Performance Evaluation of Airports During the COVID-19 Pandemic

Y. Ersoy
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引用次数: 4

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).
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COVID-19大流行期间机场性能评估
全球化、国际贸易、旅游业以及经济和技术的进步促进了航空业的发展。在全球竞争的环境中,机场需要有效地利用资源,并评估其表现,以与竞争对手竞争。数据包络分析(DEA)是一种广泛应用于机场绩效评价的方法。本研究旨在采用DEA法、TOPSIS法和EDAS法对2019年和2020年第一季度选定的主要国际机场的性能和排名进行衡量。利用CCR-DEA模型进行了效率分析。然后,根据TOPSIS和EDAS方法对备选方案进行性能评价。在本研究中,机场的排名是根据DEA、TOPSIS和EDAS方法的结果编制的。研究发现,将DEA方法与TOPSIS和EDAS等多准则决策(MCDM)方法一起用于机场绩效评估,可以对决策单元(dmu)进行全面而明确的排名。
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发文量
18
审稿时长
24 weeks
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