Non-parametric analyses of efficiency of airports

This paper estimates the efficiencies and productivity changes of 12 international airports in the Asia-Pacific region based on data from 1998 to 2006. We apply stochastic frontier analysis (SFA) to compute efficiency estimates and use the Malmquist productivity index (MPI) to analyze productivity changes. We use the SFA model with a translog-type production function after testing the statistical hypotheses. According to the results of the SFA hypothesis tests, airports have experienced a technological regression; the deviations from the efficiency frontier are caused more by technical inefficiency than random noise. However, the inefficiency was found to decrease. The MPI reveals a declining trend resulting more from technological change than from efficiency change, with a decrease in inefficiency. Taken together, both the hypothesis tests and the MPI not only provide consistent conclusions, but also suggest that airports should concentrate on technological progress.     

Effects of corruption on efficiency of the European airports

The effect of corruption on airport productive efficiency is analyzed using an unbalanced panel data of major European airports from 2003 to 2009. We first compute the residual (or net) variable factor productivity using the multilateral index number method and then apply robust cluster random effects model in order to evaluate the importance of corruption. We find strong evidence that corruption has negative impacts on airport operating efficiency; and the effects depend on the ownership form of the airport. The results suggest that airports under mixed public–private ownership with private majority achieve lower levels of efficiency when located in more corrupt countries. They even operate less efficiently than fully and/or majority government owned airports in high corruption environment. We control for economic regulation, competition level and other airports’ characteristics. Our empirical results survive several robustness checks including different control variables, three alternative corruption measures: International Country Risk Guide (ICRG) corruption index, Corruption Perception Index (CPI) and Control of Corruption Index (CCI). The empirical findings have important policy implications for management and ownership structuring of airports operating in countries that suffer from higher levels of corruption.     

The influence of the operational environment on efficiency of international airports

Heterogeneity must be considered in the efficiency analysis of decision‐making units; otherwise, the results will be strongly biased. This is also valid for airport management where the operational environment heavily influences efficiency. In this paper, conditional efficiency measures are applied to airports to incorporate heterogeneity in non‐parametric frontier models which are robust for outlying observations. In particular, the influence of the operational environment on airport efficiency is examined in a sample of 141 international airports. The conclusions show that the operational environment indeed matters and that privatisation, regulation, traffic transfer and the dominant carrier have a positive effect on efficiency, whereas aeronautical revenues influence it negatively. Copyright © 2014 John Wiley & Sons, Ltd.     

Sizing parking facilities at airports

Established rules-of-thumb and industry guidelines for estimating the supply of parking at airports are based on uncertain quantities such as design year enplanements and number of airport employees, and are independent of cost. In the presence of continued uncertainty and increasing competition for limited space in and around airports, it is important that facilities are sized in relation to cost of providing and using them. A probabilistic model based on the classical “newsboy” problem is proposed to determine the optimal supply of parking in relation to expected total cost while treating demand as a random quantity. Empirical data are used to demonstrate the application of the proposed model for decision making. In addition to construction and maintenance costs, and user costs, decisions are shown to be sensitive to the level of uncertainty of design year enplanements.     

Forecasting peak passenger flows at airports

This article reviews concepts and issues relating to the definition, measurement and forecasting of peak passenger flows at airports, and outlines some recent work carried out by BAA plc, the owner and operator of several major airports in the UK.Abbreviations BHR Busy Hour Rate - SBR Standard Busy Rate - DFR Design Flow Rate     

Congestion spill effects of Heathrow and Frankfurt airports on connection traffic in European and Gulf hub airports

We develop two stage fixed-effects single-spill and double-spill models for congestion connection spills of London Heathrow and Frankfurt airports on 9 hub airports in Europe and the Gulf. Our panel data covers connection traffic from 1997 to 2013 for Heathrow and 1997 to 2011 for Frankfurt. The single-spill results support strongly that the connection spills from Heathrow’s capacity limitations do strengthen competing hub airports of major alliance groups and to a lesser degree one Gulf hub. The double-spill model for Heathrow and Frankfurt shows nearly asymmetric overall spill characteristics between the two airports. Our results underline the influence of airline network strategies on congestion spills as European airline networks are shaped by alliances and umbrella mergers. Thus, the airline network perspective in airport capacity expansion decisions needs to play a greater role, as indicated by our asymmetric results for overall spill effects between Heathrow and Frankfurt airports.     

