Thai Airways Restructuring Plan to Avert Bankruptcy

For the past ten years, Thai Airways International Public Company Limited (THAI) has been suffering successive losses year after year. In 2014, THAI implemented a restructuring plan to improve its revenue streams, yet to no avail as it has been reporting losses. This study aims to determine the impacts of the restructuring plan on profitability ratios in the company and to determine which variable contributes the most towards their profits or losses. The data used were THAI financial statements of 2010 to 2019. As the results show, THAI's profitability ratios show no significant changes before and after the implementation of the restructuring plan, and the largest contributors to their losses are fuel and oil expenses and impairment losses of aircraft.


INTRODUCTION
Thai Airways International Public Company Limited (THAI) is the national majority-owned airline enterprise by Thailand Ministry of Transportation and was registered within the Securities Exchange of Thailand in 1991. Its primary business is transporting passengers, goods, postal, and parcels from scheduled flights to chartered flights. THAI also offers other related services, e.g., aircraft maintenance service, in-flight meals, and beverage service. The fact that the Ministry of Finance owns 53.16% of the company as of 2019 and its businesses are under the State Enterprise Policy Committee's supervision, consider THAI as a state-enterprise (Thai Airways International Public Company Limited, 2019).
In 2010, THAI received the highest profitability in its fifty years of operation, and due to the improved financial performance, it successfully regained investor confidence through its induction back into the MSCI Index (Thai Airways International Public Company Limited, 2010). However, the phase of glory did not last long when THAI started to experience loss in 2011. The losses continuously increased and became worse year by year. CAPA Centre for Aviation (2015) reported the company's operating had experienced failure more than doubled from 2013 to 2014. As a consequence, THAI's operating margin had decreased significantly from -6.2% to -14.9%.
To sustain the company, the Board of Directors and THAI management have put together the THAI restructuring plan, which they labeled as 'big change' to the company. Fedorková and Czillingová (2014) highlighted that when a company fails to eliminate its depression in the market using restoration measures, it is a suitable time for a formal restructuring. This relates to this case study, where THAI did not make profits, and therefore their financial problems escalated. Katowski and Wysocki (2014) distinguished restructuring plans into two dimensions. In a broader sense, it consists of processes, procedures, systems, and action plans, including its scope and all elements within the enterprise. To a smaller degree, it goes through a financial perspective, limited to the restructuring plan of the company's assets and liabilities.
THAI implemented the first approach of restructuring since the company's strategy covered three stages to prevent any further losses, increase the company's competitive business advantage, and build long-term sustainable growth (Thai Airways International Public Company Limited, 2014). The restructuring plan was completed in December 2014 and approved for implementation by the State Enterprise Policy Committee at the end of January 2015. THAI then carried out and proceeded with the plan continuously from 2015 to 2017.
Within the context of this study, seven variables were taken into consideration. The variables are fuel and oil expense, flight service expenses, aircraft maintenance and overhaul cost, impairment loss of aircraft, depreciation and amortization expense, and net income. Paired sample t-test and multiple regression were used to measure these variables. This paper used these chosen variables to measure the effectiveness of the implementation of the restructuring plan.

RESEARCH METHOD
The objectives of this paper are to examine the effectiveness of THAI restructuring plan and to analyze factors that lead THAI to the edge of bankruptcy. This paper solely used secondary data obtained from THAI annual and financial reports, particularly from 2010 to 2019. The profitability ratios for the four years before and after the plan implementation were listed and analyzed for THAI performance evaluation. Subsequently, six variables consisting of five independent variables and one dependent variable were selected. The dependent variable was net income while independent variables were fuel and oil expense (FOE), flight service expenses (FSE), aircraft maintenance and overhaul costs (AMO), an impairment loss of aircraft (ILA), and depreciation and amortization expenses (DAE). This study took the variables to fulfill the second objective of this paper. For the discussion section, several journals and internet sources were included to support the results.
For the first objective, the profitability ratios were divided into two periods: 2011 until 2014 (pre-restructuring) and 2015 until 2018 (post-restructuring). Firstly, the ratio of average margin was manually calculated for comparison purposes. Afterward, paired sample t-test was used to determine whether the profitability ratios showed an improvement. Meanwhile, for the second objective, to investigate the correlation between the independent variables, FOE, FSE, AMO, ILA, DAE, and the dependent variable, the net income, a regression analysis was employed. Following the multiple regression, this paper then carried out one further test, partial regression to measure precisely which one of the independent variables contributed the most towards the variation in the net income.

