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.     

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.     

Cost efficiency of African airports using a finite mixture model

This paper evaluates the operational activities of African airports using a finite mixture model that allows us to control for unobserved heterogeneity. In doing so, a stochastic frontier latent class model, which allows for the existence of different technologies, is adopted to estimate cost frontiers. This procedure not only enables us to identify different groups of African airports analysed from Angola and Mozambique, but also permits the analysis of their cost efficiency. The main result is that three groups are identified in the sample, each equipped with completely different “technologies”, suggesting that distinct business strategies need to be adapted to the characteristics of the airports. Some managerial implications are developed.     

Determining the relationship between ownership and technical efficiency by using a dynamic stochastic production frontier approach

This study adopts dynamic stochastic production frontier approach. Because of the impact of quasi-fixed inputs, airports cannot immediately adjust their production processes. Based on the heterogeneity of public and private airports’ operation models, this study estimates their individual production adjustment speed and their short-run and long-run technical efficiencies to compare transnational airport business performance. The results reveal the differences in the production adjustment of airport groups under different ownerships and performance. Private airports have faster production adjustment, whereas public airports have higher short-run and long-run technical efficiencies. As their primary goal, public airports should strive to increase the elasticity of production adjustment to increase the production adjustment speed, thus improving their long-run technical efficiency. On the other hand, private airports should prioritize eliminating short-run inefficiency to increase their actual output level, thereby improving their long-run technical efficiency.     

Technical efficiency of UK airports

In this paper, the random stochastic frontier model is used to estimate the technical efficiency of UK airports. The airports are ranked according to their productivity for the period 2000–2005 and homogenous and heterogeneous variables in the cost function are disentangled. These changes the ranking of the efficiency of UK airports compared to more conventional measures.     

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.     

Relative efficiency of European airports

Using data envelopment analysis, efficiency ratios for European airports are determined. It appears that most airports are operating under increasing returns to scale. This is also reflected in the most productive scale size determined for the airports.     

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.     

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.     

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.     

The impact of national macro-environment exogenous variables on airport efficiency

Our paper tests the extent to which airport efficiency is affected by national macro-environmental factors. The literature on airport performance measurement is extensive but has tended to focus mainly on estimating the effects on efficiency from what are mostly endogenous variables. We undertake a two-stage analysis of 59 international airports observations in the Europe and Asia-Pacific regions. The first stage involves the use of Data Envelopment Analysis (DEA) to measure the efficiency of these airports. This is followed by a second stage, where we use a Truncated Regression model that incorporates the Simar and Wilson bootstrapping technique to test the extent to which a set of macro-environmental factors affect airport efficiency. Results reveal that a state's air transport sector output, institutional quality and robustness, the macro-economic environment, safety and security, and human development, all have a significant influence on the performance of airports. The result of this study fills the gap in the literature related to the non-discretionary variables affecting the performance of airports. It also suggests that policymakers and airport managers consider the identified factors when benchmarking airports.     

Efficiencies and scope economies of Chinese airports in moving passengers and cargo

The paper looks at the technical efficiency of Chinese airports using multi-output stochastic input distance function analysis. This method provides a statistical test of scope economies to investigate the contribution of air cargo transport to airport efficiency. Our findings confirm the presence of scope economies in air passenger and air cargo transport among airports in China. We compare and contrast these results with results obtained from single-output stochastic production frontier analysis in which the effect of scope economies is not included. Our results indicate that the presence of scope economies significantly affects the estimation of technical efficiency, thus implying different efficiency rankings among airports in China.     

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.     

Accounting for size in efficiency comparisons of airports

This paper adopts the metafrontier model to analyze and compare the technical efficiency of small and large UK airports. The interesting feature of the model is that it takes into account the technological differences in the estimation of efficiency, and thus increases the accuracy in the efficiency comparison between heterogeneous airports. Results show that large airports are generally more technically efficient and have less operational wastage than small airports. Along with size, factors such as location, technological access, and capital investments could contribute to the efficiency difference between small and large airports.     

Airport quality and productivity changes: A Malmquist index decomposition assessment

This paper analyses the productivity of 20 Italian airports management companies during the period 2006–2008 using a DEA Malmquist index that includes a quality component. The proposed methodology is applied for the first time to the airport industry. In doing so, we directly assess the impact of the quality of services delivered by an airport on its productive performance. The study shows that, while Italian airports possess an acceptable level of quality in terms of their infrastructure, their managerial/administrative procedures must be strengthened in order to better deal with both technological modernization and passenger waiting time at the airports.     

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.     

Competition and efficiency in the Italian airport system: new insights from a conditional nonparametric frontier analysis

We analyse the effect of competition on technical efficiency of Italian airports by applying a novel conditional nonparametric frontier analysis for the first time to the airport industry. We find that competition affects mostly the frontier of best performers, whilst airports that are lagging behind are less influenced. A novel two stage approach shows that, on average, competition has a negative impact on technical efficiency. We estimate a measure of pure efficiency, whitened from the main effect of the competition, whose distribution has a bi-modal shape, indicating the existence of two differently managed groups of airports.     

The Italian airport industry in transition: a performance analysis

This paper analyzes the impacts of Italian government actions on the efficiency of 36 airports between 2001 and 2003. The changes have included privatization, enlargement of the services provided directly by airport management companies, through the modification of the concession agreements, and the creation of two hubs. The analysis, using the consolidated two-stage data envelopment analysis with bootstrapping, indicates that airports with a majority public holding are on average more efficient and the presence of two hubs is source of inefficiency.     

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 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.