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Performance measurement of airports using data envelopment analysis: A review of methods and findings

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  • Iyer, K.Chandrashekhar
  • Jain, Soumya

Abstract

Data Envelopment Analysis (DEA) is the most commonly used tool for performance measurement of airports. We studied 61 articles and notes published during 2009–2017 that assess the performance of airports across the globe using ontology-based text analysis. Each article aims at achieving objectives beyond the mere calculation of efficiency scores of airports. On the basis of these objectives, four themes emerge – explaining the variation of efficiency through exogenous factors; mapping the change in efficiency over time; decomposition of efficiency using network DEA; and comparing DEA with other tools. We find that there is no systematic approach for selection of inputs and outputs, as they are largely dependent on the availability of data. Most studies computing scale efficiency report that airports exhibit returns to scale. Ownership form of airports is the most commonly studied factor for explaining the variation in efficiency; however, there is no consensus in the findings. Nearly one-third articles study the change in efficiency over time reporting similar findings that can be generalized. The research gap emerging from the review is that there is insufficient thrust on the application of efficiency scores obtained from DEA for improving airport performance. The main contribution of the paper is an analysis of the approaches used for performance measurement and the associations made with the efficiency scores.

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  • Iyer, K.Chandrashekhar & Jain, Soumya, 2019. "Performance measurement of airports using data envelopment analysis: A review of methods and findings," Journal of Air Transport Management, Elsevier, vol. 81(C).
    • Handle: RePEc:eee:jaitra:v:81:y:2019:i:c:s0969699718305131
    DOI: 10.1016/j.jairtraman.2019.101707
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    Citations

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    Cited by:

    1. Thomas, Nivea & Jha, Kumar Neeraj, 2022. "Structural efficiency assessment of regional airports: Lessons from India," Utilities Policy, Elsevier, vol. 79(C).
    2. Chia-Nan Wang & Minh Nhat Nguyen & Anh Luyen Le & Hector Tibo, 2020. "A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam," Mathematics, MDPI, vol. 8(7), pages 1-24, July.
    3. Kaya, Gizem & Aydın, Umut & Karadayı, Melis Almula & Ülengin, Füsun & Ülengin, Burç & İçken, Ayhan, 2022. "Integrated methodology for evaluating the efficiency of airports: A case study in Turkey," Transport Policy, Elsevier, vol. 127(C), pages 31-47.
    4. Hu, Rong & Huang, Mengyuan & Zhang, Junfeng & Witlox, Frank, 2023. "On the Matthew effect in a multi-airport system: Evidence from the viewpoint of airport green efficiency," Journal of Air Transport Management, Elsevier, vol. 106(C).
    5. Maria Rosa Nieto & Rafael Bernardo Carmona-Benítez, 2021. "An Approach to Measure the Performance and the Efficiency of Future Airport Infrastructure," Mathematics, MDPI, vol. 9(16), pages 1-28, August.
    6. Yu, Ming-Miin & Rakshit, Ipsita, 2023. "Assessing the dynamic efficiency and technology gap of airports under different ownerships: A union dynamic NDEA approach," Omega, Elsevier, vol. 119(C).
    7. Wang, Zhanwei & Song, Woon-Kyung, 2020. "Sustainable airport development with performance evaluation forecasts: A case study of 12 Asian airports," Journal of Air Transport Management, Elsevier, vol. 89(C).
    8. Cifuentes-Faura, Javier & Faura-Martínez, Ursula, 2023. "Measuring Spanish airport performance: A bootstrap data envelopment analysis of efficiency," Utilities Policy, Elsevier, vol. 80(C).

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