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Top1. Introduction
As of 2022, the air transport industry in Malaysia consists of 40 airports providing services for 78 airlines from local destinations and around the globe. These 78 airlines comprise of 61 international airlines and 17 local airlines, including four cargo airlines. Since its establishment in 1992, the Malaysia Airports Holdings Berhad (MAHB) has come to operate 39 airports, including 17 domestic, 5 international, and 17 short take-off and landing ports nationwide. Therefore, the majority of airport operations including flight passengers, cargo and mail in Malaysia are operated by MAHB. For MAHB, its highest revenue, RM 5.2 billion, and highest net profit, RM 748.5 million, were recorded in 2019 and 2014 respectively (Hao and Xuan, 2022). In this context, MAHB represents a substantial component of the Malaysian airport operations for this study.
Throughout the years, the financial performance for the airport operations in Malaysia has varied. Between 1999 and 2021, there were a series of challenges that contributed to a disruption in the air transport industry, such as the Great Recession in 2008, the 2014 incidents involving the disappearance of MH370 and the shooting down of MH17, and most recently the novel coronavirus (COVID-19) pandemic in 2020. The COVID-19 pandemic in particular has proven to leave a significant mark on the world’s air transport industry. The period between the COVID-19 pandemic starting on March 11, 2020 (Cucinotta and Vanelli, 2020) and the COVID-19 being declared endemic in Malaysia on April 1, 2022 (Lee, 2022) is shown by the vertical lines on the time series plot of Altman Z”-score of MAHB in Figure 1.
Figure 1. Time series plot of Altman Z’’-score for years 1999 to 2021 with a decreasing trend that continues linearly for years 2022 to 2031, including financial distress thresholds between financially stable and exposure to financial distress
Altman Z”-score measures the degree of financial distress of an organisation (Altman, 1968; Altman, 1983; Altman, 2013). The Altman Z”-score originates from the Altman Z-score (1968) and Altman Z”-score (1983) as a bankruptcy prediction model. The Z”-score is more practical when analysing airline operations than other measures as it is suitable for both public and private, manufacturing, and non-manufacturing firms (e.g. Subramaniam et al., 2019; Odibi et al., 2015; Mohammed et al., 2002). For example, the bankruptcy forecasting model that has shown to have high predictive accuracy when applied to United States (U.S.) and Indian airlines (Shi and Li, 2021). In Figure 1, the calculated Altman Z”-score was the highest (9.20) in 1999 to 4.03 in 2014, and the recent score of 3.80 in 2021 which is at its worst position during the 23-year period.
The Z′′-score being more than 2.6 indicates that the financial situation of MAHB is safe from financial distress or any exposure of bankruptcy. If the Altman Z”-score is between 1.1 and 2.6, then the MAHB is being exposed to financial distress. MAHB is said to be having financial distress if the Z′′-score is less than 1.1. These financial distress threshold values of 1.1 and 2.6 are shown by the horizontal lines (green and firebrick respectively) in Figure 1. A univariate linear model with a trend is fitted to the observed Altman Z”-score from 1999 to 2021, and the declining linear trend (red) is concerning. Given the decline of the Altman Z′′-score in Figure 1, it is likely that this downward trend will continue. As shown in Figure 1, if the trend continues, into the future the forecasted trend line is expected to cross the green line by 2030, hence a reposition from being financially stable to exposing financial distress between year 2022 and 2031. Therefore, it is essential that the determinants of Altman Z′′-score for MAHB are examined.