Airport Performance Measurement Research Articles

Beyond throughput: Incorporating air transport network topology in airport performance measurement

Airport ranking studies have traditionally focused on throughput criteria such as passenger and cargo volume, overlooking the importance of air transport network topology in assessing airport performance. In this work, we propose a novel approach that incorporates both traditional throughput criteria and air transport network topology criteria, such as degree centrality (direct connections) and betweenness centrality (transit connections). To ensure unbiased criteria weight estimation, we combine objective and subjective weights using Bayes’ theorem. Using our approach, we develop a Global Airport Performance Score (GAPS) to measure the performance of airports. We then apply this methodology to rank the top 50 international commercial service airports in 2019, published by Airports Council International, to validate our proposed methodology. Furthermore, we conduct a sensitivity analysis to demonstrate the robustness of our method. The results reveal valuable insights for benchmarking airports in the worldwide air transportation network. By considering both traditional throughput criteria and air transport network topology, our approach can help airport operators, policymakers, and other stakeholders make more informed decisions about airport investments and improvements.

Study of Airport Service Quality and Profitability in Indonesia

This study was about the Airport Service Quality (ASQ) measurement and its relation to profitability in the airport industry. The main purpose of this study was to develop an understanding of the ASQ measurement in Airports by investigating the relationships of service quality in terms of creating purchase intentions. In specific to ASQ, the surveys have been systematically carried out by many airport operators all over the world. ASQ has 8 components: access; check-in; passport/personal ID control; security; finding your way; airport facilities; airport environment; and arrival services. This is different from PZB’s (1985) Service Quality dimensions. This suggests that an effective process of measuring and analyzing passenger perceptions of ASQ is not easily achieved. These concerns are certainly relevant to avoid misinterpreting passenger perceptions. The measurement model should be considered for a multidimensional approach in the context of airport performance measurement regarding service quality.The study, however, included the perceptions of both international passengers and domestic concerning the current service levels, more specific was using the measurement model of Cronin and Taylor (1992). Cronin and Taylor (1992) say that perception alone is enough and even better than other models i.e, PZB (1988) model. This study analyzes whether passengers may stay longer in the airport, recommend the airport to other people or pay higher tax if they are satisfied with the service offers by airport. This also included an assessment the ability ASQ to explain the variation in repeat purchase intention including interaction among variables. The results of this study show ASQ has a moderately low effect of purchasing intentions.

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.

Performance measurement practices in airports: Multidimensionality and utilization patterns

The purpose of this paper is to assess the current profile of airport executives concerning key aspects of their performance measurement practices. The results suggest that these practices still emphasize operational issues, such as safety, economic-financial, and service quality. In contrast, measuring performance according to a broader perspective of the airport business, including competition, long-term economic results, and the environmental and social outcomes of the airport activities, was not evident. This study has significant contributions for performance measurement and management in the airport context. Overall, the findings stress the need for broadening the approach to airport performance measurement as a business service organization, which may require adjustments in the current management information systems. Practical implications for airport management are presented.

Does Operational Efficiency Depend on the Airport’s Size?

This paper presents operational performance analysis using DEA which is short for data envelopment analysis. The study focuses on 9 South African commercial airports. These were divided into different hub groups according to their size. Few airports utilize any type of operational performance indicators for performance evaluation. Operational information such as aircrafts’ landing and take-off movements are some of the important data that can be used. Airport performance measures are necessary for stakeholders such as passengers and day-to-day business operations. The study was limited to only two inputs and two outputs. Outputs being passenger throughput and total air traffic movements. The inputs being hourly runway capacity and public parking bays. After DEA was used to evaluate the efficiency of the airports, statistical analysis was done to identify those airports that dominate others in terms of efficiency.

Improving airport services using sentiment analysis of the websites

Measuring the level of customer satisfaction of airport passengers provides a valuable feedback to airport managers. In fact, researchers and practitioners alike have recognized that measuring airport performance through purely operational approaches is not sufficient. In order to overcome such weakness a growing literature on airport performance measurement has focused its attention on models assessing passengers' needs and their perception of the airport service quality. The developed models vary according to the type of decisions supported, evaluation perspective, type of measurements, and evaluation approach used. Departing from the above literature, the present paper explores the possibility offer by data collected in the blogs and by the text extracting software for assessing the level of services perceived by airport customers. The paper identifies the strengths, weakness and synergies of the proposed approach in assessing users' perceptions of the quality of airport services.

