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Performance Evaluation of Major Asian Airline Companies Using DEA Window Model and Grey Theory

Author

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  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Tsang-Ta Tsai

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Hsien-Pin Hsu

    (Department of Supply Chain Management, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan)

  • Le-Hoang Nguyen

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

Abstract

Being an essential part of the global transport system, airline transportation is capable of delivering fast service for passengers and commodities. In the past decade, the Asia aviation industry has experienced a high growth rate of transport due to higher economic development in this area, and this trend is expected to continue in the next two decades. However, competition in the Asia aviation industry will increase dramatically. To survive in the Asia aviation industry, the Asia airline companies should understand their current and future performance. A methodology for this purpose is required. This paper proposes a hybrid approach, combining Grey model GM(1,1) and Data Envelopment Analysis (DEA) Window model, to satisfy this need. The hybrid approach proposed in this research has been used to evaluate the current and future performance of 16 major Asia airline companies. The DEA Window analysis showed that airline companies Emirates, Cebu Pacific, and Sri Lankan were leading companies in the time period of 2012 to 2016, while Singapore Airlines, Japan Airlines, and All Nippon Airways followed behind. We found that Chinese airline corporations are rising in the Asia aviation industry. All 16 Asia airline companies studied in the research were found to improve their productivity in the time period of 2017 to 2021 as their Malmquist productivity indexes (MPIs) are greater than 1.

Suggested Citation

  • Chia-Nan Wang & Tsang-Ta Tsai & Hsien-Pin Hsu & Le-Hoang Nguyen, 2019. "Performance Evaluation of Major Asian Airline Companies Using DEA Window Model and Grey Theory," Sustainability, MDPI, vol. 11(9), pages 1-20, May.
  • Handle: RePEc:gam:jsusta:v:11:y:2019:i:9:p:2701-:d:230515
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    References listed on IDEAS

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    Cited by:

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    2. Babatunde A. OKUNEYE & Oluwatosin O. OGUNYOMI-OLUYOMI, 2022. "The Role of Digitalization in the Airline Industry Performance AMID COVID-19: Evidence from Emirate Airline Balanced Scorecard Performence," Business & Management Compass, University of Economics Varna, issue 1-2, pages 365-379.
    3. Liu, Dan & Zhang, Jiahuang & Yu, Ming-Miin, 2023. "Decomposing airline profit inefficiency in NDEA through the non-competitive Nerlovian profit inefficiency model," Journal of Air Transport Management, Elsevier, vol. 107(C).
    4. Chia-Nan Wang & Thi-Ly Nguyen & Thanh-Tuan Dang, 2021. "Analyzing Operational Efficiency in Real Estate Companies: An Application of GM (1,1) and DEA Malmquist Model," Mathematics, MDPI, vol. 9(3), pages 1-28, January.
    5. Hashem Omrani & Meisam Shamsi & Ali Emrouznejad, 2023. "Evaluating sustainable efficiency of decision-making units considering undesirable outputs: an application to airline using integrated multi-objective DEA-TOPSIS," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 5899-5930, July.
    6. Yu, Ming-Miin & Chen, Li-Hsueh, 2023. "Productivity change of airlines: A global total factor productivity index with network structure," Journal of Air Transport Management, Elsevier, vol. 109(C).
    7. Yuanxin Peng & Zhuo Chen & Juanzhi Xu & Jay Lee, 2020. "Analysis of green total factor productivity trend and its determinants for the countries along silk roads," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1711-1726, December.

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