Passengers' airport choice and airports' catchment area analysis in cross-border Upper Adriatic multi-airport region

Although much research has been performed on passengers' origin airport choice, there is little research on airports' catchment area size and even less on airports' catchment areas in cross-border regions. This paper addresses passengers' airport choice and analyzes airports' catchment area size and its homogeneity in the Upper Adriatic region. Using the results of passengers' survey at three regional airports (Ljubljana Jože Pučnik Airport (LJU), Venice Marco Polo Airport (VCE) and Trieste Pietro Savorgnan di Brazza Airport (TRS)) we have estimated the airports' catchment areas and airports market shares therein using multinomial logit (MNL) model structure. To additionally explore the passengers' airport choice behavior considering the different sensitivity across travellers to regional, demographic and airports attributes and account for preference heterogeneity in airport choice a mixed logit model was used. The results indicated that the three airports have relatively small core catchment areas and that the market share rapidly decreases with the increasing access time to airport. Partially, the results reinforced earlier findings showing that access time to airport is the most important determinant in airport choice for all segments (business/leisure and cross-border/domestic), however the sensitivity to access time is more pronounced in business and domestic group. Additionally, the results indicated pronounced loyalty to domestic airports and generally low importance of ticket prices, and show that in market conditions where all airports in the region have a low-cost carrier (LCC) the effect of LCC on airport choice is limited. Finally, the results indicated that the borders might have an influence on airport choice and that overall, in the cross-border regions the passengers’ airport choice process is even more complex than in non cross-border regions.     

Airport partial and full privatization in a multi-airport region: Focus on pricing and capacity

This paper studies the capacity and pricing choice of two congestible airports in a multi-airport metropolitan region, under transition from a pure public, centralized airport system to partial or full privatization. We develop analytical models to investigate three privatization scenarios: public–private duopoly, private–private duopoly, and private monopoly. We find that, airports follow the same capacity investment rule as prior to privatization when capacity and pricing decisions are made simultaneously. Pricing rule after privatization becomes more complicated, with additional factors having an upward effect on the privatized airport(s) and a downward effect on the remaining public airport.     

Operational efficiency analysis of Beijing multi-airport terminal airspace

Multi-airport systems are growing in number and size globally, despite being afflicted by known inefficiencies due to the interferences between the flows of neighbouring airports. A macroscopic empirical approach is proposed in this paper to estimate the capacity penalties and demonstrated by a numerical case study for Beijing, which is projected to become one of the busiest metroplexes in Asia. The Pareto envelopes of the theoretical and observed peak hour capacities are statistically analysed to quantify the penalties in a comparable metroplex and are subsequently modulated by a sigmoid correlation function. The analysis predicts the practical capacity of Daxing, the penalty incurred by the pre-existing Capital airport and by the total multi-airport system. Various findings are drawn and discussed, highlighting the needs for further research.     

The origin–destination airport choice for all-cargo aircraft operations in Europe

In this paper, we analyze the origin–destination airport choice for freighter operations of combination and all-cargo carriers in Europe. First, we discuss the choice process of airlines qualitatively. Next, using a stated choice experiment, we show that the presence of forwarders at an airport is the primary factor in explaining airlines’ choices, especially for airlines serving main airports. For airlines primarily serving regional airports, the possibility for night-time flights is most important. Finally, the presence of passenger operations at an airport is not a significant factor and the level of origin–destination demand is of limited importance.     

Effects of competition and policy changes on Chinese airport productivity: An empirical investigation

This paper investigates the influence of competition and aviation policy reform (for example, the airport localization program and listing airports on stock markets) in China on the efficiency of Chinese airports. By using Data Envelopment Analysis, we estimate both the productivity level and its growth for 25 sample Chinese airports. After controlling for hub status and other airports' characteristics, we find that: (i) publicly listed airports are significantly more efficient than non-listed airports; (ii) airports with more competition are more efficient than their counterparts; (iii) the airports' efficiency and the technical progress are positively correlated with the airport localization program; and (iv) the impacts of open-skies agreements and airline mergers on the airports' efficiency are statistically insignificant.     

