentivizes a more pronounced adoption of cross-subsidization practices. Airports in densely populated areas have diminished focus on cross-subsidization while there is a positive correlation between local GDP and cross-subsidization. Finally, cross-subsidization practices do not differ between airports dominated by LCCs and those without such dominance. Future research should focus on exploring the implications of these findings for the welfare of passengers and other stakeholders in the aviation industry.

Impact of the COVID-19 Pandemic on Multi-airport Systems Worldwide

This study examines the impacts of the COVID-19 pandemic on multi-airport systems (MASs) worldwide. First, the recent literature on MASs is reviewed to identify emerging research topics and development patterns. Then, airline schedule data are collected for 53 sample MASs and used to analyse three dimensions of MAS structures before and during the late stage of the pandemic: (i) traffic and degree centrality distribution within MASs, (ii) intra-MAS airport competition; and (iii) airline competition intensity within MASs. The empirical findings reveal that MAS structures in Europe and the US have remained relatively stable despite the recent pandemic, partly because compared with Asia Pacific, air travel bans in these markets were lifted earlier, and domestic and international airline markets have largely returned to pre-pandemic levels. In comparison, significant changes have been observed in Asia-Pacific MASs due to restrictive bans on international travel and airline operations. As major airlines shifted capacity to domestic markets, in Asia Pacific intra-MAS airport traffic distribution became more balanced, intra-MAS airport competition intensified, smaller airlines dropped out, and airline concentration levels increased. In addition, with more under-utilized slots available, Chinese low-cost carriers increasingly consolidated their operations to selected airports within MASs which would allow them to achieve economies of scale. Overall, this study provides insights into the adaptability of MAS structures in the face of a global crisis.

Spatial dependence and competition between U.S. airports

U.S. commercial airports are public infrastructure owned and operated by government authorities. If so, do public commercial airports compete with each other? In this study, we investigated airport competition by applying the data of 59 U.S. hub airports from 2009 to 2019 in a Cliff-Ord typed spatial model. The model includes two modules: the first module captures the impact of neighboring airports on the airport's output with a spatial lag dependent variable, while the second module considers the bias resulting from spatial autoregressive error term. The results suggest that the airports' outputs are spatially and negatively dependent; namely, an increase in the outputs of neighboring airports leads to a decrease in the output of an airport. This indicates the existence of airport competition. In addition, we found that the outputs of airports governed by city and state are greater than those of ones governed by the port/airport authority after controlling for all other factors.

The competitiveness of global cargo airports employing the Best-Worst Method

PurposeThe global economy and air transport business have been negatively affected owing to the COVID-19 pandemic outbreak. As countries tighten restrictions on international movements, the growing emphasis on air cargo places pressure on airports to maintain and upgrade their cargo policies, facilities and operations. Hence, ensuring the competitiveness of cargo airports is pivotal for their survival under volatile global demand. This study aims to evaluate the importance of competitiveness factors for cargo airports and identify areas for further improvement.Design/methodology/approachThis study applies the Best-Worst Method (BWM) to assess the cargo airports' competitiveness factors.FindingsThe results identified “Transport Capacity” as the most significant competitiveness factor, implying that airport connectivity is crucial in promoting cargo transportation at hub airports. This result was followed by “Airport Operations' and Facilities' Capacity” and “Economic Growth.”. Additionally, the results identified Hong Kong International Airport as the best-performing cargo airport, followed by Aéroport de Paris-Charles de Gaulle and Incheon International Airport, respectively. Furthermore, both selected European airports are the most competitive airports in terms of “Financial Performance” and appear to be aware of the significance of their brand value.Originality/valueThis study forms a reference framework for evaluating cargo airports’ competitive positions, which may help identify airports’ relative strengths and weaknesses. Moreover, this framework can also serve as a tool to facilitate the strategic design of airports that can accommodate air cargo demand flexibly under demand uncertainty.

