Analysis of CEO Characteristics on the Performance of Indonesian
Mining Sector Companies
RIBHAN, ARIPIN AHMAD, RA FISKA HUZAIMAH
Department of Management,
University of Lampung,
Bandar Lampung City,
INDONESIA
Abstract: - National Energy Policy (KEN) and the Paris Agreement are a step in the energy transition in
Indonesia towards the use of new and renewable energy. The government is committed to reducing greenhouse
gas (GHG) emissions using new and renewable energy. Therefore, research related to the performance of
mining sector companies is interesting because the performance of mining companies is one of the keys to the
success of the government in implementing KEN. The method used in this research is descriptive quantitative
through the application of panel data regression models to be able to analyze the characteristics of company
CEOs in the mining sector. The result of the research is that the panel data model can provide an overview
which is then analyzed for the relationship between CEO characteristics and company performance in the
Indonesian mining sector. This study found that CEO's work experience and CEO's Strength and CEO's level of
education did not significantly influence the performance of mining sector companies in Indonesia.
Key-Words: - CEO Characteristics, National Energy Policy, Panel Data, Mining Sector.
Received: October 11, 2022. Revised: March 29, 2023. Accepted: April 23, 2023. Published: May 5, 2023.
1 Introduction
The Chief Executive Officer (CEO) is the highest
executive officer in a company who has full
responsibility for the running of the company both
in theory and practice, [1]. The CEO is believed to
be able to influence the running of the company
which will affect the company's performance in
achieving company goals, namely maximizing
company value, [2]. Several previous studies
identified several determinants of the CEO on the
quality of decision making that affect the company's
performance.
The authors in [3] revealed that the CEO who
has a fairly high percentage of ownership in the
company will become a strong decision maker to
influence every step of the company. When the
CEO has a significant stake in the company he
leads, the CEO can influence the selection of other
boards of directors, so that he can make his position
higher than other boards of directors [4], including
educational background and experience. CEOs who
have a high educational background and experience
are likely to gain greater managerial skills and may
even be able to control the company even in the
worst conditions.
A previous study conducted by the authors in [5]
showed that CEO education is important for
corporate decisions, and the results of these
decisions reflect the quality of the CEO. Like
education, the experience of a CEO is inevitable
because they can change their instincts. Therefore,
the authors in [6] argued that education and
experience are two inseparable qualities for a good
manager with a high entrepreneurial drive. This is
because a higher level of education will increase the
probability of becoming a successful entrepreneur in
generating income in the sector.
It is different with the results of research
conducted by the authors in [7] which stated that the
experience of the CEO has a negative effect on
company performance. This is evidenced by CEOs
who have experience tend to have lower
performance compared to inexperienced CEOs
when placed in the highest executive positions in
new companies in the same industry as previous
companies. They provided the reason why this
happened as CEOs who have experience tend to
have responsibility for the decline in company
performance before they are appointed CEO.
Meanwhile, the National Energy Policy (KEN)
and the Paris Agreement are steps in Indonesia's
energy transition towards the use of new and
renewable energy. The government is committed to
reducing greenhouse gas (GHG) emissions using
new and renewable energy. There are five categories
of GHG emission sources, namely: energy,
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industrial processes and product use, agriculture,
forestry and other land use changes, and waste
management. The application of low-carbon
technology or decarbonization in the energy sector
is an implementation to achieve this target.
Therefore, research related to the performance of
mining companies is interesting because the
performance of mining companies is one of the keys
to the success of the government in implementing
KEN.
Therefore, the characteristics of the CEO become
crucial in the decision-making process that affects
the performance of the company itself. On the other
hand, the Indonesian government is currently
focusing on increasing the nation's energy
independence, so the role of mining sector
companies listed on the IDX is an important element
for the successful implementation of KEN. So that
the formulation of the problem in this study is
whether the characteristics of the CEO of mining
sector companies listed on the IDX affect the
company's performance improvement.
2 Literature Review and Hypothesis
Development
CEO is the highest position of a company and has
the duty to lead a company and is responsible for the
stability of the company, [8]. In addition, according
to the article of [9], the CEO who has high power
over the company he leads is the one who is able to
consistently determine important decisions in the
company, even though there are obstacles from
other executives.
Furthermore, ownership structure is an important
source of strength both theoretically and practically ,
[10]. CEO ownership in a company has a
relationship with various important decisions of
directors such as employee selection, determination
of remuneration members and so on, [11]. The
authors in [12] in their empirical study stated that
ownership is an important source of CEO power.
