Comparative analysis of efficiency for major Southeast Asia airports: A two-stage approach

Within the past few years, the economy of Southeast Asia has been expanding rapidly with the rise in demand for air transport services. International airports are important driving forces for Southeast Asia countries' economies. Therefore, the competitive ability of these airports is very essential in terms of development and competitiveness within the region. This paper investigates the capabilities of these airports by a two-stage approach. The strengths and weaknesses of each Southeast Asia airport are evaluated by Data Envelopment Analysis – Slack-Based Measurement (DEA-SBM) in the first stage. This is a non-parametric approach to measure the efficiency of 9 major airports in the area including Changi Airport (Singapore), Suvarnabhumi Airport (Thailand), Kuala Lumpur Airport (Malaysia), Soekarno Hatta Airport (Indonesia), Ninoy Aquino Airport (the Philippines), Noi Bai Airport, Tan Son Nhat Airport (Vietnam) and Guangzhou Baiyun Airport (China), Hong Kong Airport (Hong Kong). In the second stage, Tobit regression is used to estimate the influence of multiple factors toward the efficiency of each airport. By generalizing and comparing two stages, the analysis allows us to evaluate each airport's efficiency in seven years, as well as the impact of multiple factors in one airport's performance. The implications for improvement are also obtained and discussed.     

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.     

Airport performance in a tourism receiving country: Evidence from Greece

The aim of this study is to estimate the performance of 38 Greek airports. The analysis is performed in two stages. Firstly, efficiency scores for each airport are estimated using Data Envelopment Analysis (DEA) original and bootstrap techniques. Secondly, statistical assessments (Mann–Whitney U and Kruskal–Wallis tests) and a censored Tobit regression model are employed to identify which factors significantly explain variations in the airport efficiency. The results indicated the scope for substantial efficiency improvements. In addition, island location, connectivity, and hotel infrastructure in the area were found to be significant factors affecting airport efficiency.     

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.     

Incorporating annoyance in airport environmental policy: noise, societal response and community participation

Airport capacity continues to be one of the air transport issues that creates the most concern. The major environmental constraint for airports is the noise generated by aircraft. Annoyed communities living around airports have become a limiting factor for airport capacity and operability. This paper brings together the existing literature in the fields of airport environmental capacity, non-acoustic factors of noise annoyance, NIMBYism and environmental conflicts. We also analyze the socio-environmental conflict between Barcelona airport and the community of Gavà Mar. This case shows that the lack of trust between parties, the impossibility of predicting noise exposure, the absence of opportunities for civil society to speak and the difficulty of accessing relevant information foster annoyance and mobilization in the communities that live around the airport. In addition, it is shown that, in such a situation, communities’ reactions can evolve to a post-NIMBY stage in which proactive attitudes replace reactive ones.     

Measuring total factor productivity of airports— an index number approach

There is an increasing trend towards corporatisation and privatisation of airports in an effort to improve performance. However, the normal financial reporting requirements associated with these forms of organisation are not sufficient indicators of the performance of airports since profitability can be more a function of the exercise of market power than a sign of productive efficiency. Also, there are concerns that efforts to regulate the prices charged by airports can result in under-investment and declining service standards. This makes it important to monitor the cost-efficiency, cost-effectiveness and service-effectiveness of airports. There is a growing literature on these topics, but so far there has been little attempt to apply the concepts of total factor productivity to the airport sector. We use a non-parametric index number method to illustrate how such a global measure can be used to investigate the role of disaggregated performance measures that often are very useful to managers and to those monitoring airport operations.     

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.     

Analysis of airport weather impact on on-time performance of arrival flights for the Brazilian domestic air transportation system

Air traffic operations are significantly impacted by weather conditions. These external factors may impose operational constraints and generate demand-capacity imbalances, leading to reduced on-time performance, additional airline costs and inconveniences to passengers. Efficient management of such disruptions requires an understanding of the main causes of flight delays towards increasing their predictability. In this study, we investigate the impacts of airport surface weather conditions on the likelihood of flight delays for the Brazilian domestic air transportation system. We use historical flight schedule, on-time performance and weather data and estimate a logit model to analyze how different meteorological variables at the airport of destination affect the probability of a delayed arrival. We obtain empirical evidence for the impacts of low ceiling and visibility conditions, precipitation and wind gusts on the likelihood of arrival delays for the set of Brazilian airports analyzed.     

