Airport Choice Research Articles

Discrete Choice Model Applications for Air Passenger Airport Choices: A Literature Review

Airport development is a critical factor for regional growth, improving connectivity, and stimulating economic growth. Considering the complexity of planning and policy making in this area, multiple models and frameworks have been introduced to support decision-making processes. Among these, Discrete Choice Models (DCM) stand out for their capacity to project market flows, assess the validity and benefits of implementing airport modifications, tailor policies, improve the operations’ service level, and boost revenues. Given their extensive use and importance, a thorough review of DCM applications within the context of air transportation is both timely and necessary. This review organizes and evaluates the use of DCMs in air transport research. Both descriptive and predictive applications of DCMs are analyzed, focusing on choices related to airports and related levels, such as access mode and airline decisions. Each reviewed study is classified based on the type of model used, application context, data characteristics, employed variables, and methodological contributions. Through this analysis, six prevailing gaps are identified in the current state of DCM application in air transportation: improve data quality, enhance models with detailed trip and passenger information, explore advanced modeling techniques, incorporate general correlation and substitution structures, consider non-compensatory decision-making processes, and extend applications to new geographic and temporal contexts.

Modeling airport choice for a multi-airport area using a random parameter logit model

Recent years have seen a growing demand for air transport which has led to an increase in the number of airports providing a significant number of flights in Spain and throughout the rest of Europe. Choosing which airport to use depends on the competition between the airlines operating from them and how accessible they are to the residents in the surrounding areas. This research introduces an efficient design based on D-error using a stated preferences survey to study user behaviour when choosing between competing airports. The data is modelled using a Multinomial Logit Model and a Random Parameter Error Component Logit (RPECL), a discrete choice model which allows us to study user preferences taking into account their varying systemic and random tastes, as well as find specific correlations which may exist between similar alternatives. This meant the authors were also able to calculate the direct and cross elasticities to examine the weight of the different variables involved in making the choice of airport. The results showed, for a study case in Spain (Bilbao and Seve Ballesteros - Santander airports), that increased access time to the furthest airport caused an important fall in demand (choice) for that airport. It was also shown that access fees had a lower elasticity than the flight cost and that the fewer the transfers required to reach the final destination increased the probability of choosing an airport. Therefore, in order for smaller airports to compete with larger airports they need to invest more in reducing the cost of flights, attracting more low-cost companies and offering more direct complementary destinations than those provided by larger airports.

Airport choices and resulting catchments in the U.S. Midwest

Air travelers originating from the catchment areas of airports – typically defined by administrative or geographic boundaries – will sometimes “leak” across these boundaries to farther, often larger airports that offer more attractive services and options. To investigate the attractiveness of different airports based on their proximity and geographic position relative to one another, we assess the airport choices of air passengers across a large region of the US Midwest that spans multiple administrative boundaries and airports. We combine a dataset of air tickets purchased by these passengers with other publicly available datasets, and apply mixed logit airport choice models based on air service attributes and airport access distance. We take multiple subsets of the total air tickets dataset using Halton sampling in order to achieve model estimation convergence. Model estimates are compared between data subsets, and consistently lead to the following key results. First, changes in air service attributes on short- and medium-length routes will have a more uniform influence on air passengers' airport choices, compared with long routes. Second, comparable proportional changes in air service attributes lead to greater changes in the catchment areas and market shares of small and medium airports, compared with large hubs. Within these service characteristics, airfare is found to impact passengers' airport preferences more than flight frequency. Finally, the catchment areas and market shares of small- and medium-size airports are influenced by the proximity and geographic location of neighboring airports; this differs from the catchments of large airports, which strongly extend into multiple jurisdictional boundaries in all directions despite the presence of surrounding airports. The study results provide further insight into the influence of air service attributes on long-distance airport choices over large geographic regions served by a diverse set of airports, and the resulting implications on multimodal transportation planning within and across such regions.

Modeling Airport Choice Using a Latent Class Logit Model

Studying the location of an airport is essential for optimizing its functionality, ensuring safety, and maximizing its economic benefits. There are many airports located within a short distance of each other, and users can often choose to travel between one or the other depending on a number of variables that they value for their final choice. In this paper, we design a stated preference survey and estimate a latent class logit model to study user behavior in the choice of nearby airports. The idea is to study if the choice of airport can indeed depend on the characteristics of the users and the purpose of their trip and if factors such as traveling with family, children, or friends can play a role in determining the preferred airport. It is also investigated whether the presence of low-cost airlines or direct connections to the final destinations of the trip (number of transfers) and other factors influence the choice of airport. It is shown that there are two classes of users who have different travel behavior, and that the perception of certain variables influences the choice of the nearest or furthest airport depending on the type of trip.