Experience sampling in and around airports. Momentary subjective wellbeing,airports, and aviation noise in England

We explore the wellbeing of people in and around English airports using real-time data from a large spatial positioning experience sampling dataset (Mappiness). We analyze the association between subjective wellbeing reported in the moment and aviation, in terms of airport location, aircraft noise, and activities within airports. This is the first time that a large Experience Sample Method (ESM) of momentary wellbeing measurements has been used to quantify the associations between aviation and subjective wellbeing. Being within areas of high levels of aircraft noise is associated with lower levels of happiness and relaxation. Those surveyed in proximity to airports report significantly lower levels of relaxation. These findings have important implications to policy. Exploiting the panel nature of the ESM data provides the strongest causal claims to date of the negative association between aviation activities and subjective wellbeing. The Mappiness application also allows us to assess the association between airports and wellbeing on those inside them, and divide activities within airports between those who work there and those who are passing through for travel purposes, as well as the effects of aircraft noise beyond airports. This gives us a broader insight into the range of impacts, both positive and negative, that aviation has on peoples’ momentary wellbeing, which may be used to inform aviation noise mitigation and compensation policies in the future.     

Benchmarking airports with specific safety performance measures

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system.     

Performance based clustering for benchmarking of US airports

Managing service operations is gaining significant attention in both academic and practitioner circles. In this broad area, performance evaluation and process improvement of airlines and air carriers has been the focus of several studies. Although efficient airport operations are critical for improved performance of airlines and air carriers, few studies have focused on airport performance measurement. This study evaluates the operational efficiencies of 44 major US airports across 5 years using multi-criteria non-parametric models. These efficiency scores are treated by a clustering method in identifying benchmarks for improving poorly performing airports. Efficiency measures are based on four resource input measures including airport operational costs, number of airport employees, gates and runways, and five output measures including operational revenue, passenger flow, commercial and general aviation movement, and total cargo transportation. The methodology presented here can be generalized to other industries and institutions.     

How much noise reduction at airports?

Airport noise nuisance is a negative externality especially when it occurring near urban areas. Like all externalities, noise nuisance may be a reason for government intervention. When intervening, governments should set quantitative policy targets with care. In practice, this issue is generally neglected. This line of research sets the first step towards determining optimal policy targets in the case of noise nuisance near airports, more specifically in the case of Amsterdam Airport. We use hedonic pricing to establish the benefits of noise reduction. Furthermore, we develop a bottom-up cost function to analyze the costs of reducing noise for airlines. We then equate marginal costs and benefits to establish the optimal level of noise reduction, which appears to be 3 dB in the case of Amsterdam Airport. Welfare increasing measures include alternative approach procedures, regional substitution of planes within existing fleets and early depreciation of noisy planes increase welfare. Reducing the number of flights has a negative effect on net welfare.     

Revenue sharing with multiple airlines and airports

This paper investigates the effects of concession revenue sharing between an airport and its airlines. It is found that the degree of revenue sharing will be affected by how airlines’ services are related to each other (complements, independent, or substitutes). In particular, when carriers provide strongly substitutable services to each other, the airport has incentive to charge airlines, rather than to pay airlines, a share of concession revenue. In these situations, while revenue sharing improves profit, it reduces social welfare. It is further found that airport competition results in a higher degree of revenue sharing than would be had in the case of single airports. The airport–airline chains may nevertheless derive lower profits through the revenue-sharing rivalry, and the situation is similar to a Prisoners’ Dilemma. As the chains move further away from their joint profit maximum, welfare rises beyond the level achievable by single airports. The (equilibrium) revenue-sharing proportion at an airport is also shown to decrease in the number of its carriers, and to increase in the number of carriers at competing airports. Finally, the effects of a ‘pure’ sharing contract are compared to those of the two-part sharing contract. It is found that whether an airport is subject to competition is critical to the welfare consequences of alternative revenue sharing arrangements.     

Demand for rail travel to and from airports

Rail access to airports is becoming increasingly important for both train operators and the airports themselves. This paper reports analysis of inter-urban rail demand to and from Manchester and Stansted Airports and the sensitivity of this market segment to growth in air traffic and the cost and service quality of rail services. The estimated demand parameters vary in an expected manner between outward and inward air travellers as well as between airport users and general rail travellers. These parameters can be entered into the demand forecasting framework widely used in the rail industry in Great Britain to provide an appropriate means of forecasting for this otherwise neglected market segment. The novel features of this research, at least in the British context, are that it provides the first detailed analysis of aggregate rail flows to and from airports, it has disaggregated the traditional generalised time measure of rail service quality in order to estimate separate elasticities to journey time, service headway and interchange, and it has successfully explored departures from the conventional constant elasticity position.     

