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DOI: https://doi.org/10.34069/AI/2023.63.03.1
How to Cite:
Aman, Q., & Altass, S. (2023). The impact of debt and equity decisions on business performance: Evidence from International
Airline Corporation. Amazonia Investiga, 12(63), 10-20. https://doi.org/10.34069/AI/2023.63.03.1
The impact of debt and equity decisions on business performance:
Evidence from International Airline Corporation

Received: February 10, 2023 Accepted: March 20, 2023
Written by:
Qaiser Aman1
https://orcid.org/0000-0003-4358-7940
Sultan Altass2
https://orcid.org/0000-0003-3733-7400
Abstract
Capital structure decision remains always
interesting puzzle for practitioner as well as for
researchers. Capital structure of company fluctuates
from company to company, country to country,
nature of business to business and firm age to age.
The current study examines the impact of capital
structure (financial leverage and equity decision) on
airline performance. The analysis is performed on
secondary data. Data is taken from the financial
statements of under consideration study of Pakistan
International Airline. Sample period is taken from
2004 to 2020. The financial performance is
measured by ROA and ROE, while independent
variables are debt to asset (DTA), debt to equity
(DTE), and size (natural log of total assets). Two
econometric models are developed for the analysis.
Regression and correlation are used to measure the
impact of debt and equity on company performance.
The study demonstrated that DTA has a statistically
significant negative relationship with the dependent
variable, ROA. Model 1 results indicated that only
DTA was the good predictor of ROA and size had
no significant relationship with ROA. Model 2
results demonstrated that the size had a significant
but positive relationship with ROE. Meanwhile,
DTA had an insignificant association with ROE.
Keywords: Financial Performance, Debt, Equity,
Return on assets, Return on equity, Airline
Company.
Introduction
Pakistan International Airline (PIA) was
established on 29th October 1946 with the name
Jel Classification: C21, G32, L93, M41
1
Qaiser Aman, Ph. D, Associate Professor, Department of Accounting, College of Business, King Abdulaziz University, Jeddah,
Rabigh Campus, Saudi Arabia.
2
Dr. Sultan Altass, Head of Accounting Department, College of Business, King Abdulaziz University, Jeddah, Rabigh Campus, Saudi
Arabia.
of Orient Airways. It was originally based in
Calcutta, British India, before partition. After
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partition, Pakistan International Airline
Corporation (PIAC) took control of Orient
Airways (See Appendices A). It started its
international operation in 1955 to London via
Cairo and Rome. One of the key performance
indicator of an airline is employees-to-Fleet
Ratio (See Appendices B). It is a nonfinancial
indicator of airline. It explains the size of fleet
with respect to number of employees. The Syrian
Arab Airlines has the worst employees-to-fleet
ratio, followed by PIA and Thai Airways. Garuda
Indonesia has a good employees-to-fleet ratio.
Meanwhile, Turkish Airlines has very strong
position with respect to the size of fleet and has
second good employees-to-fleet ratio. Egypt Air
has third good employees-to-fleet ratio (Shah,
2016)
Financial information always plays a vital role in
businesses' success, competition, growth, and the
brand name of the company. A good accounting
information system helps a lot in designing,
maintaining, and generating needed and specific
reports. Small to large and all kinds of businesses
need proper accounting records in order to
evaluate their progress. A sound and reliable
accounting/finance section is indispensable for
business development generally and particularly
for corporations. In time, free from errors,
verified, complete, and fair financial information
about business activities assists a company in
making good decisions. Proper records and
organized information are equally important for
businesses of all sizes and of any nature. Small
size businesses require less financial and
nonfinancial resources in comparison with
medium and large size businesses. Companies’
cross-functional decisions are very crucial. In
fact, all decisions are important such as
marketing, human resource, research and
development, operational/production, and
financial ones (Frank & Goyal, 2003). Financing
requires fundamental and major decisions.
Capital structure of a company is comprised of
debt and long-term capital. It is utilized by a
company in order to acquire the needed assets or
to fill the gap of required capital (Damodaran,
2001). Both debt and equity are ultimately
claimed by the investor over the assets of a
company. It is crucial to use them in a proper
way. Use them in productive assets so that the
company generates sufficient revenues (Riahi-
Belkaoui, 1999).