Spanish airports performance and efficiency benchmark. A PESA-AGB study

This study uses a MCDA tool to analyse and improve Spanish airports performance and efficiency. Thus, a holistic study using MACBETH (with PESA-AGB) is used. This study has never been applied before in Spanish airports. Firstly, a literature review related to this study keywords is conducted, as well as about benchmarking concept applied specifically to airports. Secondly, several methodologies in used to benchmark airports are reviewed and compared. Thirdly, airport performance and efficiency issues are addressed and described. Finally, the MCDA-MACBETH (with PESA-AGB) tool is applied to 4 Spanish airports.Spanish airports belonging to AENA transported 263, 753, 406 passengers in 2018 with an increase compared to 2017 of 5.8%. General data enables to conclude that.Spanish air transportation system is growing annually and hence there is the need to improve airports performance and efficiency, also to maintain the high levels of quality to address the growing demand. Spanish air transportation system is growing annually and is it upmost important to maintain high levels of quality to address such demand. Through this study, performance and efficiency improvements are seek within several airport key areas such as Safety and Security, Quality Service, Productivity and Effectiveness, Financial and Environment.     

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.     

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.     

Airports’ managerial human capital,ownership, and efficiency

Airport performance differences require a better understanding of the sources of efficiency and competitive advantages. Globalization drives the air transport industry into a more market-orientated business questioning the relationship between managerial decisions and airport performance. Aviation management studies do not consider managerial capabilities and skills since they are intangible exogenous factors that are difficult to assess. In this study, a stochastic frontier analysis is performed accounting for top managers' theoretical knowledge and experience enclosed as exogenous drivers of airports' efficiency. The model analyses 12 Polish airports from 2009 to 2017. The results show a diversity of airports with a different number of passengers as efficient. The top managers' experience, when gained in the same airport, has a positive impact on airports' technical efficiency. Airports having unstable management are more technically inefficient. Independently of the efficiency level, some airports change their management after the national elections, suggesting that managers are chosen by political interest rather than by their specialised knowledge or their prior experience in aviation management. The results suggest that more practical knowledge improve airports’ performance. Airports with a majority of government ownership that are the largest ones increase their efficiency significantly, suggesting that political decisions may be discriminatory in detriment of airports managed by regional and city authorities.     

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.     

Sustainable efficiency drivers in Eurasian airports: Fuzzy NDEA approach based on Shannon's entropy

This research explores the physical infrastructure and flight consolidation efficiency drivers of Eurasian airports regarding their infrastructure and movement productivity levels. A novel Fuzzy Double-Frontier Network DEA (FDFNDEA) model is proposed to investigate the relationship between desirable (freight and passenger turnovers) and undesirable (pollutant emission levels due to aircraft movements) outputs against the respective infrastructure usage, fuel consumed, and movements performed at each of the 23 Eurasian airports from 2000 to 2018. This balance between desirable and undesirable outputs emerges spatially and temporally due to the evolution of the airport system's productive resources at each one of the Eurasian countries over the period observed. Shannon's entropy is used as the cornerstone to quantify the input and output vagueness of this evolution in Triangular Fuzzy Numbers (TFN), thus allowing the accurate building of alternative optimistic and pessimistic double-frontier efficiency. Differently from previous research, Shannon's entropy is the key for measuring input and output vagueness levels in light of the maximal entropy principle. This principle states that the distribution that best represents the current state of knowledge is the one with largest entropy. Maximal entropy yields bias-free decision-making in the sense that the input/output distributional profiles for Eurasian airports contain the maximal possible heterogeneity, working as a robust or best/worst-case scenario against eventual unconsidered assumptions. Hence, optimistic and pessimistic Malmquist Productivity Indexes (MPI) for overall and each stage productivity results are subsequently regressed against contextual variables related to airport characteristics and regional socio-demographic and economic indicators of each Eurasian country using bootstrapped Cauchy regressions. The findings revealed the spatial heterogeneity of productivity factors and airport performance across Eurasia. Results also demonstrated the negative impact of income inequality and the positive impact of private participation on technological progression in the Eurasian airport industry.     

