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.     

A multiple criteria approach to two-stage data envelopment analysis

Two-stage data envelopment analysis (DEA) models are commonly used in the evaluation and benchmarking of sustainable operations and processes across multiple research fields. To date, however, little attention has been given to the unrealistic weight distribution and weak discrimination power in the modeling and evaluation of the two-stage sustainable operations when using two-stage DEA models. In order to overcome this methodological weakness, we use the multiple criteria DEA (MCDEA) approach in the evaluation of the two-stage processes. The outcome is a multiple criteria two-stage DEA model which yields more realistic weights for the inputs and outputs and thus has better discrimination power than traditional two-stage DEA models. The developed model is tested and validated by assessing the sustainable design performances of a sample of car product designs.     

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.     

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).     

Including local air pollution in airport efficiency assessment: A hyperbolic-stochastic approach

We examine data from Italian airports covering 2005–2008 to include local environmental effects in airport efficiency assessment. We consider both desirable outputs such as aircraft, passengers, and freight movements and some undesirable outputs of airport operations associated with local air pollution. We estimate both a classical distance function with no undesirable output, and a hyperbolic distance function. By comparing the estimated efficiency scores with these two frontiers we show that airport efficiency increases when local air pollution is included in the analysis. Moreover, we show a fleet-mix effect because airports with similar aircraft movements exhibit large variations in the amount of pollution per flight. Last, we find that there is complementarity between desirable and undesirable output: a 1% decrease in pollution has an opportunity cost of a 0.67% reduction in both passenger and freight traffic.     

Efficient use of airport capacity

The capacity of 35 Brazilian domestic airports was analyzed with a view to determining which of them were efficient in terms of the number of passengers processed. Data Envelopment Analysis (DEA) methodology was employed to construct the efficient frontier for the sample, to reflect which of the airports used airport resources efficiently and which offered surplus in these same facilities, and in what proportion. On the basis of passenger demand forecasts, it was possible to determine, for each airport, the periods when capacity expansions would become necessary to maintain services at standards currently perceived by passengers.     

A slacks-based network DEA efficiency analysis of European airlines

Conventional data envelopment analysis (DEA) models consider a system as a single-process ‘black box’. There are, however, DEA approaches that consider a system as composed of distinct processes or stages, each one with its own inputs and outputs and with intermediate flows among the stages. In this paper, a network DEA approach to airline efficiency assessment is presented. One conclusion of the study is that the network DEA approach has more discriminative power than the single-process DEA approach and that the computed targets, efficiency scores and rankings are more valid. This is because network DEA allows for a more fine-grained analysis that leads to a more realistic estimation of the overall system production possibility set than the one assumed by conventional DEA. In other words, compared with network DEA the conventional, single-process DEA represents an aggregated analysis that merges all system processes with their inputs and outputs and ignores their internal flows. The main drawbacks are the need for more detailed data (i.e. at the process level) and the greater complexity of the resulting models, especially if there are inputs or outputs that are shared among the processes.     

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.     

Using DEA models to jointly estimate service quality perception and profitability – Evidence from international airports

With increasing competition between airports and a growing share of non-aeronautical revenues, particularly at large international hubs, perceived quality and consumer satisfaction have not only become a key focus of management but potentially the most important tool to achieve or maintain a competitive advantage. However, in the long run stakeholders aim for profit maximisation and it has been shown for other parts of the aviation supply chain that quality does significantly impact on profitability. In this paper we aim to investigate whether perceived airport quality has an impact on airport profit margins. We further apply two-stage Data Envelopment Analysis (DEA) models to estimate a single efficiency measure that combines the potentially conflicting indicators of perceived service quality and profitability for the airport context. We also identify determinants of the jointly estimated single quality/profitability measure.     

Efficiency in Asian railways: a comparison between data envelopment analysis approaches

Performance analysis has become a vital part of the management practices in the logistics infrastructure. Although there are numerous applications using Data Envelopment Analysis (DEA) models to estimate efficiency in ports and airports, research on railway efficiency remains scarce. Most of the efficiency studies of railways assume that inputs and outputs are known with absolute precision. Here, we compare Stochastic-DEA and Fuzzy-DEA models to assess, respectively, how the underlying randomness and fuzziness impact efficiency levels in railway operations in six different Asian countries: Japan, Thailand, Vietnam, Malaysia, Myanmar, and Indonesia. Findings reveal that conclusions with respect to the ranking of these railways may vary substantially depending upon the type of model chosen, although efficiency scores are similar to some extent when compared within the ambits of Stochastic-DEA and Fuzzy-DEA models. Additionally, modeling choices on fuzziness, rather than randomness, appear to be the most critical source for variations in efficiency rankings.     

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.     

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.     

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.     

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.     

Investigation of environmental justice analysis in airport planning practice from 2000 to 2010

Municipal airport owners and the Federal Aviation Administration (FAA) regularly evaluate capacity and demand to decide if and when airports need more infrastructure. New infrastructure can alter the profile of noise, emissions, and land use, which may affect the quality of life for airport-adjacent communities. When the FAA and airport owners initiate infrastructure expansion, they must conduct environmental justice analysis to measure the distribution of negative externalities on nearby communities. This research investigates the environmental justice methodologies and narratives reported in planning documents for nineteen airport capacity expansions planned or deployed from 2000 to 2010 in the United States. The mixed-methods approach analyzes airport operations data, spatial demographic data, and planning artifacts to determine whether the environmental justice analyses were robust. This research proposes alternative metrics, the ‘Risk of disproportionate impact’ and ‘Capacity strain’, to further contextualize the presence of protected population groups alongside capacity needs. The main finding of the study is that the planning documents did not consistently detect environmental justice impacts, nor did they consistently confer importance to those impacts when high proportions of protected populations were detected. As a result, the social costs of collective airport expansion are unclear and likely underestimated. This study identifies two limitations that undermined the environmental justice analysis throughout the airport sample: (1) inconsistent methodological choices impeded the detection of impacts and, (2) narrative interpretations tended to ‘null’ the finding even when impacts were detected.     

Managerial efficiency of Brazilian airports

The efficiency of 35 Brazilian domestic airports was discussed with a view to identifying avenues to improvement in two dimensions. The first of these is improved management, which shows in the airport’s ability to generate financial returns. The second is the physical dimension, which shows the level of utilization of airport infrastructure. The data envelopment analysis methodology was used to measure distance from the airport efficient frontier and to enable avenues to managerial improvement to be identified.     

Additive models for network data envelopment analysis in the presence of shared resources

This paper studies the problem of evaluating the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a large decision-making unit (DMU). The paper develops a data envelopment analysis (DEA) approach for measuring the efficiency of decision processes which can be divided into two stages. In these processes the first stage uses its own inputs to generate outputs which a part of these outputs become the inputs to the second stage. Moreover, DMUs use shared input sources in both operation stages. This paper provides a set of additive models which measure the performance of two-stage network DEA processes with shared inputs. Numerical examples show the applicability of the approach.     

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.     

Sensitivity of prices to demand shocks: A natural experiment in the San Francisco Bay Area

We analyze the impact of a freeway interchange collapse in the San Francisco Bay Area on the difference in airfare quotes for travel into the area’s main airports. The incident temporarily made Oakland airport a less attractive choice for traveling to San Francisco, so we hypothesize that fares for travel into Oakland will be relatively lower while the freeway interchange was out of service. We test our contention using a sample of fare quotes collected on-line, and find the expected effect of a magnitude of 6–7%. Our results imply the following important conclusions. First, the demand-side shock was well absorbed by the supply side. Second, adjustment of prices and return to the status quo once the shock vanished was swift.