RESULTS AND DISCUSSION
To analyze THAI's performance after the enactment of the restructuring plan, this paper compared three profitability ratios, i.e., net profit margin, return on total asset, and return on equity of the company. The profitability ratios in 2011, 2012, 2013, and 2014 were used for pre-restructuring performance while taking 2015, 2016, 2017, and 2018 profitability ratios for post-restructuring performance. Table 1 below presents the average margin for each ratio. Note. The average margin based on the profitability ratios extracted from Thai Airways International PLC annual report were calculated manually After comparing the average margin of profitability ratios, the analysis of this paper extended by running paired sample t-test to see if there were any statistically significant changes by each ratio. The outcomes were expected to get a higher mean value for postrestructuring than pre-restructuring. The hypotheses were set as below: H0: μD = 0: There is no difference in profitability ratios before and after the restructuring plan H1: μD ≠ 0: There is a difference in profitability ratios before and after the restructuring plan At the α = 0.05 level of significance, and with the assumption that the differences were distributed normally with a sample size of n = 4 and 3 degrees of freedom, the decision rule was: tstat < ttable = −2.7764 or tstat > ttable = 2.7764, reject H0. Otherwise, H0 is not rejected.
According to Table 1, the results of paired sample t-test can be concluded as follows: a) Net profit margin At 0.05 level of significance, tstat = 0.551 > −ta = −2.7764, therefore did not reject H0. There was no statistical evidence proposing a significant change in net profit margin after the implementation of the restructuring plan.
b) Return on total asset At 0.05 level of significance, tstat = 0.215 > −ta = −2.7764, therefore did not reject H0. There was no statistical evidence proposing a significant change in return on the total asset after the implementation of the restructuring plan.
c) Return on equity At 0.05 level of significance, tstat = 1.053 > −ta = −2.7764, therefore did not reject H0. There was no statistical evidence proposing a significant change in return on equity after the implementation of the restructuring plan.
To find the sources of variation for the net income, a multiple regression test needed to be conducted as well as discussions and introduction of other secondary data to justify the fluctuations in the variables. Table 2 below presents the dataset for the variables chosen as either our dependent or independent variables used within the multiple regression test for variables affecting THAI's net income. Notice that THAI obviously experienced loss in 7 out of 10 years of our sample size.    Given that at least one of the independent variables selected did have a significant effect on net income, to determine whether which variable had a significant effect on net income, after taking into account the effect of FOE, FSE, AMO, ILA, and DAE, the null and alternative hypothesis were: H0: βi = 0 H1: βi ≠ 0 At the a = 0.05 level of significance, and 3 degrees of freedom, the critical t value was ± 2.7764. Therefore, the rejection region was: tstat < ttable = -2.7764 or tstat > ttable = 2.7764, reject H0. Otherwise, H0 is not rejected.

a)
Fuel and Oil Expenses (FOE) on Net Income The unstandardized coefficient β = −0.967 indicates that for a 1 Baht increase in fuel and oil expenses, net income would decrease by 0.967 Baht. To determine whether the FOE variable has a significant effect on net income, the tstat = −3.306 < ttable = −2.7764, therefore H0 is rejected, as there is significant statistical evidence to suggest that FOE has significantly affected net income.

b)
Flight Service Expenses (FSE) on Net Income The unstandardized coefficient β = 7.153 implies that for every 1 Baht increase in flight and services expense, the net income would increase by 7.153 Baht. To determine whether the variable FSE has a significant effect on net income, the tstat = 1.773 ttable = 2.7764, therefore H0 was not rejected. There was no significant statistical evidence to suggest that FSE had affected net income significantly.

