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.     

Comparative performance analysis of European airports by means of extended data envelopment analysis

Data envelopment analysis (DEA) has become an established approach for analyzing and comparing efficiency results of corporate organizations or economic agents. It has also found wide application in comparative studies on airport efficiency. The standard DEA approach to comparative airport efficiency analysis has two feeble elements, viz. a methodological weakness and a substantive weakness. The methodological weakness originates from the choice of uniform efficiency improvement assessment, whereas the substantive weakness in airport efficiency analysis concerns the insufficient attention for short‐term and long‐term adjustment possibilities in the production inputs determining airport efficiency. The present paper aims to address both flaws by doing the following: (i) designing a data‐instigated distance friction minimization (DFM) model as a generalization of the standard Banker–Charnes–Cooper model with a view to the development of a more appropriate efficiency improvement projection model in the Banker–Charnes–Cooper version of DEA and (ii) including as factor inputs also lumpy or rigid factors that are characterized by short‐term indivisibility or inertia (and hence not suitable for short‐run flexible adjustment in new efficiency stages), as is the case for runways of airports. This so‐called fixed factor case will be included in the DFM submodel of the DEA. This extended DEA—with a DFM and a fixed factor component—will be applied to a comparative performance analysis of several major airports in Europe. Finally, our comparative study on airport efficiency analysis will be extended by incorporating also the added value of the presence of shopping facilities at airports for their relative economic performance. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluating the operational performance of airside and landside at Chinese airports with novel inputs

ABSTRACT

This paper evaluates the operational performance of airside and landside at Chinese airports with two novel inputs. Furthermore, the airport landside operation is decomposed into passenger-terminal operations and cargo-warehouse operations. One novel input is the capability of the runway system which is introduced into airside performance evaluation. The other novel input is cargo warehousing which is introduced into landside performance evaluation. To address multiple optimal solutions when estimating Returns to Scale in Data Envelopment Analysis, we adopted the Zhu and Shen method. This empirical study shows that neither the number of runways nor total runway length is a genuine index of runway system capability in the evaluation of airside performance. Only four airports achieved full efficiency in all eight measures while eight airports did not achieve any full efficiency. In addition, one airport did not perform well in the benchmark analysis.     

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.     

Joint impact of competition,ownership form and economic regulation on airport performance and pricing

The combined impact of ownership form, economic regulation and competition on airport performance is analyzed using data envelopment analysis to measure cost efficiency in the first stage and regression analysis to measure the impact of the environment in the second stage. The empirical results of an analysis of European and Australian airports over a 10 year timeframe reveal that under relatively non-competitive conditions, public airports operate less cost efficiently than fully private airports. Irrespective of ownership form, regulation is necessary to emulate competitive forces thus pushing airport management towards cost efficiency and reasonable pricing policies. Under potential regional or hub competition, economic regulation inhibits airports of any ownership form from operating and pricing efficiently. Although public and fully private airports operate equally efficiently in a competitive setting, private airports still set higher aeronautical charges. Furthermore, mixed ownership forms with a majority public holding are neither cost efficient nor low price, irrespective of the level of competition.     

On the relationship between airport pricing models

Airport pricing papers can be divided into two approaches. In the traditional approach the demand for airport services depends on airport charges and on congestion costs of both passengers and airlines; the airline market is not formally modeled. In the vertical-structure approach instead, airports provide an input for an airline oligopoly and it is the equilibrium of this downstream market which determines the airports’ demand. We prove, analytically, that the traditional approach to airport pricing is valid if air carriers have no market power, i.e. airlines are atomistic or they behave as price takers (perfect competition) and have constant marginal operational costs. When carriers have market power, this approach may result in a surplus measure that falls short of giving a true measure of social surplus. Furthermore, its use prescribes a traffic level that is, for given capacity, smaller than the socially optimal level. When carriers have market power and consequently both airports and airlines behave strategically, a vertical-structure approach appears a more reasonable approach to airport pricing issues.     

Apron capacity at hub airports—the impact of wave‐system structure

At hub airports, dominant airlines/alliance coordinate their flights in time with the aim of increasing the number (and quality) of connections, thus producing a wave‐system in traffic schedules. This paper addresses the impact of concentrating aircraft into waves on airport apron capacity. Existing models for apron capacity estimation are based on the number of stands, stand occupancy time, and demand structure, differing between representative groups of aircraft served at an airport. Criteria for aircraft grouping are aircraft type and/or airline and/or type of service (domestic, international, etc.). Modified deterministic analytical models proposed in this paper also take into account the wave‐system parameters, as well as runway capacity. They include the impact of these parameters on the number of flights in wave, stand occupancy time, and consequently apron capacity. Numerical examples illustrate the difference between apron capacity for an origin–destination airport and a hub airport, under the same conditions; utilization of the theoretical apron capacity at a hub airport, given the wave‐system structure; and utilization of the apron capacity at a hub airport when point‐to‐point traffic is allowed to use idle stands. Furthermore, the influence of different assignment strategies for aircraft stands in the case of hub airports is also discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