It is worth mentioning that financial decisions
need particular attention and care. Financial
decisions influence all the activities and
functions of a company. Every financial decision
needs proper analysis. Two basic dimensions
always have to be considered in making a
financial decision in the form of the costs and
benefits of financing. Debt and equity decision in
a company needs great care and attention.
Technical analysis is needed with respect to
value addition in a long run (Ardalan, 2018).
Fundamental analysis helps company
management to make debt and equity decisions.
Numerous factors affect such decisions,
including investor relations, interest rates, and
conditions of a business, capacity, growth, and
length of credit, dividends, earnings per share,
market conditions, internal strengths, external
opportunities, liquidity position, and previous
earnings (Campbell & Rogers, 2018). Long-term
debt and equity relate to the capital structure of a
company. Top-level management is responsible
for capital structure decisions. Technical analysis
(ratio analysis) plays a crucial role in a firm’s
capital structure. It has been noted that no
company is self-sufficient in terms of financial
resources. Based on the corporate culture, capital
structure decisions need to require a knowledge
of the level of competition, market opportunities,
business conditions, interest rates, and previous
dividend payouts. There is no ideal figure for the
capital structure of a company. It depends upon
the nature, size, condition, growth, interest rates,
and the past and current performance of a
company. Due to the prevailing condition and the
market mechanism, corporate culture has
become popular. Economies worldwide promote
corporate culture. Such a culture plays a
significant role in those countries and is equally
important for investors and for the economy in
general. Different regions of the world also affect
the capital structure decisions of a company
differently. Institutionalized systems, quality of
life, financial literacy, transparency, and quality
of law also matter in capital structure decisions
(Butzbach & Sarno, 2019).
Financial experts have indicated different capital
structure theories since the 1950s. They have also
tried to explain the effect value of the firm and
capital structure on stock returns. In short, many
studies have been conducted and published on
this field. No one has claimed to have determined
the ideal or more suitable capital structure for
companies. There is no scientific rule and no
agreement over the optimal level of debt and
equity. Various researchers highlighted different
factors for evaluating the capital structure of a
firm. In particular, two key philosophies (trade-
off theory and pecking order theory) explain the
factors that affect the capital structure of a
company. Theory of trade-off claims that there is
an optimal capital setup for companies through
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determining the most suitable debt ratio
(Jalilvand & Harris, 1984; Frank & Goyal, 2007).
(Modigliani & Miller, 1958) have suggested that
capital structure theories operate under perfect
market condition. Expectations of perfect capital
market conditions relating to homogenous
opportunities, investors, tax holidays, no
transaction costs, and efficient market and capital
structures are inappropriate when it comes to
shaping businesses’ worth. However, the capital
structure proposition of Modigliani and Miller
(MM) is well known as the "theory of
irrelevance" of capital structure and discloses
that capital structure is independent of business
performance. Both new and existing businesses
need an appropriate amount of capital to run the
business properly. Without sufficient financial
resources, a business’s performance comes under
pressure and the company cannot meet the
expectations of investors nor that of the
company’s management (Ghosh et al., 2000).
Problem Statement
International business, especially the tourism and
hospitality business is in full swing. Due to
globalization, the boundaries of businesses have
been extended, and isolation has become a
dream. Tourism and hospitality are being
promoted by every country. This sector has
become a revenue-generating sector. The airline
industry is a prerequisite for developing the
tourism and hospitality sector. The airline
industry requires a huge amount of funds in order
to operate the business. Almost all countries
worldwide have their own airline company.
Consequently, it has become a very large
industry globally, and capital structure decisions
has a tremendous importance for airline
companies. The current study analyzes the effect
of financial leverage and equity decisions on
airline performance.
Review of the Literature
There is no doubt that every decision has some
costs and benefits. Debt has its own benefits and
costs, while equity has different ones. Both are
significantly affected by other factors; financial
leverage and capital also affect the financial
performance of a company (Miguel & Pindado,
2001). According to (Gaud et al., 2005) that the
combination of long-term debt and equity of a
firm impacts the business performance
differently, as compared to (Flannery & Rangan,
2006) and (Gonzalez & Gonzalez, 2008). (Myers
& Majluf, 1984) and (Fama & French, 2002)
reported that market information and trends
affect a company’s capital structure decisions.