CEOs with strong ownership can maintain their
positions beyond the point of effectiveness, [13],
and in contrast to the study of [14] suggested that
CEOs with low ownership can be more easily
expelled by insider coalitions. Therefore, one way to
reduce agency costs is to increase management's
share ownership, [15]. The proportion of share
ownership by managers can influence company
policy. Managerial ownership will align the interests
of management and shareholders (outsider
ownership), so that they will benefit directly from
the decisions taken and bear the losses because of
the wrong decisions.
The formal educational background of members
of the board of commissioners and directors is a
cognitive characteristic that can affect the ability of
the board to make business decisions and manage
the business, [16]. The authors in [4] stated that the
level of education is a tool for consideration of
promotions and remuneration. A good level of
education has significance in increasing the prestige
of managers in terms of providing optimum
decisions, [17]. The higher the education taken, both
formal education according to the field of work, the
higher the intellectual experience possessed, [18].
Someone who has this intellectual experience tends
to be easy to carry out the work done. With a
person's educational experience, that person will
participate more in decision making and be able to
manage the company. With the education that has
been taken by the CEO, the CEO in making
decisions or policies is based on education that is
appropriate to his field. In this case, the CEO's
educational background can affect the knowledge
and skills possessed, so that it can indirectly affect
the results of the company's performance [4].
There are differences of opinion regarding the
appointment of a CEO whether it comes from the
company itself or from professionals outside the
company, [4]. He also explained that when an
employee of a company is promoted to CEO, it is
because of his special qualities and advantages over
other managers. The authors in [9] in their empirical
study stated that if a CEO who comes from a
company promotion is on the board of directors, he
will have more experience related to the company so
that he will be able to make more effective and
efficient decisions.
The company's performance is a description of
the company's financial condition, which is
analyzed with financial analysis tools, so that it can
be known the good and bad financial condition of a
company that reflects work performance in a certain
period, [8]. According to the study of [16] company
performance can be interpreted as a work
performance produced by a company based on
certain standards within a certain period. Company
performance usually describes the real conditions of
a company. Company performance is influenced by
good or bad corporate governance. The better
corporate governance will produce good
performance, otherwise the worse corporate
governance will result in poor performance.
Company performance is an important thing
because performance is the company's ability to
manage corporate governance. Furthermore,
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according to the study of [19] the profitability ratio
is a ratio used to measure the company's ability to
generate profits at a certain level of sales, assets,
and share capital which can be measured through
the ratio of profit margin, return on total assets
(ROA), and return. on equity (ROE).
The authors in [20] suggested that net margin is
one of the ratios used to measure profit margin on
sales, which is calculated by comparing net profit
after tax with net sales. This ratio can also be
interpreted as the company's ability to reduce costs
in the company in a certain period, [19]. The higher
the net margin ratio indicates the company's ability
to generate high profits at a certain level of sales,
and conversely, the lower this ratio means that sales
are too low for a certain level of costs or costs are
too high for a certain level of sales [21].
The next profitability ratio is Return on Assets
(ROA). ROA is a ratio used to measure the
company's management ability to earn profits by
utilizing the total assets owned, [22]. ROA measures
how effectively a company can convert its return on
investment into assets. The higher the ROA of the
company, the better.
ROA is one of the profitability ratios that
measures the effectiveness of the company in
generating profits by utilizing its assets. By knowing
this ratio, we can assess whether the company is
efficient in utilizing its assets in the company's
operational activities. This ratio also provides a
better measure of the company's profitability
because it shows the effectiveness of management
in using assets to earn income, [23].
Companies that have CEOs with high share
ownership tend to have higher stock market values,
which proves that agency conflict can be overcome
by including CEOs in the share ownership structure,
[24]. This is also evidenced by the empirical
research of [9] which stated that there is a positive
relationship between the power of the CEO on
company performance. This is indicated by the
company's performance will be more optimal when
the power in the company's decision making is
centered on the CEO's decision. Based on the
description above, the following hypothesis is made:
H1: CEO power has a positive effect on
company performance
CEOs in each company have different
educational backgrounds because there are no
definite rules about educational requirements to
become a CEO. However, CEOs who have a
graduate education background in management,
economics or business are expected to improve
managerial functions and can easily make the right
decisions to improve company performance.
