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

Chia-Nan Wang (), Tsang-Ta Tsai (), Hsien-Pin Hsu () and Le-Hoang Nguyen ()
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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

Sustainability, 2019, vol. 11, issue 9, 1-20

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.

Keywords: data envelopment analysis; DEA Window model; GM(1,1); Malmquist; aviation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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