PRIVATIZING INDIAN AIRPORTS - A SCRUTINIZED EVALUATION THROUGH VARIED CONTEMPLATIONS

This paper elucidates the changing ownership of Public owned airports to Privatisation. The analysis is envisioned towards the passengers’ interest in availing air transport which are likely to become more efficient. The improvisation of regional connectivity would yield more people to opt for air transport. A series of efforts were taken before making the questionnaires that were placed in the survey including the psychological aspects when deciding about the choice of airports which are getting privatized. The collected inputs from the passengers vary from seldom travelers to frequent travelers across the country are analyzed using the linear programming technique such as the DEA[1] which depicts the effective views of the travelers to go for Privatisation. The questionnaire was carefully framed such that all the aspects covering ergonomics level, including the ease of navigation, the reach of supporting staff. The airports would get diversified with their services without the intervention of Government. In India, a total of 137 airports which include 23 International airports (3 Civil Enclaves), 10 Customs Airports (4 Civil Enclaves) having custom and immigration facilities for limited international operations and 104 Domestic airports (23 Civil Enclaves) are administered by the Airport Authority of India (AAI).[10] The USA has 14,549 Private airports (74%) within the total 19,636 airports. Many countries like the USA, Russia, China, U. K, France have a larger number of Privately-owned airports helping their countries in getting economically strengthened. IATA forecasts a growth of 6.8% per annum for India. The usage of No frill airports would reduce the cost of capital investment in making an airport to start functioning and help the nation to grow in the economy. In addition, Six AAI airports are operated, managed, and developed under Public-Private Partnership (PPP) namely, Guwahati, Jaipur, Ahmedabad, Mangalore, Thiruvananthapuram and Lucknow. At Mumbai, Delhi, Chennai, and Ahmedabad, Performance Based Navigation (PBN) arrival and departure procedures have been implemented and for Hyderabad airport, it is in progress and Space-based, Final Operational Phase (FOP) of (GAGAN), GPS Aided Geo Augmented Navigation[10] is under implementation which is not airport-based and will be available for use at all of the country's airports. Enhancing the prediction of outcomes through feature selection, the Data envelopment analysis (DEA) method is used for the analytics questionnaire. This is a function whose form is based on the efficiency of the scrutinized evaluations. It's an approach for measuring the performance efficiency of global public airports through varied contemplations of results of the survey. This technique aims to measure how efficiently a DEA uses the resources available to generate a group of outputs along with feature section models that are then analyzed after that to evaluate the contributing factors for airport operation and privatization.

Understanding the ground access and airport choice behavior of air passengers using transit payment transaction data

We investigate the ground access and airport choice behavior of individual air passengers that use rail transit in their ground transport to airports. Using a novel dataset of payment transaction records of rail transit trips, we calibrate a binomial logit model of individual's choice between two airports in Beijing, China to examine air passengers' preferences for ground rail service attributes including travel time, travel cost and number of transfers and compute the implied value of travel time and transfer penalty. We further visualize the spatial distribution of access and egress air ridership across the city at the rail transit station level with a set of heat maps and develop a gravity model to understand factors that affect the air ridership at individual stations. Our findings have significant implications for airport planner and transit authorities in assessing the potential benefit of airport rail link projects and improving the efficiency of regional airport systems.

Managing a multiple-gateway airport system with super high-speed rail

In this study, we analyzed the airport choice behavior of inbound Chinese travelers to Japan. We determined the effect of launching super high-speed rail (SHSR) on air-rail integration and its effect on the gateway functions of airports connected by high-speed rail or SHSR. We developed a bi-level model adopting nested-type stochastic user equilibrium using a capacity constraints model. Based on simulations, we concluded that (i) introducing SHSR can reduce the congestion at the primary gateway airport; (ii) direct connection with SHSR can enhance the gateway function of secondary gateway airports; (iii) when a low-cost carrier is operating in the market, the gateway function at secondary airports without SHSR may be diminished by the introduction of SHSR.

Long-Distance Airport Substitution and Air Market Leakage: Empirical Investigations in the U.S. Midwest

Following airline mergers and network reorganizations aimed at reducing operational costs, consolidated air services at large hub airports have encouraged air travelers to forego use of their smaller local airports to access large hub airports offering superior air services farther away. This study investigates airport leakage in areas of Wisconsin and Michigan served by small airports, where air travelers may leak to neighboring large hubs. Using a proximity-based service area definition, three airports experiencing leakage are identified, and a hierarchical logit airport choice model is applied that accounts for air service characteristics and access distance for travelers coming from these airports’ service areas. Results show that a similar mean number of flight legs at both the local and substitute (large hub) airports will encourage leakage at Dane County Regional and Gerald R. Ford International airports, indicating that adding direct flights alone will not be sufficient to combat leakage. Comparable access distances to local and substitute airports have opposite effects on the local markets of Gerald R. Ford International and Milwaukee Mitchell International airports—promoting leakage at the former but discouraging it at the latter. Furthermore, proportional increases in airfares at local airports lead to uneven losses of markets in investigated service areas. Overall, the study provides empirical evidence of long-distance airport leakage in parts of the U.S. Midwest, and how its implications can be used by small airports seeking to further understand and respond to travelers’ airport choices within their local markets.