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 multi-criteria evaluation of solutions and alternatives for matching capacity to demand in an airport system: the case of London

This paper applies multi-criteria decision-making (MCDM) methods to the evaluation of solutions and alternatives for matching airport system airside (runway) capacity to demand. For such a purpose, ‘building a new runway’ is considered as the solution and candidate airports of the system as alternatives for implementing the solution. The alternative airports are characterized by their physical/spatial, operational, economic, environmental, and social performance represented by corresponding indicator systems which, after being defined and estimated under given operating scenarios, are used as evaluation attributes/criteria by the selected MCDM methods. Two MCDM methods – Simple Additive Weighting and Technique for Order of Preference by Similarity to Ideal Solution – are applied to the case of the London airport system to rank and select the preferred alternative from three candidate airports – Heathrow, Gatwick, and Stansted – for where a new runway could be built.     

The impacts of changing flight demands and throughput performance on airport delays through the Great Recession

Several significant events between 2007 and 2009 impacted flight demands and the abilities of the three major New York area airports to handle demand. This paper assesses the results of applying a probabilistic simulation method – which isolates the individual contributions of changes in flight demand and changes in airport throughput performance to changes in flight delays – to diagnose how these different events may have caused operational changes at these airports, and in turn, how the results may be used to inform policies for appropriate countermeasures. The analysis revealed two key observations. Firstly, certain patterns in throughput performance shifts caused the most significant delays, and were more likely to have been caused by controller staffing issues rather than caps. Secondly, relatively constant average delays from one year to the next may result from significant demand drops accompanied by large throughput performance degradations at an airport. This suggests that not only operational limitations on capacity encourage airlines to reduce schedules, but that changed demands can also impact throughput performance. Overall, the analysis indicates that caps may not have provided their fully intended delay benefits. Although they successfully reduced overall flight demands at LGA and JFK, they also directly limited throughput performance at critical times, in turn limiting delay benefits. In addition, demands at the busiest times of the day appear to be relatively inelastic to these operational limitations, insofar as demand profiles at EWR and JFK remained “peaky” in 2008 and 2009. Also, the recession was largely responsible for reducing demands at the airports in 2009, but the delay benefits of this were dampened by a corresponding throughput performance degradation. Based on the above observations, a more direct demand management policy combined with policies that focus on maintaining high staffing capabilities at critical times of the day may be considered, to reduce the likelihood of major queue formation on days that do experience sustained demands. The results also suggest that a more flexible caps system, particularly during times of heavy queues, could be explored. Although airport practitioners have keen understandings of how their airports operate, without the support of quantitative analysis tools, it can be more difficult to argue the need for appropriate countermeasures. An analysis such as the one presented here can provide the detailed quantitative substantiation required to build cases for these targeted policy directives and infrastructure investments.     

Airport privatization in congested hub–spoke networks

This paper investigates the airport privatization issue. One congested hub and two linked local airports serve symmetric hub carriers. Passengers valuate the congestion delay cost and benefit from greater frequencies. The government considers privatizing either the hub or local airports. We find that in each privatizing scenario, welfare-maximizing public airport(s) set a charge below their operating costs in order to fully coordinate the high charge of privatized airport(s). If this fiscal deficit is not allowed, each scenario causes distortion. Interestingly, the distortion—and hence welfare losses—in privatizing a hub are smaller (larger) than those in privatizing both local airports when both passengers’ valuations are small (large); this is exactly the case when privatized local airports are strategic substitutes (complements). We also surprisingly find that retaining the hub airport as public and privatizing one or both local airports achieves the same market outcomes. We further find that if all airports are privatized, welfare becomes worse than the other scenarios; the hub airport charges lower (higher) prices than local airports when both local airports are strategic substitutes (complements).     

A generic system dynamics based tool for airport terminal performance analysis

Decision making for airport terminal planning, design and operations is a challenging task, since it should consider significant trade-offs regarding alternative operational policies and physical terminal layout concepts. Existing models and tools for airport terminal analysis and performance assessment are too specific (i.e., models of specific airports) or general simulation platforms that require substantial airport modelling effort. In addition, they are either too detailed (i.e., microscopic) or too aggregate (i.e., macroscopic), affecting, respectively, the flexibility of the model to adapt to any airport and the level of accuracy of the results obtained. Therefore, there is a need for a generic decision support tool that will incorporate sufficient level of detail for assessing airport terminal performance. To bridge this gap, a mesoscopic model for airport terminal performance analysis has been developed, that strikes a balance between flexibility and realistic results, adopting a system dynamics approach. The proposed model has a modular architecture and interface, enabling quick and easy model building and providing the capability of being adaptable to the configuration and operational characteristics of a wide spectrum of airport terminals in a user-friendly manner. The capabilities of the proposed model have been demonstrated through the analysis of the Athens International Airport terminal.     