Factors influencing cargo agents choice of operations in Abuja airport,Nigeria

The ability of an airport to attract traffic can vary within a multi-airport model of operation and highly competitive environment. This study is an effort to examine the factors that cargo agents rank as most important in their choice of Abuja airport cargo transhipment operations. A questionnaire survey was conducted on a random sample of members of the Association of Nigeria Customs Licensed Agents (ANCLA) at Abuja airport for primary data collection. The study employed a combination of Factor Analysis (FA) and Multiple Linear Regression (MLR) to analyse the data collected. The results of the factor loadings indicate airport capacity, airport charges and customs efficiency as the most significant factors that agents consider in their choice of handling cargo through Abuja airport. The three variables were found to have a high correlation relationship (R = 0.802) with the dependent variable of airport choice after subjecting it to regression analysis. This serves as information to airport managers for the airport planning of capacity in cargo operations within multi-airport country such as Nigeria.     

Market segmentation analysis for airport access mode choice modeling with mixed logit

Accessing airports can be considered as a crucial issue since passengers need not miss their flights. This issue makes the mode choice to access the airports important to study on and develop policies regarding it. Many studies show destination type as domestic or international affects the airport access mode choice, along with other factors. In this study, we investigate the effect of destination type of mode choice using mixed logit, using market segmentation approach. Market segmentation regarding destination type as domestic or international is a first in airport access mode choice modeling. Revealed-preference data was collected by face-to-face passenger surveys at Ataturk International Airport in Istanbul, Turkey, in 2015. We did market segmentation analysis for Multinomial Logit (MNL) and Mixed Logit (ML) models. When MNL and ML models were compared, it was observed that ML was superior to MNL. Further, results of market segmentation analysis revealed that using segmented models produced more accurate results than using the pooled model; both in MNL and ML. This finding was also supported by the value of time estimates; there were significant differences between domestic and international travel markets in terms of airport access mode choice. These results showed that different transportation policies may be introduced for domestic and international traveler segments, which also were explained.     

Estimating the sensitivity of small airport catchments to competition from larger airports: A case study in Indiana

An accurate estimation of airport catchment area enables airlines and airport operators to make informed decisions and to target potential markets precisely. This study uses the state of Indiana as a case study to estimate traffic leakage from the local airport, Indianapolis International Airport (IND), to two large hub airports in Illinois, the neighboring state of Indiana, namely Chicago O'Hare International Airport (ORD) and Chicago Midway International Airport (MDW). By using a decision making model that considers flying cost and access cost, this study simulates from local passengers' perspective which origin airport delivers the most cost effective flight itinerary. Using the top 20 routes of IND in 2018 as model inputs, the catchment area of two Chicago based airports in Indiana with variable coverage is plotted for different traveling scenarios. The analysis shows that an airport catchment area is sensitive to location, service level and traffic volume of competing airports nearby, as well as purpose of travel (business or leisure), number of travelers in a group (single, couple, family or multiple), length of trip, destination (domestic or international), preference of airlines (network carrier or budget carrier), and frequent flyer program status (premier member or general member). These findings could be valuable to all three aforementioned airports as well as airlines serving these airports when allocating operational and marketing resources. More importantly, this study creates a generic model that could be used by virtually any airport to estimate scenario-based catchment area using readily available itinerary and spatial data without resorting to expensive passenger surveys.     

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.     