Various empirical studies related to the CEO
background that can increase positive performance
have been carried out and stated that there is a
significant positive relationship between CEO
educational background and company performance,
[4] in his empirical research found that there is a
positive relationship between CEO educational
background and company performance. This is
because education is an important element that must
be contained in the CEO in making and
implementing decisions for the company. While the
authors in [16] stated that the educational
background of the CEO has an important role in
improving company performance, because the
education level of a CEO can prove the CEO's
connections and abilities which will ultimately have
an impact on company performance. Based on this
description, the following hypothesis is obtained:
H2: CEO educational background has a positive
effect on company performance
An employee who has special talents and good
performance for the company and has more
advantages compared to his colleagues in a
company can be promoted as CEO, [9]. CEOs who
come from the company's own employees when
compared to recruiting CEOs from non-companies
tend to further improve the company's performance
well, because it is believed that the CEO already has
more experience and knowledge about the company.
Furthermore, the authors in [3] stated that the
promotion of employees to become CEOs indicates
that the CEO has more power when compared to
other executives. From the description above, the
following hypothesis is obtained:
H3: CEO tenure has a positive effect on
company performance
3 Research Methods
The data used in this study is secondary data with a
data collection period of 2017-2021. The population
in this study are all Mining Sector companies that
are officially listed on the Indonesia Stock
Exchange (IDX) in the study period, namely 2017-
2021, while the sample of this study is Mining
Sector BUMN companies that are consistently listed
on the IDX in 2017-2021.
The analysis technique that will be used in this
research is panel data regression analysis technique,
which is a combination of cross-sectional data and
time series data. In panel data, observations were
made on several subjects which were analyzed from
time to time. To test the hypothesis (1), hypothesis
(2), and hypothesis (3) will be carried out using the
following Equation (1) model:
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Equation (1):
FPit = β0 + β1OWNit + β2EDUCit + β3TENit + eit
Where 𝐹𝑃
𝑖𝑡 is Firm performance ratio through
ROA in firm i and year t; OWNit is power ratio in
firm i and year t; EDUCit is CEO education
background in firm i and year t; TENit is CEO work
experience in firm i and year t; and 𝜀𝑡 = Error term.
Next is to test using panel data regression. In
panel data regression there are four models that can
be used. These models include the pooled OLS
model, the fixed effects least square dummy
variable (LSDV) model, the within-group fixed
effects model and the random effects model
(Gujarati and Dawn, 2013). The selection of the
model to be used is through a selection with a model
specification test. There are two specification tests,
namely fixed effects, or random effects.
The specification test is to determine the panel
data analysis model to be used through the Chow
Test, Hausmann Test, and Lagrange Multiplier
(LM) Test, [25]. Meanwhile, to test the linear
regression model, this study will apply the classical
assumption test so that the model becomes valid as
an estimator. Furthermore, the model built will also
be tested for feasibility or in this case will test each
hypothesis that has been built through simultaneous
significance tests (F-test) and individual parameter
significance tests (t-test), [25].
4 Results and Discussion
The analysis in this study begins with a description
of some basic statistical values for all tested
variables which are presented in Table 1. The
statistical descriptions that will be described are the
average, minimum, maximum and other values. The
average value for ROA in mining sector companies
in Indonesia is 7.22% during the research period.
This ROA percentage indicates that Mining Sector
companies are on average able to generate a positive
return to assets ratio amid unstable economic
conditions due to the Covid-19 Pandemic.
Furthermore, the average value of CEO power is
very low, which is only 0.6%, which means that
most CEOs do not have share ownership in the
companies they lead as a proxy for CEO power. The
average CEO education variable has a statistical
average of more than 50%, which indicates that
more than half of the COEs in the sample have a
postgraduate education level. The variable tenure of
CEOs in Indonesian Mining Sector companies is an
average of 6 years, which means that many
companies retain CEO leadership for more than 1
period. Meanwhile, the minimum ROA value is
negative 0.035100 and the maximum is 0.204. This
negative ROA value is believed to have occurred at
the peak of the Covid-19 case that occurred in 2020,
so that some companies were unable to generate
profits on their assets.
Table 1. Statistical Descriptive
ROA
CEO Power
CEO Tenure
Mean
0.072274
0.006348
6.395667
Median
0.062000
0.000000
3.433333
Maximum
0.204000
0.061800
28.00000
Minimum
-0.035100
0.000000
0.083333
Std. Dev.
0.064980
0.018326
7.448445
Skewness
0.660296
2.659305
1.761149
Kurtosis
2.513455
8.092677
5.291622
Jarque-Bera
4.126434
112.9645
36.78774
Probability
0.127045
0.000000
0.000000
Sum
3.613700
0.317400
319.7833
Sum Sq. Dev.