Modeling hesitancy in airport choice: A comparison of discrete choice and machine learning methods

Noticing that people may become more hesitant about their airport choice when exposed to abundant information and multi-channel on-line sales opportunities, this paper analyzes hesitancy in the choice of transfer airport in a multi-airport region using three approaches: a multinomial logit model, a random forests algorithm, and deep reinforcement learning. These methods are applied to the outcomes of a stated choice experiment, which was designed to survey the iterative airport choice process under hesitancy. The results indicate that a quarter of the passengers show evidence of hesitancy. Further, the deep reinforcement learning approach is found to provide the highest accuracy in representing the stated choices; the random forests algorithm also gives good results in capturing the reconsideration decision, while the multinomial logit model seems less accurate in representing the choice behavior of interest. Moreover, hesitancy involved a switch from flight-related attributes to ground transport-related attributes. Managerial implications for airlines and airports are discussed.

Spatio-temporal dynamics in airport catchment areas: The case of the New York Multi Airport Region

Using the example of domestic connections departing from the New York Metropolitan Area, this paper contributes to research on airports' catchment areas in Multi Airport Regions by exploring their spatio-temporal dynamics. Given that previous research has consistently shown that airport accessibility and different elements of airport utility (fare, connectivity characteristics, on-time performance) are key drivers of airport choice, we draw the analogy with Huff models to calculate airport attractiveness to passengers in different census block groups. We marshal data sources that allow for an assessment of the spatio-temporal variability in the accessibility and utility of airports, which allows us to compare catchment areas for different times of the day, days of the week, and quarters of the year, and this for different utilities as well as overall utility. Results reveal different types of dynamics, and can be used as the input to follow-up research. We argue that such a model-based approach holds major potential in comparative research and research on MAR dynamics, but should be fine-tuned through the use of other information sources, refined model specifications, and state preference data.

The impact of airport parking fees on the tourist's airport/airline choice behavior

This paper analyzes the airport/airline choice behavior of tourists for Saxony/Germany. We employ flexible parametric choice methods (mixed logit) in order to test the effect of standard attributes on the choice probability. In addition we extend existing literature with the introduction of parking charges in the choice experiment. Our results show a significant and negative impact of parking charges on airport choice probability. Thus, we can compute high elasticities of parking charges for tourists. These results suggest, that airport managers have in form of parking policies a powerful policy instrument as they can directly affect the size of the airport catchment area.

Reinterpreting the role of primary and secondary airports in low-cost carrier expansion in Europe

This paper discusses the long-term effects of low-cost carrier (LCC) presence at European airports and identifies the airports that have benefited the most from LCC consolidation since 2001. The research uses ‘LCC Market Share’, in terms of seats, to measure the relative importance of LCCs within each airport; and introduces ‘EU LCA Rank’ as a normalised metric of the capacity share of every airport in the European low-cost segment. It evaluates the trends between 2001 and 2019 in all airports in Europe using OAG supply information (seats by carrier). Results show two different phases of LCC rise in Europe, 2001 to 2008 and 2009 to 2019, marked by the effects of the financial crisis of the Great Recession. The analysis highlights the role that LCCs have played in boosting the growth of both primary and secondary airports. Indeed, despite the fact that LCCs have put many smaller airports on the European map, during the second phase of the period of analysis growth has been more significant for major airports and for a few airports that were keen to support the earliest development of LCCs. In that sense, this paper contributes to a better understanding of the historical and contemporary dynamics in European LCCs choice of airports and, in particular, the long-term effects that this disruptive business model have had for airports. This is increasingly important in the context of a potential recovery path from the effects of the response to the Covid-19 pandemic. This paper also attempts to settle academic discussions that attach LCC development to secondary/regional airports disregarding the wide range of strategies used by airlines and airports.

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.