Evaluating civil aviation airport competitiveness in the Yangtze River Economic Belt of China: A lens of spatial-temporal evolution

The civil aviation industry plays an important role in advancing interregional socio-economic development. Investigating the competitiveness of civil aviation airports (CAAs) from the tempo-spatial change perspective aids in the optimization of airport layout towards balanced and coordinated regional development. This research assesses the overall competitiveness of 86 CAAs in 11 provinces or provincial-level municipalities of the Yangtze River Economic Belt (YREB) from 2009 to 2019 by the entropy weight approach, then characterizes their spatial-temporal evolution via Moran index of spatial auto-correlation analysis, and finally explores their dynamic changing tendency of the spatial variability based on Theil index measurement and decomposition. The findings are concluded: 1) From 2009 to 2019, the overall competitiveness of civil aviation airports is dramatically improved and an evidently hierarchical system is formed at the provincial level, with the spatial pattern of “strong in the east and west, weak in the middle”. 2) The global Moran indexes of civil aviation airport competitiveness in 2009, 2014, and 2019 are negative, indicating that superior and inferior airports are likely to be spatially clustered. 3) The local Moran Indexes show that the spatial agglomerations of civil aviation airports tend to be more evident in the recent decade. The high-high competitiveness clusters lie in the Yangtze River Delta Economic Zone for the long run, transforming from “Shanghai-Hangzhou” high-competitiveness pole to “Shanghai-Hangzhou-Nanjing” and further extending to central Jiangsu. Civil aviation airports in provincial capitals and secondary cities have formed clusters of high-low competitiveness. Moreover, clusters of low-low competitiveness stretch from the Yunnan-Guizhou Plateau to cities in the middle reaches of the Yangtze River. 4) The interprovincial Theil indexes of civil aviation airport competitiveness fluctuate, with the discrepancy increasing and then decreasing.

Airport competition in Brazil’s northeast region

Aviation growth is mainly due to the integration between national and world economies in the global era. The capital’s airports of the Brazilian Northeast were managed by a federal public company and are currently being granted to private companies, which have the premise of expanding the number of passengers. The increase in number of passengers drives competition between airports, since they must have adequate infrastructure to contain the demand. The choice by the user for an airport can be evaluated based on factors such as access mode, air fares, availability of flights and airport infrastructure. This paper aims at evaluating the choice of passengers between two airports in the Northeast of Brazil since 2014 and how this choice has been changing over the years. The binomial logit model was used to obtain the probability of choosing between airports and to evaluate the most relevant factors. The results of the study presented that availability for direct flights, preference for airlines, access time, air fares and general satisfaction of the airport fluctuated in the choice of the two airports during the study period. By evaluating the likelihood of choice, subsidies are provided to improve services considered indispensable by passengers.

Platform competition and consumer foresight: The case of airports

This paper studies the effect of competition and consumer foresight on platform profits. The focus is on airports, which provide passengers with aeronautical and commercial services through airlines and retailers. Our results can be summarized as follows. First, we unravel the relationship between consumer foresight and the optimal pricing of the two services. When passengers are myopic, they undervalue the surplus they derive from the retail services, so that the airport charges low landing fees and makes profits from the retail business. When passengers are foresighted, they better anticipate the surplus from the retail services, so that the airport changes its strategy by charging higher landing fees and boosting competition in the retail sector. Second, we find that the relationship between profits and consumer foresight strictly depends on the considered market structure. When the airport has no competitors, airport profits are non-decreasing in the degree of consumer foresight. By contrast, under duopoly competition, a weakly-negative correlation between airport profits and consumer foresight is observed. These results allow to derive two main managerial implications. First, airport competition can lead to higher landing fees. Second, under competition, an airport is not necessarily interested in informing passengers about its retail facilities. However, an extension where airports decide whether to set an advertising campaign to inform passengers about their retail facilities reveals that they end up locked in a Prisoner’s Dilemma.

Airport Competition and Megaregional Impacts: Challenges and Opportunities for Planning Institutions

Airport Competition and Megaregional Impacts: Challenges and Opportunities for Planning Institutions

Research on Passenger Throughput Forecast of Civil Aviation Airport Based on Multi-source Data

In order to scientifically predict the passenger throughput of civil aviation airports. The paper taked Hefei Xinqiao International Airport as the research object, comprehensively considers multi-source data such as GDP, permanent population, airport competition, and spatial distance, used multiple linear regression, gravity-regression and other methods to construct a prediction model, and the results were obtained by different methods. The prediction result errors were compared and analyzed. The results of the study show GDP and population are important factors affecting the passenger throughput of civil aviation airports. The multiple linear regression model that considers the factors affecting airport competition can improve the accuracy of prediction, and the gravity-regression model can effectively predict the passenger throughput of civil aviation airports.

