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.     

Car parking management at airports: A special case?

The number of employees who daily commute to an airport represents, on average, one quarter to one half of the daily number of passengers. At UK airports it is rare for employees to pay for their car parking, with most employers absorbing the charges imposed by the airport authority. This paper details the main issues with offering free parking to employees drawing comparisons between a selection of case studies where parking management measures for employees have been introduced, and the airport sector. The paper then reports on a survey and a series of focus groups that were conducted with employees at a large UK airport in order to gauge their attitudes and likely behavioural responses to potential parking management strategies. Key findings are presented to show how airports may be able to learn from the experiences of others in the successful introduction of parking management strategies, but that there are also key barriers that are specific to airports that would need to be overcome.     

Performance assessment of UK airports: Evidence from a Bayesian dynamic frontier model

This paper analyzes the cost efficiency of UK airports over the period 1998-2008, using a Bayesian dynamic frontier model. This model provides a more structural explanation for the variation in airports inefficiency than has been presented by previous models, and also allows for cost inefficiency effects. On average, the dynamic frontier results, estimated via the Markov Chain Monte-Carlo simulation, indicate that UK airports improved their efficiency over time. Factors found to be important determinants of cost efficiency include airport size, price regulation, price cap variations and airport competition. Policy implications of the results are derived.     

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.     

Indicators and evaluation model for analyzing environmental protection performance of airports

This study develops an evaluation model for analyzing environmental protection performance of airports. First, indicators for evaluating environmental protection at airports are derived by reviewing related literature and existing environmental management plans using the Fuzzy Delphi method. Then, the weights and value functions of these indicators are obtained through expert questionnaire surveys. Applying the value functions to the environmental data from different airports yields the value of each indicator. Finally, multiplying the values with their corresponding weights sheds light on the performance of individual and overall indicators. Findings of this study offer references for airport management in evaluating airport performance in energy conservation, carbon reduction, and implementation of environmental protection measures, as well as in developing performance improvement schemes according to the state of the airport.     

Understanding air travellers' trade-offs between connecting flights and surface access characteristics

This paper reports on a study which seeks to improve our understanding of how people choose between different kinds of flight at competing airports, and how their choices are affected by access conditions. In particular, using stated choice data collected in Scotland, it investigates whether improving surface access to regional airports that are in relatively close proximity to one another (Glasgow and Edinburgh) leads people to avoid taking indirect flights from their nearest airport in favour of direct flights from an alternative airport. In line with expectations, our estimation results from Cross-Nested Logit models show strong aversion to connecting flights, resulting in a willingness to either pay higher fares for direct flights or accept non-trivial increases in access time. For the latter, even without the potential new direct rail link between the two airports, current access times are such that a scenario where direct flights were only available at the non-home airport, a substantial share of passengers would choose to travel from the alternative airport.     

Does a reward program affect customers’ behavioural intention of visiting the airport? A case study of Singapore Changi Airport

An understanding of the behavioural intentions of customers in visiting airports may help airport management to boost airport retail revenue (i.e. non-aeronautical revenue) by increasing customer spending at the airports. This study aims to examine the connection between airport reward programs and customers' behavioural intentions of visiting the airport, attempting to bring some benefits and credits for implementing reward programs in the airport sector by using Singapore Changi Airport as a case study. Two types of customer behavioural intentions (i.e. time spent at the airport and various purposes of visiting the airport) were investigated in the study to examine the effects of Changi Airport's reward program (i.e. Changi Rewards). An on-line survey was conducted, and the participants' responses were analysed via a structural equation modelling approach. The results showed that the attractive benefits of Changi Rewards could have a positive influence on arousing customers' intentions to engage with the programme. In addition, customers' intentions to engage with the programme can have a positive effect on increasing passengers' time spent at the airport and inducing customers to visit the airport for leisure purposes. Managerial implications to the airport sector are discussed.     

A comparative efficiency analysis of Spanish and Turkish airports

AENA in Spain and DHMI in Turkey operate a large majority of the airports in their respective countries. These two airport operators share some similar characteristics, but also present many differences with respect to their management strategies. For instance, the Turkish DHMI introduced a Build-Operate-Transfer (BOT) model and concession agreements, which enables active private participation in airport management. In contrast, management and operation responsibilities at all airports in Spain –with a few exceptions-have remained with AENA. This paper utilizes a data envelopment analysis (DEA) to compare the relative efficiency of airports within AENA and DHMI for the years between 2009 and 2011. Based on the efficiency scores, it further identifies the sources of inefficiencies resulting from various management strategies and other external factors. The results indicate higher average efficiency levels at Spanish airports, but private involvement enhances efficiency at Turkish airports. The majority of the airports in Spain and Turkey operate under increasing returns to scale. Certain policy options, including a higher private involvement and improvement of the airport network by closing some inefficient airports, should be considered in order to increase the airport efficiency in both countries.     

