Multiple Airport Regions Research Articles

Misallocation in multiple airport regions

In many of the most densely populated and dynamic economic regions around the world, passengers have access to multiple airports in their neighborhood. Beijing, Hong Kong and the Greater Bay Area, London, New York and Tokyo can serve as prominent examples. Due to geographic accessibility and facility characteristics, some airports within the same multiple-airport region (MAR) may have unused capacity whereas others experience severe congestion. Policy makers in MARs, therefore, face a common challenge: managing the allocation of air traffic among airports. Perimeter rules set upper limits on the distances of nonstop flights operated from specific airports within MARs. Traffic distribution rules such as perimeter rules have been used in the United States and Japan. In this study, we distinguish between misallocation and quantity effects. We demonstrate that in the absence of regulation (laissez faire) a combination of a high demand combined with low capacity, as would be the case for LaGuardia as well as Reagan National in the US, can produce substantial welfare losses due to misallocation. This indicates that there can be benefits from centralized policies in the form of perimeter rules and that the introduction or repeal of such rules requires a careful assessment of the effects on the MAR as a whole.

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.

Towards analyzing the robustness of the Integrated Global Transportation Network Abstraction (IGTNA)

The well-functioning of our transportation systems is essential for ensuring the mobility of people and goods. According to the Sustainable Developmental Goals (SDG) adopted by the United Nations General Assembly in 2015, it is of utmost importance to build and maintain a resilient infrastructure. In terms of transportation systems, a resilient infrastructure guarantees seamless connections and robustness against failures and targeted attacks. Existing studies on small-scale road, subway, or air transportation networks have revealed interesting patterns and phenomena for different parts of the world. These studies, however, are usually either spatially or modal-wise constrained. Most notably this holds for the worldwide airport network, which has frequently been analyzed in the literature. Transportation interactions on the ground are usually considered through aggregation of nodes into either cities or multiple airport regions. This conceptual simplification leaves room for the analysis of an Integrated Global Transportation Network Abstraction (IGTNA), covering aviation and ground transportation on our planet. We believe that it is crucial for planners and analysts to include all infrastructure, assets, networks, modes, and users as a single system. IGTNA enables to model all aspects of interconnectivity at a high-level of details, encoding points of interests as nodes and potential transitions between points of interests as links. Our aggregated network representation of the global transportation system consists of 5.3 million nodes and more than 8.6 million links. We propose scalable data extraction and network dismantling techniques. This study is, to the best of our knowledge, the first to report on the robustness of the IGTNA. We believe that our study enables decision-makers to achieve effective decision-making on future transportation investment through a holistic understanding of the impacts from negative shocks of disruptive events.

Evaluation of Homogenization in Metroplex Operations Based on Multi-Dimensional Indicators

The development of a Multiple Airport Region (MAR) could lead to fierce competition. To evaluate the level of homogenization between airports in a MAR, a homogenization evaluation method based on multi-dimensional indicators was developed. A multi-dimensional indicator system is proposed that takes into account infrastructure, integrated support, operational efficiency and airline networks. Then the Critic method and the Delphi method are used to assign hierarchical weights for each dimension of the indicators. The multi-layer homogenization matrix of the airport pairs within the MAR is derived. For airport pairs with high comprehensive homogenization, suggestions are provided according to analysis of the indicators. This study paper selected three typical MARs internationally to demonstrate the advantage of the proposed approach. The airport pairs with high a homogenous coefficient (greater than 0.5) were selected to analyze the reasons causing high homogeneity. Results show that the multi-dimensional indicators and hierarchical fusion captured the characteristics of the homogenization of MAR. Most airport pairs in New York MAR and in London MAR had strong differentiation of route network layout, airport pairs in Greater Bay MAR had ambiguous division of labor and low homogenization of route network, except CAN and SZX airports. Suggestions are discussed separately to mitigate the homogeneity of the airports in the MAS, thus, to improve the operation performance of the MARs.

A supply-side categorization of airports across global multiple-airport cities and regions

Cities and regions with multiple airports providing commercial air service are common across the globe. Within these regions, both airlines and consumers have various opportunities to provide air transport services on the one hand, and consume them on the other. While a literature addressing features of consumer behavior related to multiple airports and their regions has developed over the past two decades, very little research has taken a comprehensive global view of the regions themselves, and more specifically, of the assortment of component airports. The results of the present paper provide structure to the activities at airports within multiple airport cities and regions as of 2015. Using hierarchical cluster analysis, 131 airports in 53 global multiple airport regions are analyzed utilizing supply-side variables such as aspects of competition, routes, and aircraft capacities among others. The results show that the airports, identified from the literature, can be classified into six primary groups. Some of the groups confirm prior expectation, for example based, upon size. Yet other groups are, at least on the surface, a bit more eclectic. Moreover, combinations of airport type in individual cities and regions vary widely across geographies, pointing to the complexity of places and the industry. As global commercial aviation continues to change quickly along multiple dimensions, understanding the roles airports play, and the ways airlines use them becomes enhanced. Multiple airport regions will provide both opportunities and difficulties in navigating these changes.