0.206900
0.016457
2718.488
Observations
50
50
50
Source: EViews 10 (data analysed)
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Table 2. Correlation between Variables
4.1 Chow Test
The Chow test is used to determine the best panel
data regression model among the models obtained
based on the common effect model (CEM) approach
with the model obtained using the fixed effect
model (FEM) approach, with the formulation of the
hypothesis:
H0: Common effect model
H1: Fixed effect model
The following are the results of the Chow test to
determine the best model between CEM and FEM.
\
Table 3. Results (Output) of the Chow Test
Source: Processed data (EViews 10)
Covariance Analysis: Ordinary
Date: 09/13/22 Time: 22:58
Sample: 2016 2020
Included observations: 50
Correlation
ROA
CEO Power
CEO
Education
CEO Tenure
ROA
1.000000
CEO Power
-0.076625
1.000000
CEO Education
-0.160452
0.307938
1.000000
CEO Tenure
-0.170972
0.199815
0.503192
1.000000
Redundant Fixed Effects Tests
Equation: Untitled
Test cross-section fixed effects
Effects Test
Statistic
d.f.
Prob.
Cross-section F
6.946138
(9,37)
0.0000
Cross-section Chi-square
49.469645
9
0.0000
Cross-section fixed effects test equation:
Dependent Variable: ROA
Method: Panel Least Squares
Date: 09/13/22 Time: 23:05
Sample: 2016 2020
Periods included: 5
Cross-sections included: 10
Total panel (balanced) observations: 50
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
0.086224
0.014397
5.988797
0.0000
CEO Power
-0.085632
0.539991
-0.158580
0.8747
CEO Education
-0.012045
0.022377
-0.538275
0.5930
CEO Tenure
-0.001041
0.001463
-0.711995
0.4801
R-squared
0.037174
Mean dependent var
0.072274
Adjusted R-squared
-0.025619
S.D. dependent var
0.064980
S.E. of regression
0.065808
Akaike info criterion
-2.527546
Sum squared resid
0.199209
Schwarz criterion
-2.374584
Log likelihood
67.18865
Hannan-Quinn criter.
-2.469297
F-statistic
0.592007
Durbin-Watson stat
0.611545
Prob(F-statistic)
0.623391
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From the output of the Chow test above, it can be
concluded that the probability value of cross-section
F and Chi-square is less than 0.05, or in other
words, H0 is rejected. Thus, from this Chow test the
FEM model is the chosen model. Therefore, we
continue to test the best model between FEM and
REM using the Hausman test.
4.2 Hausman Test
Hausman test is used to determine the best panel
data regression model among the models obtained
based on the random effects model (REM) approach
and the model obtained using the fixed effect model
(FEM) approach. The initial hypothesis was that
there was no relationship between the model error
and one or more explanatory variables, with the
formulation of the hypothesis as follows:
H0: Random effect model
H1: Fixed effect model
The following are the results of the Hausman test
to determine the best model between REM and
FEM.
Table 4. Hausman Test Output
Source: Processed data (EViews 10)
Correlated Random Effects - Hausman Test
Equation: Untitled
Test cross-section random effects
Test Summary
Chi-Sq.
Statistic
Chi-Sq. d.f.
Prob.
Cross-section random
2.485377
3
0.4779
Cross-section random effects test comparisons:
Variable
Fixed
Random
Var(Diff.)
Prob.
CEO Power
13.079092
-0.312782
538.928299
0.5640
CEO Education
0.028540
0.006136
0.000317
0.2081
CEO Tenure
0.005150
0.000048
0.000013
0.1505
Cross-section random effects test equation:
Dependent Variable: ROA
Method: Panel Least Squares
Date: 09/13/22 Time: 23:19
Sample: 2016 2020
Periods included: 5
Cross-sections included: 10
Total panel (balanced) observations: 50
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.059672
0.158392
-0.376737
0.7085
CEO Power
13.07909
23.24199
0.562735
0.5770
CEO Education
0.028540
0.032009
0.891621
0.3784
CEO Tenure
0.005150
0.004260
1.208851
0.2344
Effects Specification
Cross-section fixed (dummy variables)
R-squared
0.642019
Mean dependent var
0.072274
Adjusted R-squared
0.525917
S.D. dependent var
0.064980
S.E. of regression
0.044741
Akaike info criterion
-3.156939
Sum squared resid
0.074066
Schwarz criterion
-2.659813
Log likelihood
91.92348
Hannan-Quinn criter.