Usually, internal financing is more suitable than
external financing for companies. Internal
financing depends upon the generation of
revenue and sufficient availability of funds. In
short, companies prefer debt due to the
unavailability of internal funds. Therefore, the
pecking-order theory stance does not claim to
encourage the presence of an ideal liability ratio.
It considers investor behavior, corporation tax,
and principal and agent relations (Frank &
Goyal, 2009).
Asgharian (2003) examined the relationship
between highly debt firms and firm performance.
The study findings showed that more debt leads
to less sales growth and less stock return.
Whereas, still highly debt firm shows greater
progress in profitability. The study suggested that
decline in sales of highly financial leveraged
firms might be a question of management
performance.
Aman & Altass (2019) analyzed the impact of
capital structure and its impact on business
performance over the period of 1990 to 2015 of
an airline industry. They reported no significant
effect of debt to assets with respect to business
performance. While the results showed positive
and significant impact of debt to equity on
business performance of Airline Company. Nenu
et al., (2018) examined the leverage on risk and
performance of company. They collected data
from registered firms on the Bucharest Stock
Exchange. Their results demonstrated that
leverage is positively correlated with the size of
firm. Leverage also influences the market price
of share. (Mallinguh et al., 2020) analyzed the
situation with respect to age, business sector, and
firm performance in terms of the mediating role
of financial leverage and foreign ownership.
Results indicated that debt has a significant effect
on firm’s performance. They investigated 146
enterprises in which leverage was found to be a
significant contributor to firm’s performance.
They also found insignificant relation of foreign
ownership with firm’s performance. However,
Mallinguh et al., (2020) explained that the
internal ownership of a firm perceives that the
availability of debt impacts the company’s
performance. Some financial scientists claim that
leverage does not influence business
performance. Debt harms firms when their
conditions, growth, and performance are not up
to the required standard. Although some of the
literature warns against high leverage levels, high
leverage actually depends upon specific
businesses that need high liquidity for their
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processes. In short, insufficient internal funds
lead to the use of external funds.
Warokka, Jose & Abdullah (2011) analyzed the
capital structure and firm financial performance
of 532 East Asian companies in term of post
Asian Financial Crises. Their findings predicted
significant association with debt and firm
performance. While study depicted inverse
relationship between ownership structure and
firm performance. On the other hand Margaritis
& Psillaki (2007) investigated the association
between debt and firm efficiency. Their research
questions were “Does higher leverage lead to
better firm performance? And Does efficiency
exert a significant effect on leverage over and
above that of traditional financial measures of
capital structure? What is the signaling role of
efficiency to creditors or investors? Is the effect
of efficiency on leverage similar across different
capital structures? Their results demonstrated
that efficiency declines as debt increases. While
leverage has positive effect on profitability.
This controversial dialog has allowed different
researchers to explain the attributes of various
variables with respect to company and country
profiles. It is a universal truth that every company
and country have their own characteristics and
environment, law and order, corporate laws,
institutional frameworks, targets, international
relations, economic situation, investors trust, and
so on. Former researchers have pointed out that a
company’s financial arrangement is not affected
by firm-specific variables. At the same time,
country-specific environment impacts the
financial structure of a company (Booth et al.,
2001; Bancel & Mittoo 2004). Despite this, the
firm particular dynamics and country-specific
factors are equally important, and both influence
the firm’s financial leverage decisions (De Jong
et al., 2008).
Usually businesses use debt for tax shield
purposes. This way, a firm’s value can be
enhanced due to debt financing (Jensen, 1986).
(Hadlock & James, 2002) also reported the same
findings. On the other hand, some researchers
have pointed out an adverse relationship between
debt and the financial performance of a firm
(Fama & French, 2002; Simerly & Li, 2000),
while (Zeitun & Tian, 2007) supported the
argument that financial performance depends
upon a balanced capital structure.
Methodology
A study database was designed through the use
of the standardized financial statements of the
company. Data were collected from the
company’s annual reports. PIA was taken as a
case to find the debt and equity impact over the
period from 2004 to 2020. The first step was to
download the financial reports from the given
website (https://www.piac.com.pk/corporate/).
The second step was to arrange and organize the
data in an Excel sheet. The third step was to
calculate necessary ratios for dependent and
explanatory variables. The fourth step was to
export organized information to SPSS software
for further analysis.