Формування конкурентної стратегії аеропорту в умовах невизначеності

The article states that airports as part of the transport system are the most important component of the national, regional and local infrastructure. It has been proven that the basis of the airport's competitive strategy is the need to ensure its effective operation by adapting to the uncertainty of the external environment; is a tool for the formation and maintenance of competitive advantage, the basis of optimal distribution and effective use of resources. The purpose of the study is to develop a system approach to the formation of a competitive strategy of airports in conditions of uncertainty of the influence of the external environment. It is proved that the system of forming the competitive strategy of the airport is presented in the form of the following subsystems: information support for forming the competitiveness of the airport; airport competitiveness management; planning and forecasting the airport's competitive strategy; complex adaptability to changing operating conditions. It is substantiated that the competitive strategy of the airport: determines the direction of development of the airport as a system, its mission, goals, main tasks, forms and content of activity; establishes a uniform system of priorities for the airport and determines directions for their implementation; is the basis for making decisions in the field of transport policy and the growth of airport capitalization, the development of target programs for the development of the infrastructural component; is considered as a basis for developing a unified vision of the airport's modern role and prospects for its development, interaction with executive and legislative authorities of various levels, business, and users of air transport services. Further developments are aimed at developing a mechanism for forming a competitive strategy of airports in conditions of uncertainty.

Exclusivity in concession revenue sharing contracts

Our paper studies the effects of concession revenue sharing contracts by endogenizing the choice of the signatory airline. It is shown that an airport finds it profitable to share concession revenues with airlines and this increases both consumer surplus and social welfare. The airport prefers an exclusive agreement when the net per passenger revenue generated on non-aeronautical services at the airport is sufficiently low; it extracts higher payments by exploiting the competition between airlines to become the sole signatory. The level of aeronautical charges, that are regulated, influences the airport’s decision and, consequently, the intensity of airline competition. Welfare is higher under a non-exclusive arrangement, which may be in conflict with the airport’s decision. The incentive to use these contracts remains under airport competition and revenue sharing increases. With an airline alliance, revenue sharing increases traffic for a large enough degree of cooperation between airlines.

The effects of concession revenue sharing contracts in airport competition

This paper studies the effects of concession revenue sharing contracts to analyze how airport–airline vertical structures compete for passengers in the same catchment area. The analysis studies the effects of such contracts depending on airport ownership structure. We show that private airports tend to share less concession revenues than public ones eventually leading to lower welfare levels. These results have relevant policy implications when concession revenue sharing contracts are specified in practice.

The spatial dimension of competition among airports at the worldwide level: a spatial stochastic frontier analysis

This paper analyses the potential impact of airport competition on technical efficiency by applying the spatial stochastic frontier approach (SSFA) rather than the traditional model (SFA). The SSFA allows for isolating the cross-sectional spatial dependence and evaluating the role of intangible factors in influencing an airport's economic performance through the inclusion of the distance matrix and the shared destinations matrix calibrated for different distances. By analysing the statistical differences between the traditional and the spatial model, it is possible to identify the competition effects. This study includes 206 airports at the worldwide level. The results show the existence of the spatial component: we detected a different influence of airports’ efficiency levels according to the geographical distances. This could have not been captured by the traditional SFA. We conclude that when incorporating spatial spillover effects into the airport efficiency analysis, the efficiency dynamics are strongly dependent on the spatial distance among airports.

Comparative accessibility of Chinese airports and high-speed railway stations: A high-resolution, yet scalable framework based on open data

Despite China's massive infrastructure expansions in airports and high-speed railway (HSR), accessibility to these infrastructures from the passenger's perspective has yet been clearly analyzed and compared. The main objectives of this study are: (1) to evaluate accessibility by travel time between a given population grid cell and the nearest airport/HSR station, by accounting for both motorized vehicles and public transport; and (2) to measure and visualize the size of catchment area of an airport or a HSR station. We automatize the computation of free-flow road travel times, as well as the public transit times (by bus, subway, light-rail, tram and railway), from grid cells to infrastructure elements, by using a scalable routing framework. The Chinese air transportation network and HSR network are used as case studies to elaborate and evaluate the efficiency of our proposed framework. We find that the HSR network for China is much better accessible for the population than airports. Furthermore, grid cells with a high population density are much better connected to the Chinese transportation networks than other grid cells. Our methodology is generic in that it can be applied on an even larger scale (whole planet) and with different points of interest. Our work can help provide decision support for airport competition, privatization, and regulation, and for policy makers in infrastructure investment, in particular potential market and the location of new infrastructure elements.