Incorporating negative externalities into productivity assessments of US airports

This paper analyses the efficiency of 44 US airports for the period 2005–2009. In addition to the conventional outputs (i.e., passengers, flights and cargo), we consider three undesirable externalities of airport activities: delays, noise and local air pollution. We adopt a directional distance function approach and perform a second stage analysis to investigate potential determinants of efficiency. Our base case results with only the positive outputs show that the greater the average aircraft size serving an airport and the larger the dimensions of the airport, the higher the technical efficiency. However, our results are sensitive to the inclusion of the undesirable outputs. The implications are that the inclusion of these externalities into the calculation of efficiency may impact policy decisions.     

Implementation of a thrust reverse noise detection system for airports

A thrust reverse noise detection methodology for airports is developed and tested in terms of meeting the restrictions at Madrid-Barajas airport. The detection is based on thresholds applied to the sound power level time histories estimated using a microphone array and an inverse sound propagation model. The two sound events detected are classified as landing and thrust reverse to complete the identification of thrust reverse activation. The methodology performs well especially in the detection stage because the estimation of sound power level enhances the sound events and their separation, even if landing and thrust reverse are close to each other. The implementation of the TREND tool has error rates lower than 10%.     

Quantitative analysis of passenger and baggage security screening at airports

The terrorist attacks in the United States in 2001 opened a new era in air transportation. The realization that civil aircraft can be used as powerful weapons of mass destruction by a small group of people has drastically increased the need for security screening procedures to protect civil flights. Serving as the interface between the air and land transportation modes, airports have become the main focus in the implementation of those procedures. The need to more thoroughly screen passengers and baggage, and the consequent increase in processing time, has created the need for more space for security checkpoints and baggage screening inside passenger terminal buildings—space that is costly and very difficult to find in existing buildings. This paper evaluates the impact those measures have had on the planning and operation of airport passenger terminals. Quantification of those impacts is performed with the use of discrete‐event simulation and spreadsheet models.     

The punctuality performance of aircraft rotations in a network of airports

The aim of this paper is to investigate the influence of aircraft turnaround performance at airports on the schedule punctuality of aircraft rotations in a network of airports. A mathematical model is applied, composed of two sub-models, namely the aircraft turnaround model (turnaround simulations) and the enroute model (enroute flight time simulations). A Markovian type model is featured in the aircraft turnaround model to simulate the operation of aircraft turnarounds at an airport by considering operational uncertainties and schedule punctuality variance. In addition, stochastic Monte Carlo simulations are employed to carry out stochastic sampling and simulations in both the aircraft turnaround model and the enroute model. Results of simulations show the robustness of the aircraft rotation model in capturing uncertainties from aircraft rotations. The propagation of knock-on delays in aircraft rotations is found to be significant when the short-connection-time policy is used by an airline at its hub airport. It is also found that the proper inclusion of schedule buffer time in the aircraft rotation schedule helps control the propagation of knock-on delays and, therefore, stabilize the punctuality performance of aircraft rotations.     

Dealing with the efficient allocation of scarce resources at congested airports

The existing slot allocation mechanism, based on the International Air Transport Association (IATA) system and its complementary version of the European Union (EU) regulation, produces rather poor capacity allocation outcomes for congested EU airports since it fails to properly match slots requested with slots allocated to airlines. Inefficiencies during the initial allocation are mainly due to the problem complexity in conjunction to limited decision support available to slot coordinators. On the other hand, substantial inefficiencies give rise to severe slot misuse and unreasonably low utilisation of airport resources running already into scarcity. The objective of this paper is to develop an optimisation-based model implementing the existing EU/IATA rules, operational constraints, and coordination procedures with the ultimate objective to better accommodate airlines’ preferences at coordinated airports through the minimisation of the difference between the requested and the allocated slot times to airlines. The results of the model are assessed and compared vis-à-vis the allocation outcome produced according to current slot coordination practice in three regional Greek airports. The proposed model produces very promising results and demonstrates that there is large room for improvement of the efficiency of the current allocation outcome in a range between 14% and 95%. The discussion of the model results is complemented by a sensitivity analysis highlighting the importance of declared capacity and the magnitude of its influence on slot allocation efficiency.     

A model to forecast aircraft operations at general aviation airports

Forecasting the demand for aviation activities is an important task in economic planning. Traditionally, forecasting the demand for general aviation airports has been done using trend and ratio analyses. Both techniques ignore the changes in many external factors that influence aviation activities. This paper develops an econometric model that relates the number of aircraft operations at a general aviation airport to some socioeconomic characteristics and supply variables. The model was estimated using data for 82 airports in the state of Georgia. The results of estimating the model suggest that the demand is inelastic with respect to total employment. The results also show that presence of aviation related services such as avionics, charter flights, rental, repair and crop dusting are important factors in determining aviation activities. The demand seems to be responsive to the location of the county as a tourist/recreational destination.