c)
Aircraft Maintenance and Overhaul Costs (AMO) on Net Income The unstandardized coefficient value proves that net income decrease by 2.929 for every 1 Baht increases aircraft maintenance and overhaul cost. To determine whether the variable AMO has a significant effect on net income, the tstat = −2.479 ≮ ttable = −2.7764, therefore H0 is not rejected, as there is no significant statistical evidence to suggest that AMO has significantly affected net income. d) Impairment Loss of Aircraft (ILA) on Net Income The unstandardized coefficient value of impairment loss of aircraft is −2.074. This indicates that for every 1 Baht increase in an impairment loss of aircraft, the net income experience decreased by 2.074 Baht. To determine whether the variable ILA has a significant effect on net income, the tstat = −3.593 < ttable = −2.7764, therefore H0 is rejected, as there is significant statistical evidence to suggest that ILA has significantly affected net income.

e) Depreciation and Amortization Expense (DAE) on Net Income
The unstandardized coefficient β = 4.632 implies that for every depreciation and amortization expense increase by 1 Baht, net income increases by 4.632 Baht. To determine whether the variable DAE has a significant effect on net income, the tstat = 1.721 ttable = 2.7764, therefore H0 is not rejected. There is no significant statistical evidence to suggest that DAE has significantly affected net income. Table 4 below presents the proportion of variance within the net income based on the fuel and oil expense, flight service expense, aircraft maintenance and overhaul cost, impairment loss of aircraft, and depreciation and amortization expenses.  Table 4 shows the correlation between the observed and predicted values of net income is 0.933 (strong). Whereas the coefficient of multiple determination, r 2 value is 0.870. This implies that 87% of the variation in the net income can be explained by the values of the independent variables. Note that the corrected r 2 shown within table 4 is 0.707. This indicates 70.7% of the variation in the net income is described by the multiple regression model which has been adjusted for the number of independent variables used in this study and the sample size.

The model in
Given that 70.7% of the variation in the net income can be explained by the multiple linear regression model, as well as two of the five independent variables have a significant effect on the net income, it is crucial to ascertain the factors that lead to the two variables FOE and ILA to have such a significant impact on the dependent variable, net income of THAI.

a)
Fuel and Oil Expense (FOE) Fuel and oil expenses are the highest contributors to THAI's operating expenses. The highest FOE the company ever reported from 2010 until 2019 was in 2013 with 80,525 million Baht (35.9% of total costs), followed by 2012 at 80,178 million Baht (39.50% of total costs). Note that these were the years before the restructuring plan was implemented. According to Thailand Airways International PLC (2013), the company was facing difficulties in managing its FOE as the jet fuel price was relatively high and fluctuating at that time. Due to political uncertainties in oil-producing countries, specifically the North Africans and Middle Eastern countries. Park and O'Kelly (2014) stated that airlines were struggling in confronting financial pressures caused by higher fuel prices in 2013, which eventually led them to merge or enter route-sharing deals with other lines.
As jet fuel accounted for approximately 40% of THAI's operating cost, the company was motivated to improve its fuel hedging and fuel surcharge to lessen the impact of rising jet fuel costs on FOE. Furthermore, hedging is useful when it comes to relaxing financial constraints. Hedging strategy enables the company to provide a higher value by decreasing the expected expenses from their inadequate investing (Froot, Scharfstein, & Stein, 1993), or by attempting to minimize expected expenses beyond the cost of doing business (Smith & Stulz, 1985). THAI's decision of enforcing more efficient fuel hedging management in 2012 resulted in a compensation income of as much as 3,764 million Baht. Unfortunately, in 2013 the amount decreased to 1,885 million Baht, and even worse, THAI recorded an expense for fuel hedging with 281 million Baht in 2014. This amount was due to the weakening Thai Baht against the US Dollar that affected not only the fuel hedging plan but also the amount of fuel and oil expenses for that year. The fuel hedging then remained as the expense to the company until 2019.
Aside from the negative effect of depreciating Thai Baht against the US Dollar that THAI had to face, another mistake that led to THAI's poor performance was the errors in coordinating the aircraft types to their stage length (Thai Airways International Public Company Limited, 2019). This mistake only had been recognized by THAI management at the end of 2018 after analyzing the main problems that made the company had fallen into the trap of a repeated cycle of business loss for a long time. The mismatch in coordinating aircraft types had made THAI incurred high fuel costs considering that old aircraft consumes more fuel than the new-generation aircraft.
Within the aviation industry, reducing fuel consumption is an important goal, and fuel efficiency correlates directly to several prominent factors, such as the distance an aircraft can fly (Mrazova, 2013). Youredi in Santhanakrishnan, Naithani, Parasar, and Gilliani (2019) argued that reducing fuel consumption could save substantial costs. Likewise, Park & O'Kelly (2014) found that other than seat configuration and the number of stops at an intermediate hub location, the stage distance of the aircraft also linked to the fuel burn rates. These findings indirectly emphasized the importance of getting the proper stage length according to the aircraft type or else having to suffer high fuel cost, just like what happened to THAI. In brief, high jet fuel price, fluctuation in foreign exchange rates, and aircraft problems were the reasons for the increase in FOE for THAI.