A dynamic network efficiency measurement of airports performance considering sustainable development concept: A fuzzy dynamic network-DEA approach

In this paper, sustainability of airports is considered through a multi-perspective, multi-system, and multi-process operation. It is explored how an extension of fuzzy dynamic network performance measurement approach helps to determine the efficiency performance of an airport system. In this way, a three-pronged approach is intended which considers the internal functions of an airport, functions affecting the community and functions related to the passengers simultaneously. This novel combination makes it possible to have a comprehensive evaluation of airports' performance. Besides, fuzzy extension of SBM dynamic network approach makes it possible to deal better with the vagueness of variables during analysis. So, this extension is valuable from both technical and conceptual aspects which in turn provide useful information and insights for the future design of holistic strategies connected with sustainable development of airports where ever they are.     

Measuring airports’ operating efficiency: a summary of the 2003 ATRS global airport benchmarking report

This paper provides a partial summary of the 2003 ATRS (Air Transport Research Society) Global Airport Benchmarking Report which uses the annual data for 2000–2001. The objective of the ATRS benchmarking report is to measure and compare the performance of several important aspects of airport management and operation: productivity and efficiency, unit costs and cost competitiveness, financial results. The report also examines the relationships between various performance measures and airport characteristics in order to better understand the observed differences in airport performance. This particular paper extracted from the benchmarking report focuses on measuring and comparing operating efficiency performance of the world’s major airports. In particular, the paper presents the results on the airports’ Variable Factor Productivities (VFP) after removing the effects of the variables beyond managerial control. In the process, it identifies the effects of various factors influencing airport’s VFP, and computes a ’residual’ VFP index as an indicator for airports’ operations efficiency.     

Greek airports: Efficiency measurement and analysis of determinants

This paper presents a performance evaluation of the Greek airports considering their relative technical efficiencies and factors determining these determinants. The analysis shows the importance of seasonality in demand on the performance of the airports, and the effect of location, size and operating characteristics on their technical efficiency, signifying peculiarities of the Greek airport system.     

Determinants of Brazilian international flights: The role of hub-and-spoke and infrastructure variables

The objective of this study is to evaluate the determining factors influencing airline companies to operate international origin-destination (O-D) routes from different Brazilian airports. The results are based on a panel data model and support the assumption that statistically significant explanatory variables stem from gravity factors (GDP and an airport competition measure weighted by distance), hub-and-spoke variables and capacity inputs. We find that a composite variable made up by the airport capacity variables – given by the size of the terminal building and the length of runways – and its domestic connections have a positive effect on airport competitiveness. In conclusion, we find that not only well-known demand-side factors, but also supply-side variables – strategic decisions taken by airport management – matter in attracting international flights.     

Small community airport choice behavior analysis: A case study of GTR

The issue of airport selection attracts considerable attention. However, most studies focus on using advanced discrete choice models to analyze airport choice behavior in metropolitan areas with several closely located, competing airports. This paper addresses passengers’ choice behavior in selecting between local small community airports and more distant major commercial airport. It looks at factors affecting air travelers’ airport choice behavior in cities with small community air service. Data relating to the Golden Triangle Regional Airport in Mississippi is used in logistic regressions to identify the key factors that influence air travelers’ airport choices. Ticket price, experience with Golden Triangle Regional Airport and flight schedule were found to be the strongest effects.     

Can we explain airport performance? A case study of selected New York airports using a stochastic frontier model

This paper uses stochastic frontier models to assess whether technical efficiency at Newark Liberty International, New York John F. Kennedy International, and New York LaGuardia airports improved from June to August 2008 compared with the summers of 2000 and 2007. An airport is efficient if it can handle operations on-time by minimizing overall demand and maximizing available airport capacity. Granger-causality tests determined the factors that may cause changes in key components and indicators of airport performance. Compared with the other airports, JFK experienced the greatest improvement in technical efficiency. The Granger-causality tests stressed the significance of airport operations and en route factors in supporting efficiency.