Airport–Airline interaction: some food for thought

Abstract

We provide an interpretive analysis of vertical relations between airports and carriers, while assessing the way in which deregulation of the airline market and the privatization of airports have created incentives for airport–airline interaction. In particular, if the vertical structure approach has become the standard approach in air transport research, we add to the literature by discussing three issues that we believe need further understanding. The three issues that we think should be the focus of future research on airport–airline interaction are (i) incomplete contracts and asymmetric information structure; (ii) upstream horizontal complementarities; and (iii) airports as two-sided platforms.     

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.     

Modeling taxi drivers’ decisions for improving airport ground access: John F. Kennedy airport case

Taxi service is an important component of airport ground access, which affects the economic competitiveness of an airport and its potential positive impact on the surrounding region. Airports across the globe experience both taxi shortages and excesses due to various factors such as the airport’s proximity to the city center, timing and frequency of flights, and the fare structure. Since taxi drivers are independent entities whose decisions affect the taxi supply at airports, it is important to understand taxi drivers’ decision mechanisms in order to suggest policies and to maintain taxi demand and supply equilibrium at the airports. In this paper, New York City (NYC) taxi drivers’ decisions about airport pick-ups or cruising for customers at the end of each trip is modeled using logistic regression based on a large taxi GPS dataset. The presented approach helps to quantify the potential impacts of parameters and to rank their influence for policy recommendations. The results reveal that spatial variables (mainly related to proximity) have the highest impact on taxi drivers’ airport pickup decisions, followed by temporal, environmental and driver-shift related variables. Along with supplementary information from unstructured taxi driver interviews, the model results are used to suggest policies for the improvement of John F. Kennedy (JFK) airport’s ground access and passenger satisfaction, i.e. the implementation of taxi driver frequent airport server punch cards and a time-specific ride share program.     

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.     

Preference-based evolutionary algorithm for airport surface operations

In addition to time efficiency, minimisation of fuel consumption and related emissions has started to be considered by research on optimisation of airport surface operations as more airports face severe congestion and tightening environmental regulations. Objectives are related to economic cost which can be used as preferences to search for a region of cost efficient and Pareto optimal solutions. A multi-objective evolutionary optimisation framework with preferences is proposed in this paper to solve a complex optimisation problem integrating runway scheduling and airport ground movement problem. The evolutionary search algorithm uses modified crowding distance in the replacement procedure to take into account cost of delay and fuel price. Furthermore, uncertainty inherent in prices is reflected by expressing preferences as an interval. Preference information is used to control the extent of region of interest, which has a beneficial effect on algorithm performance. As a result, the search algorithm can achieve faster convergence and potentially better solutions. A filtering procedure is further proposed to select an evenly distributed subset of Pareto optimal solutions in order to reduce its size and help the decision maker. The computational results with data from major international hub airports show the efficiency of the proposed approach.     

A time series analysis of the dynamic competition between major cargo airports

This paper models the dynamic competition between major cargo airports from the time series perspectives of long-term equilibriums and short-run dynamics. We first apply a unit root test to examine the stationarity of cargo throughput data. Airports are then analysed pairwise by region to test their equilibrium relationships through cointegration analysis. Meanwhile, we also utilise the error correction model to investigate the short-run impacts of cargo traffic between the airports. According to our findings, there are four positive long-term equilibriums, one positive short-run dynamic and three negative short-run dynamics in Asia. In addition, the airports in North America are found to have four positive long-term equilibriums, three negative long-run equilibriums, seven positive short-run impacts and three negative short-run impacts. As these dynamic relationships imply competition between cargo airports, our study can provide airport authorities with the reference to develop their long-term strategies and short-run operational plans.     

基于功能定位的国际航空枢纽评价

针对我国国际枢纽机场未按照设计之初功能定位发展的现状,运用AHP法构建国际枢纽机场综合评价指标体系,将国际航空运输规模指标、国际节点网络连通度指标、枢纽功能指标、综合交通指标纳入体系当中。首先对国内外大型国际枢纽机场进行评价,其次对我国机场布局规划中的10个国际枢纽机场进行评价。结果表明我国国际枢纽机场国际业务发展、航空枢纽建设与国外对标机场有一定差距,与自身战略规划有所偏差,针对薄弱指标项基于自身优势给出发展建议。最后基于一市两场与机场群的视角,分析了如何根据自身功能定位进行协同发展问题。     

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.