Financial and Operational Performance Analysis Using LOPCOW Based MARCOS Method: A Case Study of the Asian Airline Market

Year 2025, Volume: 12 Issue: 1, 246 - 270, 31.03.2025

Veysi Asker , Zehra Kilinç

https://doi.org/10.30798/makuiibf.1495165

Abstract

The purpose of the study is to view how companies operating in the Asian airline market responded to the crisis caused by the COVID-19 pandemic. Additionally, it aims to compare the financial and operational performance of airlines in the Asian airline market before, during, and after the COVID-19 pandemic. In this context, the financial and operational performance of 18 airlines in the Asian airline market for the period 2019-2022 was analysed using the Lopcow-based Marcos method. Firstly, financial and operational variables related to airlines were weighted using the Lopcow method. As a result of the weighting conducted with the Lopcow method, it was determined that the Dept Ratio and ROA variables had the most weight on the performance of these airlines. Subsequently, the performance ranking of airlines was conducted using the Marcos method. According to the ranking results obtained by the Marcos method; Spring Airlines (2019), Qantas Airways (2020), Air Arabia (2021) and Singapore Airlines (2022) were found to have the best performance. This study will make a significant contribution to the performance management of airlines in the Asian airline market. It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.

Keywords

Financial Performance, Operational Performance, Lopcow Method, Marcos Method, Airlines.

Ethical Statement

Ethics Committee approval was not required for this study. The authors declare that the study was conducted in accordance with research and publication ethics. The authors confirm that no part of the study was generated, either wholly or in part, using Artificial Intelligence (AI) tools. The authors affirm that there are no financial conflicts of interest involving any institution, organization, or individual associated with this article. Additionally, there are no conflicts of interest among the authors. The authors affirm that they contributed equally to all aspects of the research.

Financial and Operational Performance Analysis Using LOPCOW Based MARCOS Method: A Case Study of the Asian Airline Market

Abstract

The purpose of the study is to view how companies operating in the Asian airline market responded to the crisis caused by the COVID-19 pandemic. Additionally, it aims to compare the financial and operational performance of airlines in the Asian airline market before, during, and after the COVID-19 pandemic. In this context, the financial and operational performance of 18 airlines in the Asian airline market for the period 2019-2022 was analyzed using the Lopcow-based Marcos method. Firstly, financial and operational variables related to airlines were weighted using the Lopcow method. As a result of the weighting conducted with the Lopcow method, it was determined that the Dept Ratio and ROA variables had the most weight on the performance of these airlines. Subsequently, the performance ranking of airlines was conducted using the Marcos method. According to the ranking results obtained by the Marcos method; Spring Airlines (2019), Qantas Airways (2020), Air Arabia (2021) and Singapore Airlines (2022) were found to have the best performance. This study will make a significant contribution to the performance management of airlines in the Asian airline market. It will provide airline managers with insights and guidance on how to enhance the performance of their airlines during periods of crisis, such as the COVID-19 pandemic.

Keywords

Financial Performance, Operational Performance, Lopcow Method, Marcos Method, Airlines

Ethical Statement

Ethics Committee approval was not required for this study. The authors declare that the study was conducted in accordance with research and publication ethics. The authors confirm that no part of the study was generated, either wholly or in part, using Artificial Intelligence (AI) tools. The authors affirm that there are no financial conflicts of interest involving any institution, organization, or individual associated with this article. Additionally, there are no conflicts of interest among the authors. The authors affirm that they contributed equally to all aspects of the research.

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