Decentralized Congestion Policies: Pricing Versus (Grandfathered) Slots in Airport Networks

This dissertation consists of four related studies on the assessment of decentralized welfare-maximizing airport congestion policies involving (grandfathered) slot policy and pricing policy. Different demand structures and airport networks are considered in the presence of origin-destination passengers. These studies capture that local and non-local origin-destination passengers may have one or two destinations to choose from, in which the two destinations may or may not be considered as substitutes. This dissertation shows that even a small variation can fundamentally change the analysis and the assessment of the congestion policies. The first study considers networks with two or three airports. The results show that equilibrium policies involve slots when airport profits do not matter and pricing policies when airport profits matter. The main results show that in the presence of congestion effects, equilibrium slot policies will lead to too high and equilibrium pricing policies to too low passenger quantities relative to the first best outcome that maximizes the welfare of all airport regions. The second study considers a stylized airport network with two airports designed to clearly identify the role of local and non-local passengers. The analysis shows that the local welfare-maximizing slot quantity can coincide with the first-best outcome whereas this is impossible in the case of pricing policy. Whether the outcomes coincide in the case of slot policy depends on the shares of inframarginal and marginal local and non-local passengers. The results provide clear insights on the reasons why slot quantities are found to be excessive in the three-airport network considered in the first study. The third study is an extension of the analysis of the three-airport network considered in the first study. This extension involves a variation of the demand structure in the sense that the air services offered at the congested airports are considered as imperfect substitutes whereas they are not considered as substitutes in the first study. The analysis shows that the presence of substitute air services is a necessary condition for equilibrium slot quantities to reach the first-best outcome. The results derived from the second study help understand the reasons why equilibrium slot quantities can lead to first-best outcome. Whereas equilibrium pricing levels will always be too high relative to the first-best prices independent of the presence or absence of substitute air services. By contrast with the third study, the fourth study proceeds with the consideration of substitute air services for non-local passengers in a three-airport network to concentrate on the role of airport competition. The results show that airport competition will lead to too low equilibrium slot quantities in the case of slot policies, or too low equilibrium prices in the case of pricing policies, to maximize the total welfare of the two congested airports. The results further show that slot policies can lead to first-best outcome that maximizes the total welfare of three airport regions. Whereas pricing policies are too strict with too high equilibrium prices relative to the first-best outcome.

Research trend of Chinese airport terminal using the Network Analysis

With the acceleration of economic globalization, the development of aviation logistics plays an increasingly significant role in the logistics industry. As the foundation of aviation logistics development, airport terminals are attracting increasing attention. In this respect, the aim of this research is to analyze 65 academic papers on Chinese airport terminals from 2003 to 2020 by utilizing analytic keywords of academic papers and suggest the research trend of Chinese airport terminals. The SNA was adopted as research methodology. Airport Terminal, Boned, and Chinese Mainland were the keywords for the first period (2003-2008), while the second period (2009-2014) included the keywords such as China, DEA, Airport, and Flight Delay. For the third period (2015-2020), Airport Competitiveness and Aviation Network were also highly connected keywords. This indicates that with the growth of the economy, the research trend of China’s airport terminals has been gradually expanding from infrastructure construction to network development. The results have implications on suggesting the research trend of Chinese airport terminals, and providing insights to the policy makers, academics, and practitioners in neighboring countries including Korea.

Airport Competitiveness Analysis from Aircraft and Passenger Movement

Air transportation development is strictly related to airport competitiveness, since the airport management seeks to improve the capacity to produce services, increase passenger and aircraft movement, improve revenues from aeronautical and non-aeronautical activities, and optimise the other items related to the competitiveness of this type of organisation. In this sense, this study seeks to identify variables associated with the competitiveness of airports, based on their infrastructures, operations, and locations, which can influence the decision-making of airport managers continuously and efficiently. An analysis of the seven busiest Brazilian airports, in terms of aircraft and passenger movement, has been made, and multivariate data analysis has been used through a multiple regression, verifying the relationship between the variables of airports competitiveness, such as the total area of the airport site, number of aircraft parking positions, number of airlines, quantity of aircraft movementlandings and takeoffs, total number of passengers and the GDP of the city where the airport under study is located. The results present an index of competitiveness for each airport analysed after the data mathematical treatment, showing the coefficients at the general equations form aircraft and passenger movement.