Multiple airport regions based on inter-airport temporal distances

We formulate and implement a new metric for identifying multiple airport regions (MARs) around the world, based on the temporal distance between airports. This metric, opposed to existing studies based on spatial distance, takes into account the real travel time between airports of latent passengers and their journeys via ground transportation. We investigate a variety of properties of the newly built MARs network at the global scale for the year 2015, including the importance of MARs in global air transportation, similarity clustering, destination overlap, and airport roles inside a MAR. Commonalities and differences to the simplified spatial distance are identified.

Airport choice model in multiple airport regions

Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory.Design/methodology/approach: This research generates a Multinomial Logit Model (MNL), which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia). This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH) Airport and José María Córdova (JMC) Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport.Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

Airport location in multiple airport regions (MARs): The role of land and airside accessibility

This paper approaches the airport location problem as a function of accessibility considerations. First, a structural equation model is established to find the relationship between the size of an airport catchment area and its flight network scale. Landside and airside accessibilities are measured by the qualities and costs of surface transportation and flight networks. The two accessibilities are combined to form a regional air transportation accessibility profile, which can be used as a criterion to evaluate airport locations at a macro-planning level. Finally, the scenarios of airport locations in terms of small and large areas are analyzed using two regional case studies in China.

Route-level passenger variation within three multi-airport regions in the USA

Many large conurbations have more than one airport that serves the air transport needs of their region. This paper models the relative route level within three multiple-airport regions (MARs) in the United States: Boston, Washington, and San Francisco. Although passenger-level surveys provide the researcher with the most detailed information on how travelers choose between airports and airlines, as well as geographic information about both the start and end of a journey, such data are often difficult or expensive to obtain. Here, we use freely available aggregate data from the U.S. Department of Transportation and linear models to assess whether passenger levels on routes involving airports within the three cities vary in relation to known correlates of airport choice. The results show that they do, and that variables such as the “Southwest effect,” fare, and market size, among others, help explain the complexity of air-travel patterns within MARs. Importantly, the results point to the difficulty in easily classifying cities or airport pairs into simple groups. We conclude that aggregate data can be used to establish initial evidence of the strength of a functional multi-airport region and, as such, may prove useful in informing individual traveler-based research and as inputs to policy decisions.

Passenger choice decisions at a regional airport in South Africa

The choices made by departing air transportation passengers from multiple airport regions impact on the strategies of competing airlines, airport operators and planners and local authorities. For these stakeholders it is important to understand which determinants influence passenger decision-making. The purpose of this article is to determine the main factors which influence airport choice decisions at a regional airport in the Greater Johannesburg area in South Africa.

Low-cost airlines and airport competition

An important question from the viewpoint of competition analysis in the air transport industry is the extent to which low-cost airlines operating from a secondary airport compete with full-service airlines serving a main airport in a multiple airport region. In this paper we address the issue of the competition between full-service and low-cost airlines serving adjacent airports in the Greater London using econometric estimation of demand structure (own- and cross-price elasticities). Our analysis follows the methodology in (Pels, E., Nijkamp, P., Rietveld, P., 2000. Airport and airline competition for passengers departing from a large metropolitan area. Journal of Urban Economics, 48 (1), 29–45, Pels, E., Nijkamp, P., Rietveld, P., 2003. Access to and competition between airports: a case study for the San Francisco Bay area. Transportation Research Part A: Policy and Practice, 37 (1), 71–83). It is based on the nested logit model which we use to capture three key dimensions of passenger choice: air fare, surface-access costs and frequency. We obtained estimates of the own- and cross-price elasticities, which was the focus of our interest. On the basis of our understanding of the industry dynamics we find these estimates, especially of the cross-price elasticities, to be on the low side.

Passenger Market Equilibrium for Competing Airports in Multiple Airport Region

Major metropolitan areas are often served by two or three air carrier airports. Researchers have developed airport choice models that focus on the decision structures and attributes of the passengers’ choice of departure airport. A study extended the scope of airport choice models in a multiple airport system region and tried to estimate from the viewpoint of airport authorities how many flights a competing airport should seek and the resulting passenger shares when market equilibrium is reached. Each airport aims to maximize its own payoff in this game in an air travel oligopolistic market by determining its own strategies while being affected by those of its opponents. The payoff function is formulated to reflect the airlines’ and the passengers’ responses. The prices charged by airports to airlines are assumed to influence flight frequencies and, hence, the passengers’ preferences among airports. The passenger market shares equilibrium is then determined when no airport has incentives to deviate from its own pricing strategies. The structure of the model can help analyze the impact of airports’ strategies and those of their competitors. To demonstrate the model's potential as a policy analysis tool, a simple numerical example is designed and solved.