Theoretical Framework:
Grafic 1. Research Study Model
Source: Researchers’ developed 2023
Hypotheses of the Study
H1: It is predicted that DTA and firm
performance have negative relation.
H2: The DTE has a positive relationship with
business performance.
H3: The size of the firm and business
performance have positive relationship.
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Variables Construction and Concepts
Business performance of airline is measured by
ROA and ROE ratio. The explanatory variables
are measured through DTE and DTA, while the
size of the company is measured through total
assets of the company.
Dependent Variables
Financial performance is reflected to be a key
indicator of corporate achievement. Investors
and management are greatly concerned with
firms’ performance. Investors motivate and make
investment decisions through the consideration
of the financial soundness of the company.
Meanwhile, management performance is
checked through business achievement and
financial performance of the company. Many
dimensions of a firm linked with the firm’s
performance. Two quantitative financial
parameters are taken as the dependent variables
ROA and ROE.
Return on Assets
ROA or investment measures the efficiency and
utilization of total assets and is considered to be
a key performance indicator. It measures the cash
inflows generated by the total assets of a firm.
Return on Assets = Net Profit / Total Assets
Return on Equity
ROE is also a good performance indicator. It
measures the return on stockholders’ equity. A
high ROE increases the trust of stockholders and
increases the likelihood of success if an issue
regarding raising capital occurs in the future. It
also portrays the good image of company in the
market. A good market image ultimately
increases the market price per share.
Return on Equity = Net Income / Shareholders’
Equity
Independent Variables
Debt and equity decision becomes indispensable
for companies. The current study utilized three
independent variables in the form of DTA ratio,
DTE ratio, and the total assets of the firm.
Debt to Assets
DTA measures how many assets are financed
through debt of a company. Alternatively, it
denotes the percentage of debt in assets. A high
ratio indicates risk and reduces the net profit of
the firm.
Debt to Assets = Total Debt / Total Assets
Debt to Equity
DTE is another explanatory variable which is
utilized for measuring a company's financial
leverage. Such ratio indicates the use of debt in
comparison with equity when company makes
investment.
Debt to Equity = Total Liabilities / Total equity
Size of the Firm
Total investment of the firm is measured through
the total assets of the company. This study has
taken the natural log of the total assets and
regressed to firm performance.
Size = LNTA (Natural logarithm of total assets)
Data Examination
The trends of data are examined through
descriptive analysis. Meanwhile, correlation and
multiple regression are utilized for investigating
the impact of debt and equity on business
performance. More precisely, the relationship of
debt to asset is considered with respect to a firm’s
performance. DTE is regressed to ROA and ROE
to find the relationships and identify how much
change occurs in the dependent variable when
one-percent change occurs in independent
variables. How debt and equity affect the firm’s
performance is also considered. Data analysis
also checks the association, direction, and
strengths of associations between independent
and dependent variables. The following models
are constructed based on in-depth review of the
literature:
Yit = α+ β1it DTA +β2it DTE + β3it Size +
ε______________________________(1)
Where,
Yit is the return on assets,
Α is the coefficient of intercept,
DTA is the debt to asset,
DTE is the debt to equity,
Size is the natural log of the total assets,
Ε (ε) is the error term.
Yit = α+ β1it DA +β2it DE + β3it Size + ε____ (2)
Where,
Yit is the return on equity,
Α is the coefficient of intercept,
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DTA is the debt to asset,
DTE is the debt to equity,
Size is the natural log of the total assets,
Ε (ε) is the error term.
Analysis and Results of Model 1.
To draw a conclusion, the following tests results
and statistics are presented below:
Table I.
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. deviation
ROA
17
-8.9037
40.0209
2.7995
11.2677815
ROE
17
-23.1751
73.1792
4.2010
20.0532246
DTA
17
22.7604
61.5809
3.5247
9.2527943
DTE
17
29.4673
160.2873
5.8464
30.6756934
Size
17
20.4867
21.6413
2.1113
.3530912
Source: Researchers’ calculated 2022
Table II.
Correlations
ROA
DTA
DTE
Size
ROA
Pearson
correlation
1
Sig. (2-tailed)
DTA
Pearson
correlation
*
.604-
1
Sig. (2-tailed)
.010
DTE
Pearson
correlation
**
.723-
**
.977
1
Sig. (2-tailed)
.001
.000
Size
Pearson
correlation
*
.605-
.276
.327
1
Sig. (2-tailed)
.010
.283
.200
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).