-2.967631
F-statistic
5.529787
Durbin-Watson stat
1.612625
Prob(F-statistic)
0.000027
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From the Hausman Test output above, it can be
concluded that the random cross-section probability
value is greater than 0.05, or in other words H0 is
accepted. Thus, from this Hausman test the REM
model is the chosen model.
From the results of the Chow test and Hausman
test on panel data regression, the statistically
recommended model is the Fixed Effect Model
(FEM). The FEM output is presented in more detail
as follows.
Table 5. Output FEM Model
Source: Processed data (EViews 10)
From the output above, the econometric model
formed is as follows:
FPit = -0.059672 + 13.07909*OWNit +
0.028540*EDUCit + 0.005150*TENit
The model formed above statistically has an R-
Squared of 64.2 percent, which identifies the three
independent variables tested have a relatively large
effect on the dependent variable ROA (company
performance) and has an F-statistical probability of
less than 0.05 which makes the FEM model a
significant model fit.
CEO's share ownership in mining sector
companies in Indonesia in this study shows a
statistically insignificant relationship with company
performance. The results of this study are different
from previous studies which stated that the greater
the CEO stock ratio, the greater the company's
performance, [9], [26], [27]. This is because in the
research sample companies only a few CEOs have
contributed share ownership in the company he
leads, so the percentage of share ownership does not
have a significant effect on company performance.
Dependent Variable: ROA
Method: Panel Least Squares
Date: 09/13/22 Time: 23:35
Sample: 2016 2020
Periods included: 5
Cross-sections included: 10
Total panel (balanced) observations: 50
Variable
Coefficient
Std. Error
t-Statistic
Prob.
C
-0.059672
0.158392
-0.376737
0.7085
CEO Power
13.07909
23.24199
0.562735
0.5770
CEO Education
0.028540
0.032009
0.891621
0.3784
CEO Tenure
0.005150
0.004260
1.208851
0.2344
Effects Specification
Cross-section fixed (dummy variables)
R-squared
0.642019
Mean dependent var
0.072274
Adjusted R-squared
0.525917
S.D. dependent var
0.064980
S.E. of regression
0.044741
Akaike info criterion
-3.156939
Sum squared resid
0.074066
Schwarz criterion
-2.659813
Log likelihood
91.92348
Hannan-Quinn criter.
-2.967631
F-statistic
5.529787
Durbin-Watson stat
1.612625
Prob(F-statistic)
0.000027
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The educational background of the CEO in this
study statistically has no significant effect on
company performance. This means that companies
with a bachelor's educational background
statistically have no effect on improving company
performance. This study contradicts previous
research conducted by [16] and [28] in which the
authors stated that CEOs who have a master's
educational background and doctors can
significantly improve the company's performance.
This study found that CEO's length of service
had no effect on company performance. The CEO
who has led the company for a long time does not
mean that it will increase the value of the company.
This result contradicts the findings of [29] in which
the authors stated that a CEO who has led an
organization for a long time will tend to have a
higher level of knowledge of the culture and
operations of the company, so that he will be able to
make a more effective contribution to improving
company performance. However, our research
supports the results of research by the authors in
[30] which stated that investors tend to choose
companies with shorter CEO tenures on the grounds
that these companies have a better level of financial
stability. Likewise (Nguyen et al., 2018) which
describes long service CEOs as having no influence
on developing companies.
5 Conclusion
The National Energy Policy (KEN) and the Paris
Agreement are steps in Indonesia's energy transition
towards the use of new and renewable energy. The
government is committed to reducing greenhouse
gas (GHG) emissions using new and renewable
energy. Therefore, the role and background of CEOs
in mining companies in Indonesia are crucial in
improving company performance. This study found
that CEO's work experience and CEO's Strength and
CEO's education level did not significantly
influence the performance of mining sector
companies in Indonesia.
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DOI: 10.37394/23207.2023.20.87
Ribhan, Aripin Ahmad, Ra Fiska Huzaimah
E-ISSN: 2224-2899
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Volume 20, 2023
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
-Ribhan carried out the concept study and was
responsible for discussion section as well as made
revisions.
-Aripin Ahmad conducted data collection
and analysis.
-R. A. Fiska Huzaimah was in charge of the
literature reviews and methods.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflict of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.87
Ribhan, Aripin Ahmad, Ra Fiska Huzaimah
E-ISSN: 2224-2899
950
Volume 20, 2023