Operational efficiency of Asia–Pacific airports

Airports are important drivers of economic development and thus under tremendous pressure from emerging competitors. However, few studies have analysed the operational efficiency of Asia–Pacific airports. This study therefore evaluated the operational efficiency of 21 Asia–Pacific airports between 2002 and 2011. A two-stage method was used: Data Envelopment Analysis (DEA) to assess airport efficiency, followed by the second-stage regression analysis to identify the key determinants of airport efficiency. The first-stage DEA results indicated that Adelaide, Beijing, Brisbane, Hong Kong, Melbourne, and Shenzhen are the efficient airports. The second-stage regression analysis suggested that percentage of international passengers handled by an airport, airport hinterland population size, dominant airline(s) of an airport when entering global airline strategic alliance, and an increase in GDP per capita are significant in explaining variations in airport efficiency.     

Sustainable airport development with performance evaluation forecasts: A case study of 12 Asian airports

This study evaluates airport performance from 2014 to 2021 with actual and forecasted data to help plan airport sustainability and establish sustainable airport development strategies. Eight Chinese airports (PEK, PVG, CAN, SZX, SHA, XMN, HAK, and HKG) and four representative Asian airports (HND, ICN, SIN, and DEL) are studied. Airport performance is evaluated from the process level (i.e. operational processes providing aeronautical service and financial processes providing commercial service) to the airport level using the Network DEA with actual and forecasted data from the grey model. Results indicate that HKG has been and will be efficient for the entire study period. There is an observed trend of an overall efficiency decrease during the forecast period of 2018–2021. This study classifies operationally efficient airports (PEK, HND, and XMN) and financially efficient airports (HAK, ICN, and DEL). Mainland Chinese airports show significantly higher operational efficiency than financial efficiency, and lower rankings in overall efficiency. It is expected that mainland Chinese airports will soon develop beyond the transportation center, possibly towards the aerotropolis, balancing economic, social, and environmental aspects for sustainable development. This study helps airport management to evaluate sustainable development strategies by assessing current and near future conditions affecting sustainability.     

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 and route classification by modelling flight delay propagation

Flight delay can be divided into the root and propagated delays for identification and analysis of airports/routes that have a great influence on actual flight delay using flight operations raw data (tower logs) for South Korean domestic flights. In addition, the presented concept of “generated delay” classifies airports as affecting other airport delays or affected by other airport delays. The generated delay refers to the delay time at a particular airport/route, and this delay thereafter actually propagates to other airports/routes. In this study, the generated and propagated delays were displayed on a two-dimensional graph, and the airports/routes were grouped according to delay characteristics. Group A represented airports with high generated and propagated delays, and group B represented airports that are highly affected by delays of preceding airports/routes. Group C represents airports where newly formed delays affect other airport delays, but these airports mitigate delays from other airports. Airports in group D have relatively low delays and propagation. Thus, we targeted airports belonging to groups A and C because of their delay propagation impact on other routes/airports, which must be reduced by decreasing the root delay from targeted routes/airports. Among the airports, Jeju international airport (CJU) had the highest average delay time and propagated flight delay time with similar averaged generated delay times. Among the routes, departure flights from various airports to CJU had significant propagation effects on the subsequent flights. CJU and related routes have a very large impact on domestic flight delays because South Korean domestic airline routes are concentrated on CJU. However, there has been no quantitative analysis, and it is meaningful that the quantitative analysis results were presented in this study. In addition, we suggest that other airports such as GMP (Gimpo), CJJ (Cheongju), WJU (Wonju), and KUV (Gunsan) have a significant impact on domestic flight delays.     

Substitution and complementarity in aviation: airports vs airlines

In this paper a model concerning substitution and complementarity on the linkage between airport facilities and airlines from the viewpoint of pricing policy is formulated. This model is used to analyze whether airport pricing policies, e.g. to ensure cost recovery, are compatible with competition for transfer passengers. It is found that airports with a high volume of demand can pursue cost recovery and still be the most preferred hub. Airports with a low level of demand will not be the preferred hub, even if the larger airport charges higher taxes to recover costs.     