Source: Researchers’ calculated 2022
The above explains the relationship, direction,
and association strengths between the variables.
Almost all the variables have significant
relationship with each other. However, DTE is
highly correlated with DTA and ROA. This
indicates that there is a problem of
multicollinearity resulting in spurious results.
Consequently, the study removed the DTE
variable from the model and tested the
correlation again. After removal of the DTE
variable, the correlation between the variables
comes within the normal range.
Table III.
Correlations
ROA
DTA
DTE
Size
ROA
Pearson correlation
1
Sig. (2-tailed)
DTA
Pearson correlation
*
.559-
1
Sig. (2-tailed)
.020
Size
Pearson correlation
-.401
.220
-.267
1
Sig. (2-tailed)
.111
.396
.300
Correlation is significant at the 0.05 level (2-tailed).
Source: Researchers’ calculated 2022
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Table IV.
Model Summaryb
R
R square
Adjusted R square
Std. error of the
estimate
Durbin-Watson
a
.644
.414
.279
8.83827
1.949
a. Predictors: (Constant), DTA, size. b. Dependent variable: ROA.
b. Source: Researchers’ calculated 2022
Table V.
ANOVAb
Model 1
Sum of squares
df
Mean square
F
Sig.
Regression
718.550
3
239.517
3.066
a
.066
Residual
1015.494
13
78.115
Total
1734.044
16
a. Predictors: (Constant), size, DTA. b. Dependent variable: ROAs.
Source: Researchers’ calculated 2022
Overall regression model goodness-of-fit is observed, and the results were shown to be unbiased, and the
sample is normally distributed.
Table VI.
Coefficients
Model 1
Unstandardized coefficients
Standardized
coefficients
t
Sig.
B
Std. error
Beta
(Constant)
182.232
166.518
1.094
.294
DTA
-.041
.019
-.470
-2.133
.053
Size
-10.261
8.947
-.256
-1.147
.272
a. Dependent variable: ROA.
Source: Researchers’ calculated 2022
The results of table explain that DTA has a
significant negative relationship with ROA. It
indicates that DTA has a negative impact on
ROA. The results demonstrate that the increase
in DTA leads to a reduction in ROA of the
company and vice versa. On the other hand,
firm’s size has no significant association with the
dependent variable. The results show that only
DTA is a predictor of ROA.
Research Model 2 Results
Table VII.
Correlations
ROE
DTA
DTE
Size
RTE
Pearson correlation
1
Sig. (2-tailed)
DTA
Pearson correlation
.078
1
Sig. (2-tailed)
.767
DTE
Pearson correlation
**
.951-
-.211
1
Sig. (2-tailed)
.000
.415
Size
Pearson correlation
.096
.220
-.267
1
Sig. (2-tailed)
.713
.396
.300
tailed).-Correlation is significant at the 0.01 level (2
**
Source: Researchers’ calculated 2022
The study found the same multicollinearity
problem with debt to equity in the second model.
To avoid the misleading statistical evidence the
study removed DTE from the model and then
performed correlation analysis given below.
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Table VIII.
Correlations
ROE
DTA
Size
ROE
Pearson correlation
1
Sig. (2-tailed)
DTA
Pearson correlation
.078
1
Sig. (2-tailed)
.767
Size
Pearson correlation
.096
.220
1
Sig. (2-tailed)
.713
.396
Source: Researchers’ calculated 2022
Table IX.
Model Summaryb
Model 2
R
R square
Adjusted R square
Std. error of the estimate
Durbin-Watson
a
.970
.942
.928
17.28118
2.413
a. Predictors: (Constant), size, and DTA. b. Dependent variable: ROE
Source: Researchers’ calculated 2022
Table X.
ANOVAb
Model 2
Sum of squares
df
Mean square
F
Sig.
Regression
62565.277
3
20855.092
69.834
a
.000
Residual
3882.309
13
298.639
Total
66447.586
16
Table XI.
Coefficients
Model 2
Unstandardized coefficients
Standardized
coefficients
t
Sig.
B
Std. error
Beta
(Constant)
719.064
325.588
2.209
.046
DTA
-.056
.038
-.103
-1.485
.161
Size
37.507
17.494
.151
2.144
.052
a. Dependent variable: ROE.