Modelling the effects of capacity constraints on air travellers’ airport choice

This paper analyses the effects of limited capacity on air travellers’ airport choice. The analysis is based on a market-segment specific airport choice model that accounts for limited capacities. The region of Stuttgart in Germany serves as a case study to examine the impact of limited airport capacity on air travellers’ airport choice. Air travellers’ choice depends on the supply of flights and accessibility of the airports in their choice set as well as on their preferences and willingness-to-pay. To elaborate the effects of limited airport capacity, scenarios relating to the capacity situation at airports serving the air travel demand of the Stuttgart region are analysed. This paper reveals the mutual dependence among airports. Capacity constraints at one airport cause spill-over effects and thus influence air travel demand served at other airports. In some cases this may even lead to new capacity constraints elsewhere.     

Evidence of passenger preferences for specific types of airports

Studies of air travel choice behaviour increasingly make use of data collected through stated choice surveys. Here, we put forward the hypothesis that when making their choices in such surveys, respondents may complement the information presented to them by additional attributes. Specifically, we look at characteristics linked to airport size and breadth of service, as well as the proximity to a respondent's home. Our findings in a discrete choice analysis suggest that, all else being equal, respondents prefer larger to smaller airports while having a preference for the airport closest to their home. This could suggest that even though respondents associate a higher likelihood of delay and other inconveniences with larger airports, there is a perception that if things go wrong (e.g. flight cancellations), the backup options at larger airports (e.g. replacement aircraft) are superior to those at small or regional ones.     

A border effect in airport choice: Evidence from Western Europe

Some commentators suggest that air travelers are reluctant to use a foreign airport as a point of departure for their journey. Such reluctance has implications for marketing and policy measures, especially in border regions and in smaller countries, such as the Netherlands and Belgium. In this study, we tested this supposed barrier effect of national borders with empirical data.Our research is based on a subsample (n = 4083) of a large-scale survey among German, Dutch and Belgian adults. Participants were asked about their most recent flight, preferences regarding long-distance travel, and general travel behavior. The survey information about the most recent trip was linked to the Official Airline Guide with data from 18 airports in the Western European region. On average, however, only 10 airports offered a direct connection to the destination of the respondents’ most recent flight. A conditional logit model with varying choice sets allowed us to model only the relevant airports per respondent, while accounting for other known determinants in airport choice, such as travel time, airline competition, and number of available flights.The model results confirmed our expectations: people strongly prefer a departure airport situated in their own country. The model predictions suggest that without the border effect the share of people in our sample departing abroad would rise from 7.7% to 18.7%. Experience (with multiple airports as a point of departure) mitigates the barrier effect of the border. The performance of our model is good: the median probabilitie for the chosen alternative is 68%. Our research stresses the importance of the barrier effect of borders in airport choice: even when traveling across borders in the European sky, national borders remain important.     

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.     

US airport financial reform and its implications for airport efficiency: An exploratory investigation

This study investigates the effect on airport productive efficiency of two major funding sources used by US airports, namely the Airport Improvement Program (AIP) grants and the Passenger Facility Charges (PFC). A two-stage Data Envelopment Analysis (DEA) modeling approach is employed for this purpose. In the first stage, we estimate airport productive efficiency using a variable returns-to-scale DEA model with both desirable and undesirable outputs. In the second stage, random effects regression models are estimated with airport efficiency scores from the first stage as the dependent variable and PFC and a proxy for AIP grants as two of the explanatory variables. By applying the two-stage DEA model to 42 primary US airports, it is found that PFC use has a positive impact on airport productive efficiency, whereas the impact of AIP grants is negative. Multiple counterfactual scenarios are examined by altering the mix of the two types of funding sources. The results show that simultaneously raising the PFC ceiling and decreasing AIP grants could lead to greater airport productive efficiency. The US federal aviation authority would also benefit from realizing these scenarios, especially given the budgetary constraints it faces.     