A parameterized consideration set model for airport choice: an application to the San Francisco Bay Area

Airport choice is an important air travel-related decision in multiple airport regions. This paper proposes the use of a probabilistic choice set multinomial logit (PCMNL) model for airport choice that generalizes the multinomial logit model used in all earlier airport choice studies. The paper discusses the properties of the PCMNL model, and applies it to examine airport choice of business travelers residing in the San Francisco Bay Area. Substantive policy implications of the results are discussed. Overall, the results indicate that it is important to analyze the choice (consideration) set formation of travelers. Failure to recognize consideration effects of air travelers can lead to biased model parameters, misleading evaluation of the effects of policy action, and a diminished data fit.

Airport and Airline Choice in a Multiple Airport Region: An Empirical Analysis for the San Francisco Bay Area

PELS E., NI JKAMP P. and RIETVELD P. (2001) Airport and airline choice in a multiple airport region: an empirical analysis for the San Francisco Bay area, Reg. Studies 35, 1–9. In this paper a nested logit model is used to describe passenger preferences concerning airports and airlines. A statistical model for the passengers' sequential choice of airport and airline is calibrated. It appears the nested multinomial logit model, with airports as the common elements in the nests, is statistically preferable to the 'standard' multinomial logit model. Frequency and access time to the airport are all significant. Separate models are estimated for business and leisure travellers, but there appear to be only small diVerences. PELS E.,NI JKAMP P. etRIETVELD P. (2001) Le choix d'aéroport et de compagnie aérienne dans une région à aéroports multiples: une analyse empirique du golfe de San Francisco, Reg. Studies 35, 1–9. A partir dA'un modéle emboîté logit, cet article cherche à présenter les préférences des passagers pour aéroports et les compagnies aériennes. Un modèle statistique relatif aux choix séquentiels des passagers est calibreé. Donné que les aéroports constituent les éléments communs des emboîtements, le modèle emboîté multinomial logit sA'avère statistiquement préférable au modèle normal multi‐nomial logit. La fréquence et l'accessibilityé sont, toutes les den deux, importantes. On évalue d'autres modèles pour ceux qui voyagent en classe affaires ou en touristes. Toujours est'il que les différences s'avèrent minimes. PELS E., NI JKAMP P. und RIETVELD P. (2001) Flughafen und Fluglinienwahl in einer Region mit mehreren Flughafeneine empirische Analyse fur das Gebiet der Bucht von San Francisco, Reg. Studies 35, 1–9. In diesem Aufsatz wird ein satzartig angelegtes Logitmodel dazu benutzt, die Bevorleszugung von Flughafen und Fluglinien seitens der Passagiere zu beschreiben. Ein statistisches Modell fur Reihenfolge der Flughafen'und Fluglinienwahl der Fluggaste wird geeicht. Er weist sich, daß ein satzartig angelegtes multinominelles Logitmodell mit Flughäfen als gemeinsamen Elementen in den Nestern statistisch dem 'Standard' multi‐nominellen Logitmodell vorzuziehen ist. Frequenz und Anfahrtszeit zum Flughafen sind wichtig. Es werden getrennte Modelle für Geschäftsreisende und Vergnügungsreisende erstellt, doch die Unterschiede scheinen nur gering zu sein.

Evaluation of the Patterns of Air Traffic Distribution According to Airport Accessibility in Multiple-Airport Regions

This paper evaluates the patterns of air traffic distribution according to the airport accessibility for passengers in multiple-airport regions. Previous studies have found that airport access time was one of the most significant factors of airport choice, so that we adopted access time as accessibility criteria. The developed model can allocate passengers to each airport depending on the accessibility, which considers passenger characteristics of both arriving/departing and transit passengers. The model was applied to the Tokyo multiple-airport region. A discussion of features of a future new third airport function in multi-airport system, based on the analysis results, concludes the paper.

Airport Choice in Multiple-Airport Regions

A logistic model is constructed to predict airport choice in a multiple-airport region and estimated using passenger data from the Washington, D.C./Baltimore area. In agreement with previous work, it was found that airport access time and flight frequencies were significant predictors of airport choice, although, as might be expected, decreased access time and additional flight frequencies were more important to the business traveler than to the nonbusiness traveler. Additional estimations indicated that when only those passengers within reasonable proximity of more than one airport were included in the estimation, the significance of access time decreased and that of flight frequencies increased. Additional variables for a passenger's experience with an airport were then included in the model and were significant. This would indicate that passengers who have used an airport will tend to continue to use the same airport, all other factors being equal.

Airport choice in a multiple airport region

This paper reports on an investigation of air traveler behavior in choosing among departure airports in a multiple airport region. Data from a 1980 survey of air passengers in the San Francisco Bay Area were used to study the characteristics of airport choice for local residents. Multinomial logit models were developed for business and nonbusiness travelers. The analysis demonstrates that ground access time and the frequency of direct air service to the chosen destination can account for a large portion of the variation in airport usage patterns, but that both access time and frequency have nonlinear effects on airport utility. It also suggests that even multi-stop direct service is strongly preferred to connecting flights. The results highlight the importance of attention to ground access in planning for multiple airport systems, and the difficulty of predicting airport use without information about market-specific airline schedules.