Measuring airport service quality: A multidimensional approach

Currently, airports are expected to be operated as self-sufficient service organizations providing efficient and high-quality services to a variety of customers. In this context, improving airport service quality (ASQ) has become paramount. However, due to the complexity of the airport service environment, an effective process of measuring and analyzing passenger perceptions of ASQ is not easily achieved. Generic scales for perceived service quality might not cover some particularities of the passenger–airport interaction. Furthermore, while some measurement practices have been developed within the airport industry, there has been only limited consideration for validity and reliability. These concerns are certainly relevant to avoid misinterpreting passenger perceptions. In view of these concerns, this paper has a twofold objective. First, to fit a measurement model for perceived ASQ built on typical service measures within the airport industry. Second, to test for the model's equivalence across groups of passengers. Sample data from an extensive survey applied at a major Brazilian airport was used for confirmatory factor analysis. The results suggested that a six-factor structure provides a meaningful multi-item measurement model for perceived ASQ. The model was validated for international and domestic departing passengers with respect to its factorial structure and metric invariance. The proposed measurement model could be considered an alternative for a multidimensional approach in the context of airport performance measurement regarding service quality. Finally, the findings from this research might contribute to the discussion on passenger perceptions of ASQ, particularly concerning its multidimensionality and the need to review current practices for ASQ analysis.

A decision support system for total airport operations management and planning

SUMMARYThe airport planning and decision making process exhibits various trade‐offs and complications due to the large number of stakeholders having different, and sometimes conflicting, objectives regarding the assessment of airport performance. As a result, the airport performance assessment necessitates the use of advanced modelling capabilities and decision support systems or tools in order to capture the multifaceted aspects, interests and measures of airport performance like capacity, delays, safety, security, noise and cost‐effectiveness. Presently, airport decision makers lack decision support tools able to provide an integrated view of total airport (both airside and landside) operations and analyse at a reasonable effort and decision‐oriented manner the various trade‐offs involved among different airport performance measures. The objective of this paper is twofold: (i) to describe the decision‐oriented modelling framework and development process of a decision support system for total airport operations management and planning, and (ii) to demonstrate the decision support capabilities and basic modelling functionalities of the proposed system. Copyright © 2010 John Wiley & Sons, Ltd.

Terminal chaos: why U.S. air travel is broken and how to fix it

Introduction: Frequent Flying, Frequent Frustration Passengers Who Act Like Sheep Will Be Treated Like Sheep A Typical Flight and Why It's Often Delayed Destination Chaos: How We Arrived and Who Were the Pilots Why Don't the Airlines Just Fix This Problem? The Anatomy of Winners and Losers The Flight From Chaos: Expansion, Modernization, and the 30 per cent Solution Bibliography Appendix A: Airline and Airport Codes Appendix B: 18 Major U.S. Airport Performance Measures Appendix C: The Mathematics of Less Than 100 per cent Slot Utilization Appendix D: Market-Based Slot Allocations at Congested Airports Appendix E: The European Passenger's Bill of Rights Appendix F: Travel Tips for Road Warriors Appendix G: Trade-Off Between Passenger Delay Costs and Lost Consumer Surplus.

Advanced Modeling Capabilities for Airport Performance Assessment and Capacity Management

Airport decision makers face frequently complex decisions related to airport planning, design, and operations. These decisions are highly complicated since they involve a variety of entities processed through the system, a number of different airport elements, and a large variety of airport performance measures such as capacity, delays, safety, security, noise, and cost-effectiveness. Existing airport modeling capabilities suffer from (a) fragmentation between the various airport elements, entities, and their operations; (b) the isolated manner in which the airport performance measures are assessed and modeled; and (c) the lack of user-friendly modeling capabilities and decision support systems adopting a problem-oriented approach for airport decision making and planning. Advanced airport modeling capabilities should be deployed to integrate domain knowledge with tool expertise in assisting airport decision makers to answer frequently arising airport planning questions in an integrated, user-friendly, and problem-oriented environment. The operational concept for an integrated, problem-oriented modeling approach for total airport performance analysis is introduced, the development of a decision support system for airport performance assessment and capacity management is described, and the modeling and decision support capabilities of the system are demonstrated.

Benchmarking airport reconstruction projects

The impact of redevelopment and expansion of airport operations has not received much attention in the literature. Data were collected for 22 North American airports, 26 airport projects, and 107 individual operational years (airport years) with at least 3.5 million passengers annually. Each airport undertook at least one brownfield passenger terminal project between 1991 and 2001. The study shows that some factors, such as traffic volume, air traffic movements, and cargo, may indicate impacts of airport redevelopment. It was also found that the strategic use of space is critical to operational efficiency, especially with the full range of non-aeronautical services that can be offered at airports. The cost of space may be higher, but it tended to improve overall efficiency. Reconstruction projects that were evaluated as successful tended to show operational recovery within 2 years of construction completion; this result was consistent through a wide range of project sizes, traffic levels, and services.Key words: airport terminal reconstruction, benchmarking, reconstruction impacts, airport performance measures, data envelopment analysis.