Source: Researchers’ calculated 2022
The above results demonstrate that DTA has no
association with the dependent variable. Size also
has a positive impact on firm performance.
Results show that size is a predictor of ROE.
Conclusions
In order to reach sound conclusions, the current
study developed two econometric models in
order to analyze debt and equity decisions with
respect to company’s financial performance. The
financial management of the airline industry is
not an easy task. It is a capital-intensive industry,
and its financial decisions have critical
importance, especially with regard to the use of
debt and equity decisions. Higher levels of debt
make a firm riskier and vice versa. The
advantages and disadvantages of debt and equity
must be taken into account when making
appropriate capital structure decisions.
PIA uses more debt in comparison with equity,
even though the interest rates are high in
Pakistan. The results of the first model found that
only DTA plays a significant role in terms of
financial performance, whereas size does not
have a substantial effect with respect to capital
structure. DTA was found to have negative
relationship with ROA, but PIA is using more
debt. This is the reason that company is going
into loss. Having financial distress is why a
company uses debt to operate. In fact, when
company takes more debt, it can give greater
returns to creditors in the form of interest
expenses. The second model investigated the
possibility that size plays a significant role in
firm’s performance. The company has sufficient
total assets and can utilize them in a productive
way. Efficient and effective use of total assets
creates value addition to the firm, and such value
addition is needed by PIA. It is essential to make
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the assets productive and reduce the use of
nonproductive assets. In fact, nonproductive
assets have a liability over the company to pay
insurance, maintenance expenses, etc. There is
no doubt that the airline company is extremely
capital intensive and is often considered to have
a high debt-to-equity ratio. Therefore, substantial
amounts of capital are required to buy planes,
heavy tools to support them, major fuel charges
which depend upon market price, air hangars,
flight simulators, maintenance to airplanes,
flyers, trip attendants, luggage handlers, and
catering cost. A major problem of PIA is
overstaffing. It has just 28 airplanes with very
low number of destinations, just 45.
Approximately 10500 employees are working in
PIAC which is too much as compared to its fleet.
Employees-to-fleet ratio 375/aircraft which is
very high. It shows worst staff-to-plane ratio in
the airline industry after Syrian airline. It is a
weak indicator of airline. It is highly
recommended to reduce the number of
employees.
PIA is a national flag airline, and company would
take serious action to revive the airline. It has a
lot of potential, and very huge number of
Pakistanis are working abroad. Company would
attract them and activate public relation
department. It would also work on cost reduction
strategies.
Acknowledgement: This work was funded by
the Deanship of Scientific Research, King
Abdulaziz University, Jeddah, Under Grant No.
G: 300-849-1441. We are grateful to the
Deanship of Scientific Research, King Abdulaziz
University, Jeddah for their funding this project.
Bibliographic references
Aman, Q., & Altass, S. (2019) Impact of Capital
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Appendices A
Important Facts about PIAC
Source: Pakistan International Airlines (2021)
Established
October 29, 1946
Age
75 years
Subsidiaries
1. Roosevelt Hotel 2. Hotel The Scribe (Paris) 3. Skyrooms (Pvt) Limited 4. PIA Investment Limited
Fleet size
28
Destinations
56
Parent company
Aviation division, GoP
Revenue
$590 million
Operating income
$-4.2 million
Net income
$-220 million
No. of employees
10500 (10 April 2021)
Website
https://www.piac.com.pk/corporate/
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www.amazoniainvestiga.info ISSN 2322- 6307
Appendices B
Employees-to-Fleet Ratio of Some Airlines
Source: Shah (2016)
S. no.
Airline company
No. of employees
Fleet
Employees-to-fleet
ratio
1
Garuda Indonesia
7,861
140
1:56.15
2
Turkish Airlines
18,882
298
1:63.36
3
Egypt Air
9000
63
1:141.41
4
Etihad Airlines
17712
119
1:148.84
5
Saudi Arabian Airlines
24842
163
1:152.40
6
Qatar Airways
31,000
173
1:179.19
7
Malaysian Airlines
14,000
77
1:181.82
8
Emirates Airlines
59,519
255
1:233.40
9
Thai Airways
25,323
82
1: 308.82
10
PIA
10,500
28
1:375
11
Syrian Arab Airlines
4,000
10
1:400