Covid −19, the collapse in passenger demand and airport charges

This paper analyses the price responses of airports to a demand collapse, such as that prompted by Covid-19. In the crisis, airports need to achieve viability, in the short run through sufficient liquidity, and in the long run, by covering costs. From a public policy viewpoint, price increases in a crisis are argued to be undesirable, as they would further jeopardise the viability of airlines and tourism as well as the wider economic transport benefits such as connectivity. The institutional environment of airports differs from airport to airport; some are publicly owned, others are private but regulated, and others face competition. The price response of each (of 6) types of airport is considered, and how policy could respond to keep prices low in the crisis while ensuring longer term viability. Regulated airports could defer price increases until demand had recovered, if regulators insisted they do so. Publicly-owned airports could be directed by governments to keep charges low. Governments might also state that unregulated airports that raised charges could be made subject to price regulation in the future. Competitive airports would be unable to raise charges but this could jeopardise their viability. In this case and others where airports might need financial assistance, assistance could be made conditional on keeping charges low in the crisis.     

Access mode choice for relocated airports: the new Athens International Airport

To estimate the capacity requirements for all access related facilities of a new airport and to set pricing or operational policies it is necessary to forecast the share of each transport mode that airport passengers use. The development of these forecasts cannot be based on mere transfer of experience from other airports, particularly in the modern era of wide regulatory reforms, liberalization of the aviation market and increasing airport competition. First access modal split at the existing airport is determined via passenger classification and discrete choice modeling. Both are conducted via a passenger survey study specifically designed for this purpose. The resulting models are then employed to forecast access modal splits for the relocated airport by proper adjustment of the attribute values. The method is applied to the new Athens International Airport.     

Brand perceptions of airports using social networks

The management of social media activities by airports is an emerging issue, and existing empirical literature on the measurement of brand perception in the airport industry is lacking. Usually, the measurement of brand perception is carried out by surveys, which are costly and rapidly become outdated. This study employs a newly developed algorithm to infer brand perceptions by mining the social connections of airports. Twitter accounts of 118 airports in the world are analysed by considering three emerging attributes in the airport industry: environment, disability and luxury. The paper shows how it is possible to identify the current positions of airports in the perception of the customers.     

Intermodal integration in air transportation: status quo, motives and future developments

Soaring air traffic, increasing urban expansion and airports operating at full capacity are reasons that have caused a discussion about improvements in airport landside access systems. One approach to better match customer demands and address airport congestion is to facilitate the intermodal integration of airports. Building on a survey on intermodal passenger air transportation, we elaborate on the current and future situation at major airports. Our findings indicate a high modal concentration and dependence on individual access modes. However, while airport managers intend to reduce the share of these modes, they plan to increase that of high-occupancy airport access modes. We analyze the underlying motives that cause airports to extend their connections to surface infrastructure. In a case study, we assess an intermodal best practice solution for the integration of air and rail.     

Estimating hourly variations in passenger volume at airports using dwelling time distributions

A mathematical model using a probability density function of the terminal dwelling time distribution is developed to estimate the number of passengers arriving at an airport terminal at various times. A two-way ANOVA that tests the effects on different airports and access time durations were carried out, and the results showed a significant difference between terminal dwelling times among airports. The paper also provides some insight into airport terminal operation when there are significant changes to flight schedules and the introduction of new airlines, etc.     

Measuring airport quality from the airlines’ viewpoint: an application of data envelopment analysis

The main objective of this paper is to develop a model to determine the relative efficiency and quality of airports. This factor seems to have a strong effect on the airlines’ choice of hubs. Previous studies of airport quality have used subjective passenger data whereas in this study airport quality is defined from the airlines’ viewpoint. Accordingly, we have solicited airlines’ evaluations of a number of European and non-European airports by means of a detailed questionnaire. Statistical analysis of the median score has shown that these evaluations vary considerably relative to quality factors and airports. The key methodology used in this study to determine the relative quality level of the airports is Data Envelopment Analysis (DEA), which has been adapted through the use of principle component analysis. Of the set of West-European airports analyzed, Geneva, Milan and Munich received uniformly high, relative efficiency scores. In contrast, Charles de Gaulle, Athens and Manchester consistently appear low in the rankings.