Abstract
COVID-19 has dealt an unprecedented blow to the aviation industry since 2020. This paper applies the interval epsilon-based measure (IEBM) model to evaluate the optimal quarterly environmental efficiency of 14 global airlines of passenger and cargo subsystems during 2018–2020. Then, the time series prediction method is applied to forecast the interval data of inputs and outputs from 2021 to 2022. Finally, we can calculate the quarterly efficiency. Thus, the future development trends of airlines can be predicted. The results show that (1) COVID-19 has hit the passenger subsystem harder, while the freight subsystem has become more efficient; (2) the efficiency of the freight subsystem has inevitably declined in the post-epidemic era; and (3) therefore, the airlines will have a “√” shaped recovery curve in the next few years.
Highlights
From late 2019 to early 2020, the COVID-19 epidemic swept the world with sudden momentum
A variety of methods had been applied to research airline efficiency, such as the TOPSIS method (Barros and Wanke 2015; Bae et al 2021), factor analysis (Siregar and Norsworthy 2001; Barbot et al 2008; Pappachan 2020); stochastic frontier analysis (SFA), and data envelopment analysis (DEA) method (Bhadra 2009; Ouellette et al 2010; Tavassoli et al 2021)
This paper focuses on the impact of COVID-19, whose outbreak has dealt a heavy blow to the aviation industry
Summary
From late 2019 to early 2020, the COVID-19 epidemic swept the world with sudden momentum. Improving the efficiency of carbon dioxide emissions is of great significance for airlines to meet these challenges. On the discussion method of efficiency, Cui and Li et al (2018) used a neural network to predict the efficiency of 29 international airlines during 2021–2023. They proposed a network epsilon-based measure with managerial disposability to discuss the differences. BP neural network has been widely used in airline input-output indication prediction because of its good performance in non-linear function approximation. This paper presents an interval EBM model to evaluate sample airlines’ quarterly overall and subsystem efficiency with the predicted interval values. The last section is the conclusion and future research directions
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