b)
Impairment Loss of Aircraft (ILA) In 2010, Thai Airways stated the company would recognize impairment losses in its income statement whenever the carrying amount of an asset, in this case, its aircraft, exceeded its recoverable amount. Based on Table 2, THAI was able to keep its ILA low until 2013, where THAI had an increase of 4,655 million Baht or 603.8% compared to 2012. This significant expense (Thai Airways International Public Company Limited, 2013) has made THAI incurred a net loss in 2013 of 12,000 million Baht due to the impairment of a total of 11 aircraft including 4 Airbus A340-500, 3 Airbus A300-600, and 4 Boeing B737-400, compared to 2012, where THAI earned 6,510 million Baht of net profit.
The company had put a strategy to optimize its fuel consumption by working on several adjustments in its flight schedule and the use of appropriate aircraft. Thus, in their efforts to modernize their fleet, 11 planes were impaired. THAI's foresight was right because flight planning affects fuel consumption (Schiefer & Samuel, 2011) and route selection (Altus, 2009) aside from other factors. Therefore, the increase of the ILA in 2013 was expected by THAI's management as they also bought several new aircraft as part of the plan. Besides, according to Rutherford (2020), each newer generation of aircraft operates 15% more efficient fuel per passenger kilometer compared to older aircraft, which supports its fleet modernization strategy.
The ILA expenses kept increasing from 2013 to 2015 with 2015 holding the highest amount at 11,876 million Baht as THAI continued to impair up to 26 aircraft in 2015 consisting of 6 Airbus A340-600, 4 Airbus A340-500, 2 Boeing B747-400, 2 Boeing B747F (freighter), 6 Airbus A330-300, 4 Boeing B737-400, and 2 ATR72. Note that 2015 was the first year of the implementation of THAI Transformational plan. The high number of impaired aircraft in 2015 was due to efficiency issues, or these assets were at the end of their useful lives.
THAI's president said the company would sell their planes to reduce its fleet to 77 from 101 jets by the end of 2015 and he also stated they would incur impairment charges. When being asked the details of the expected costs, THAI's president refused to answer (Webb & Jittapong, 2015). Elliott and Hanna (1996) hypothesized that successful impairment recognition would make analyzing their recurring revenues complicated, and thus would lead to lower investor confidence in the company. THAI was, therefore, unable to successfully predict the impact of the ILA expenses on their future recurring revenues, incurring substantial losses and eventually affected THAI's net income.

CONCLUSIONS
In terms of profitability ratios, THAI has not shown any significant improvements in its net profit margin, return on total asset, and return on equity. The results of the paired samples t-test using a significance level of 95% showed that the improvements made were statistically insignificant, and there was no difference in financial performance between pre-restructuring periods and post-restructuring periods.
Within THAI's financial statements, over the past 10 years, two items greatly impacted the net income negatively, namely fuel and oil expenses and impairment loss of aircraft. These two, along with flight service expenses, aircraft maintenance and overhaul expenses, and depreciation and amortization expenses contributed to 70.7% of the variation found within the net income of THAI. Increases in fuel and oil expenses may be attributable to the company's innate difficulty in managing FOE. Errors in managing the coordination of aircraft types to their stage length have led THAI to increase in FOE, the largest contributor to THAI's expenses for the past 10 years.
Since THAI has not made significant improvements in their profitability and suffered continuous increases in expenses from 2010 to 2019, this study contributes towards the current aviation industry by highlighting issues faced by THAI within this period, as well as providing statistical insight towards their financial issues. Although the restructuring plan was supposed to carry out its proper goals and objectives, its implementation of the restructuring plan was riddled with mismanagement issues.