Improving US airport taxicab services through governance arrangements

Most airports internationally have implemented customer satisfaction programs into their operations to increase non-aeronautical revenues. In the US, taxicabs are an essential airport transport mode given the limited public transport options available. Effective airport taxicab planning efforts can increase airport customer satisfaction levels, as well as facilitate handling increased airport passenger volumes. However, little is known on how US airports have adapted their governance practices from a traditional hierarchical to a network approach in their efforts to undertake airport taxicab planning initiatives since the deregulation of the transportation industry. Data acquired from 51 US hub airports is used to examine their existing taxicab planning practices. The findings offer how US airports can modify governance processes in their airport taxicab planning processes to better support increases in the customer satisfaction levels of airport taxicab patrons.     

Estimating airport efficiency of New Zealand airports

New Zealand's airport industry has experienced substantial growth over recent years, but few studies have analysed the operational efficiency of New Zealand airports. This paper aims to extend the study of Francis and Lyon (2007) by exploring the efficiency and productivity changes of New Zealand's major airports between 2010 and 2012, using slacks-based measure (SBM) model and the Malmquist productivity index (MPI). The findings suggested that the majority of New Zealand airports increased efficiency and productivity during the period under investigation, but should decrease scale of operations in order to operate at their most productive size. Decomposition of the MPI showed that most New Zealand airports experienced gains in efficiency but, in terms of technology, they have regressed. Four significant factors (i.e. airport hub status, airport operating hours, airport ownership, and the Rugby World Cup 2011) were identified by the Simar–Wilson bootstrapping regression analysis as explaining variations in airport efficiency. Importantly, the significant effect of the Rugby World Cup 2011 (a major sport tournament) on New Zealand's air transport demand and airports' efficiency has been demonstrated in this research.     

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.     

Operational performance evaluation of international major airports: An application of data envelopment analysis

This paper uses data envelopment analysis to assess the operational performance of 20 major airports around the world. It is found that the form of ownership and the size of an airport are not apparently correlated with operational performance of airports. In contrast, the existence of a hub airport, the location of the airport, and the economic growth rate of the country in which the airport is located are all related to the operational performance of airports. The 20 airports are put into four groups according to their efficiency values.     

Applying deep learning models to twitter data to detect airport service quality

Measuring airport service quality (ASQ) is an important process for identifying shortages and suggesting improvements that guide management decisions. This research, introduces a general framework for measuring ASQ using passengers’ tweets about airports. The proposed framework considers tweets in any language, not just in English, to support ASQ evaluation in non-speaking English countries where passengers communicate with other languages. Accordingly, this work uses a large dataset that includes tweets in two languages (English and Arabic) and from four airports. Additionally, to extract passenger evaluations from tweets, our framework applies two different deep learning models (CNN and LSTM) and compares their results. The two models are trained with both general data and data from the aviation domain in order to clarify the effect of data type on model performance. Results show that better performance is achieved with the LSTM model when trained with domain specific data. This study has clear implications for researchers and airport managers aiming to use alternative methods to measure ASQ.     

Evaluating financial performance of commercial service airports in the United States

Studies on airport performance have focused primarily on productivity and operational efficiency. There are very few studies on airports’ financial viability and strength, especially those in the United States. Most of the U.S. commercial service airports are government-owned entities and operated for the service of the community rather than for profit, but expected to be financially self-sufficient and raise capital funds mainly through the bond markets. However, past studies of the financial performance of U.S. airports have relied on traditional profitability measures and financial efficiency measures that are more appropriate for airports owned and operated by for-profit entities. Based on the literature for non-profit organizations and the practices of credit rating agencies and government oversight bodies, this paper adopts six pertinent financial performance metrics to measure and compare the operational financial performance, leverage, and liquidity of 60 large and medium commercial service airports in the United States during the 2010–2017 period. The paper further examines factors that may affect airport financial performance. The results reveal that large hub airports have better liquidity while medium airports have better leverage during the study period. These results suggest that the effect of airport size on financial performance is inconclusive. Regression analysis shows that airports with high productive efficiency and those without a dominant carrier tend to have more surplus revenues for meeting their operational financial needs and capital spending and have better liquidity. The paper highlights the importance of using appropriate metrics to evaluate the financial performance of public sector entities and provides relevant information to bond investors. The devastating impacts of the COVID-19 pandemic on airports accentuate the significance of leverage and liquidity. Therefore, the financial metrics discussed in this paper would help support public policy debates and allocate public funds to the airports.     

Marketing innovation: Sources,capabilities and consequences at airports in Europe's peripheral areas

This paper investigates sources, capabilities and consequences of marketing innovation at airports in Europe's peripheral areas. A questionnaire-based survey was administered to airport managers. Ten sources of airport marketing innovation are identified. Innovation is significantly higher at airports that are administered as an independent entity compared to airports that are administered as part of a regional or national airport system. Large airports have a significantly higher level of innovation compared to small airports. Innovation has a significant positive effect on airport marketing performance, irrespective of the strategic focus of the airport.