A comparison of alternative airport performance measurement techniques: A European case study

The aim of this paper is to assess the comparative performance of European airports by using a mixture of different approaches that are available to measure efficiency and productivity. The paper adopts a financial focus and considers partial factor productivity, financial ratio analysis and data envelopment analysis. A sample of 31 individual European airports and four European airport systems is used for the ten-year period beginning in 1990. This sample includes airports of varying sizes, in public, mixed public-private and fully private ownership. The research reveals differences in financial performance between the airports in terms of geographical location, airport size and ownership status.

Aviation benchmarking: issues and industry insights from benchmarking results

Purpose – This paper aims to describe the processes used to ensure that the comparisons made between airport and airline performance are as meaningful as possible, and to highlight a number of issues which need to be considered when making performance comparisons in aviation. Design/methodology/approach – Evidence was gathered from an international data sample of airports and airlines. Operational and financial data was derived from published reports. Findings – The research illustrates the scale of differences in airport performance levels, and it also highlights the considerable difference in performance levels between airports and airlines. It is clear that many factors can impact on an airport's ability to optimise its performance, and on its relative level of performance when compared to its peers. Practical implications – The research highlights and demonstrates the need for a degree of understanding of contextual factors when comparing airport performance measures with each other and when comparing airline performance. Originality/value – Insight into the process by which airport and airline performance measurements can be compared with each other.

Aviation benchmarking

Purpose – This paper aims to describe the processes used to ensure that the comparisons made between airport and airline performance are as meaningful as possible, and to highlight a number of issues which need to be considered when making performance comparisons in aviation. Design/methodology/approach – Evidence was gathered from an international data sample of airports and airlines. Operational and financial data was derived from published reports. Findings – The research illustrates the scale of differences in airport performance levels, and it also highlights the considerable difference in performance levels between airports and airlines. It is clear that many factors can impact on an airport's ability to optimise its performance, and on its relative level of performance when compared to its peers. Practical implications – The research highlights and demonstrates the need for a degree of understanding of contextual factors when comparing airport performance measures with each other and when comparing airline performance. Originality/value – Insight into the process by which airport and airline performance measurements can be compared with each other.

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.

Performance measurement: a review of airports

Abstract This paper considers the past, present and future of airport performance measurement. The authors examine the changing nature of the performance measurement of airports. Airport performance measures are important for day to day business and operational management, regulatory bodies, Government and other stakeholders such as passengers and airlines. Measurement systems have been forced to develop in response to changing organisational contexts. With pressures for change coming from changing ownership patterns, an increased commercial focus, regulation, rapid passenger growth, increased concern for the natural environment and technical innovation, the experiences shared and lessons to be learnt highlighted in this paper will be of interest to both academics and practitioners.

Performance Measurement in Airports

This article examines airport performance measurement systems under varying ownership patterns in Europe andthe United States, bringing together a rich picture of different practices. The need for airports to give greater emphasis to their operational context to evaluate their performance objectively is emphasized. Many performance measures currently in use are output variables, usually quantitative andbasedon what is easy to measure rather than what is important to measure. The dysfunctional effects of measurement systems are considered, including the problems of discrepancies in the definition of key variables and of attempts to achieve direct comparability between airports.

Traditional Airport Performance Indicators: A Critical Perspective

Airport managers require effective performance measures to enable them to plan and manage within the context of rapid passenger growth and the trend toward an expansion of commercial activities. Airport performance measurement in various ownership patterns from Europe and the United States is reviewed, bringing together a rich picture of different practices. The need to be aware of contingent circumstances to evaluate airport performance objectively is emphasized. Many measures currently in use are output variables and are usually quantitative and based on what is easy to measure instead of what is important to measure. The problems of discrepancies in the definition of key variables and of attempts to achieve direct comparability between airports are examined. Consideration is given to the dysfunctional effects of measurement systems and how they can be adapted to encourage innovation and organizational learning through such techniques as best-practice benchmarking. Airport planners, managers, and academics who have an interest in performance measurement and who wish to question the role of traditional measures will be interested in the discussion. Lessons from European experience in a postprivatization environment are considered. The research recommends the adoption of a performance measurement system for airports that examines processes as well as results and that considers antecedent variables as well as outcome variables. The conclusions indicate how airport planners and managers can gain new insight into the underlying processes behind quantitative indicators and how an understanding of these processes can stimulate organizational learning and innovation.

Introduction Airport performance measurement and airport pricing

Introduction Airport performance measurement and airport pricing