IDEAS home Printed from https://ideas.repec.org/a/sgh/gosnar/y2021i4p23-53.html
   My bibliography  Save this article

Performance Evaluation of Airports During the COVID-19 Pandemic

Author

Listed:
  • Yusuf Ersoy

Abstract

Globalisation, international trade, tourism, and economic and technological advances have contributed to the development of the aviation industry. In a globally competitive environment, airports need to use their resources efficiently and evaluate their performance to compete with their rivals. Data Envelopment Analysis (DEA) is a widely used method in the performance evaluation of airports. This study was aimed to measure the performance and ranking of selected major international airports in 2019 and the first quarter of 2020 using the DEA method, the Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) method, and the Evaluation Based on Distance from Average Solution (EDAS) method. Efficiency analysis has been carried out using CCR-DEA models. Later, performance evaluation of the alternatives was made according to the TOPSIS and EDAS methods. In this study, the ranking of the airports has been compiled according to the results of the DEA, TOPSIS and EDAS methods. The study found that the use of the DEA method together with Multi-Criteria Decision-Making (MCDM) methods such as TOPSIS and EDAS for the performance evaluation of airports allows a full and clear ranking of decision-making units (DMUs).

Suggested Citation

  • Yusuf Ersoy, 2021. "Performance Evaluation of Airports During the COVID-19 Pandemic," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 4, pages 23-53.
  • Handle: RePEc:sgh:gosnar:y:2021:i:4:p:23-53
    as

    Download full text from publisher

    File URL: https://gnpje.sgh.waw.pl/pdf-143335-71076
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Airport performance; COVID-19 pandemic; DEA; EDAS; TOPSIS;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sgh:gosnar:y:2021:i:4:p:23-53. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Grzegorz Konat (email available below). General contact details of provider: https://edirc.repec.org/data/sgwawpl.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.