An Analysis of Inverse of Airport Choice Leakage in China Multi-Airport Regions

An Analysis of Inverse of Airport Choice Leakage in China Multi-Airport Regions

Simulating the Market Share Variation in Multi-Airport Area Incorporating Airport Choice Habit

Simulating the Market Share Variation in Multi-Airport Area Incorporating Airport Choice Habit

Determinants of air traffic volumes and structure at small European airports

This study investigates the determinants of air traffic volumes and structure (carrier type) at lesser studied small European airports serving below one million passengers per annum. It discusses airport choice factors for airline customers and focuses on the characteristics of small airports and their catchment areas in order to explain variation in 2016 traffic volumes for 146 regional gateways in 21 EU countries. Through the application of multiple linear regression and correlation it is found that population size, airport charges and the need for capacity coordination are the most related to the number of passengers using these airports. Several different correlations are found with respect to the share of low-cost, full-service and charter carriers as a proportion of total airport traffic, which in most cases extends the findings of the limited number of other studies in the field of small regional airports. The research concludes that while certain relationships can be found, their statistical significance is moderate, leaving scope for a deeper study into a smaller samples of airports.

Competition and Sustainability Development of a Multi-Airport Region: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area

A new era in the development of multi-airport regions (MARs) has been in China, especially in the construction of global urban areas such as the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). In order to better understand competition and provide significant advice to support sustainable development of Chinese MARs, this paper takes the GBA-MAR as an example, and then explores the competition between airports in this multi-airport region based on route level and its impact on passenger airport choice using three liner models. According to our findings, competition is concentrated on a few air routes in the Northeast–East Coastal region and the Asia-Pacific region, in which all three airports operate. Although the domestic market of the GBA-MAR has been relatively mature, the international air transport market is still left with considerable room, which is also reflected in connections to the world’s cities and tourist destinations. In addition, the research also found that different airport brands created by route type significantly affected passenger airport choice. Overall, the study revealed that whether from a supply or demand aspect, competition between airports in a multi-airport region—not just airline competition in a single airport—is an important topic.

Determining factors of air passengers’ transfer airport choice in the Southeast Asia – North America market: Managerial and policy implications

This paper investigates the factors affecting air passengers’ transfer airport choice in the market between Southeast Asia (SE Asia) and North America (NA). By estimating demand parameters, the study sheds lights on an airport operator’s business strategies, including identifying effective routes to compete for transfer passengers. Specifically, a discrete choice model is applied to estimate air travelers’ utility function from choosing different transfer airports in an origin-destination market. Our dataset consists of 78 city-pairs in the SE Asia–NA market. Instrument variables are used to control for potential endogeneity of airfare, while airport characteristics including minimum connection time (MCT), service quality, size, and detour degree are treated as exogenous. The main empirical findings are: (1) Transfer passengers’ airport choice is determined by an airport’s characteristics including MCT and service quality of flight connection, in addition to the traditional factors such as airfares and travel time. (2) Based on the estimated utility function parameters, we quantify transfer passengers’ willingness-to-pay for several characteristics of the transfer airport. (3) With our estimation results, a case study is conducted for Incheon International Airport to identify candidate routes that have the greatest potential for the airport to increase the number of transfer passengers.

Examination of low-cost carriers' development at secondary airports using a comprehensive world airport classification

The existing literature appears to suggest that low-cost carriers (LCCs) tend to focus their business at “secondary airports” instead of “primary airports”. However, there lack systematic quantifiers to distinguish the two airport types. The present paper investigates whether this remark still holds today, and if not, whether the change is a worldwide phenomenon. We first establish a systematic parameterization to classify airport types, based on aviation network connectivity, regional importance, and MAR (multi-airport region) effects. With this classification of world airports, our analysis of the latest empirical data shows that some previously indubitable features of LCCs might have slowly changed. In particular, LCCs are expanding fast at both upper-tiers’ and lower-tiers’ airports, and there is a trend of shifting airport choice from lower-tiers’ to upper-tiers’ airports for LCCs in some continents. The evolving competition relationship between the full-service carriers (FSCs) and LCCs is also discussed.

Determining Factors of Air Passengers' Choice of Transfer Airports in the Southeast Asia – North America Market: Managerial and Policy Implications

This study investigates the factors affecting air passengers’ choice of transfer airport in the market between Southeast Asia (SE Asia) and North America (NA). It estimates demand parameters and sheds lights on the business strategies for an airport operator including identifying effective routes to better compete for transfer passengers. Specifically, a discrete choice model is applied to estimate air travelers’ utility function from choosing different transfer airports in an origin-destination (OD) market. Our data consists of 78 routes in the SE Asia - NA airline market. Instrument variables (IVs) are used to control for potential endogeneity of airfare, while we treat airport characteristics including minimum connection time (MCT), service, size, and detour degree as exogenous. The main empirical findings are the following: 1) Transfer passengers’ airport choice is determined by an airport’s characteristics including MCT and service quality, in addition to those traditional factors such as airfares and travel time. 2) Based on estimated utility function parameters, we also quantify transfer passengers’ willingness-to-pay for several transfer airport’s characteristics. 3) With our estimation results, a case study is conducted for Incheon International Airport to identify candidate routes that have the greatest potential for the airport to increase the number of transfer passengers.