Liyanita Dewi Kurnia, Christina Dwi Astuti
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282
JoSS:
Journal of Social Science
THE EFFECT OF CORPORATE GOVERNANCE MECHANISMS ON FINANCIAL
DISTRESS
Liyanita Dewi Kurnia
1
, Christina Dwi Astuti
2
Universitas Trisakti Jakarta Indonesia
[email protected]
KEYWORDS
independent
commissioners,
audit committee,
institutional
Ownership has a
financial distress
ARTICLE INFO
Accepted:
03 February 2023
Revised:
12 February 2023
Approved:
14 February 2023
ABSTRACT
The purpose of this study is to analyze the effect of corporate governance
mechanisms on the likelihood of financial distress In this study, the authors
were interested in examining how institutional ownership, independent
commissioners and audit committees affect financial distress. The
population of all manufacturing companies listed on the Indonesia Stock
Exchange from 2018 to 2021 amounted to 106 samples, according to the
criteria needed in this study, only 19 companies were sampled for 2018 to
2021. The results showed that the Board of Directors had a significant
positive influence on financial distress, the proportion of independent
commissioners had an insignificant effect on financial distress, the size of
the audit committee had an insignificant effect on financial distress, and
institutional ownership had a significant negative effect on financial
distress.
INTRODUCTION
Financial Distress is the level of financial difficulty of the company with indications of
a decrease in the company's internal financial performance and can result in bankruptcy
(Rizaky and Dillak 2020). If this bankruptcy occurs, it will undoubtedly affect investors
because they have invested their capital and do not get the right return. And, of course, the
economy will also experience a decline because many employees end up having to be
unemployed due to company bankruptcy. This is what finally makes researchers aware of the
importance of financial Distress as a warning to avoid bankruptcy. Companies that
experience delisting on the Indonesia Stock Exchange are one of the signs financial
difficulties . Based on data from the Indonesia Stock Exchange in the range of 2018 to 2020,
there are still companies that have experienced delisting. In 2018 there were four companies
that experienced delisting. In 2019, there was an increase of 6 companies, and in 2020 there
were also six companies.
One of the companies that experienced delisting was PT. Borneo Lumbung Energi dan
Metal Tbk (BORN). Based on an announcement from the Indonesia Stock Exchange with
the number Peng-SPT-00009/IDX. PP1/05- 2019 stated that it temporarily suspended trading
of shares of PT. Borneo Lumbung Energi dan Metal Tbk. as of May 09, 2019. By reason of
any indication of doubt going concerned in PT. Borneo Lumbung Energi dan Metal Tbk. In
terms of performance, until September 2018, sales of PT. Borneo Lumbung Energi dan Metal
Tbk. Declined by 92%. Where the sales figures in September 2018 ranged at US$ 16.11
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The Effect Of Corporate Governance Mechanisms On Financial
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283
million from September 2017, which reached US$ 194.64$. As a result of this decline in
sales, PT. Borneo Lumbung Energi dan Metal Tbk. posted a net loss of US$ 8.06 million,
which in the previous year still scored a profit of US$ 56.75 million (Saleh and Teich 2019).
Then on December 16, 2019, based on an announcement by the Indonesia Stock Exchange
with the number Peng-UPT-00010 / IDX. PP1/12-2019 conveyed the lifting of the temporary
suspension of stock trading for only up to 20 days starting from December 17, 2019, along
with the IDX decision with the number Peng-DEL-00003/IDX. PP1/12-2019 to delist PT.
Borneo Lumbung Energi dan Metal Tbk., which became effective on January 20, 2020, due
to the company's condition experiencing conditions that significantly negatively affected the
company's business continuity, and the company could not show adequate indications of
recovery (Malau and Murwaningsari 2018). Delisting is carried out to minimize the
possibility of increasingly significant losses experienced by investors and the company itself.
This proves that there are still some companies that have not been able to manage their
company correctly, which in the end, puts the company in a state of financial difficulty which
is an early warning system for companies that will experience bankruptcy.
In this study, internal factors that affect financial Distress are corporate governance
which consists of several indicators, including the commissioner of institutional Ownership,
the size of the audit committee, and the independent commissioner. The number of
commissioners in a company has an important role because it supervises the management of
the company and is responsible to shareholders (Amanda and Tasman 2019).
METHOD RESEARCH
The research method in this study is a quantitative research method. The type of data
used in this study is secondary data that is quantitative in nature. Secondary data are obtained
from corporate documentation, books, and scientific journals. (Sugiono and Rachmawati
2019). The population that is the object of this study is all transportation sector companies
listed on the Indonesia Stock Exchange (IDX) during the 2018-2021 period. Sample selection
was carried out by purposive sampling so as to obtain a sample of 19 companies or 76
observations (the number of companies selected multiplied by four years of the observation
period). Sample data were processed using Statistics Program for Social Science (SPSS)
version 23 (Wolk, Dodd, and Rozycki 2016).
Financial Distress
The condition of financial Distress can be seen from the following: the company's
performance continues to decline, the company's inability to pay off its obligations, the absence
of dividend distribution to shareholders, cash flow problems in the company, difficulties in
terms of liquidity, termination of labour by the company, poor corporate governance, increase
in the composite stock price index, inflation and exchange rates (Theresa and Pradana 2022).
Dependent variables are measured with the Grover measurement model. (Hartianah and
Sulasmiyati 2017).
The grover model equation includes: S = 1.650X1 + 3.404X3 – 0.016ROA + 0.057
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Bound Variables (Independent)
1. Institutional Ownership
A number of shares belonging to the commissioners as well as the board of directors, the
meaning of managerial share ownership. This variable is shown using the percentage of
shares owned by the institution (Pasaribu and Sulasmiyati 2016). KEP. INS= (Number of
institutional shares)/(Total shares outstanding)
2. Independent Commissioner
Independent commissioners are members of the board of commissioners who do not have
any relationship with the company's managerial party. Independent commissioners are
measured using the percentage of members with the total commissioners of the company
(Damayanti and Kusumaningtias 2020). KOM_INDEP= (Number of Independent
Commissioners)/(Number of Commissioners) x 100%
3. Audit Committee
The competence of the audit committee is one of the important characteristics to
ensure that the audit committee carries out its duties effectively. Strengthening supervision
related to financial statements, risk management, and governance implementation is also
connected to the implementation of audits for companies the meaning of the audit
committee (Damayanti and Kusumaningtias 2020). The measurement of the audit
committee is the total of all members of the audit committee in the t period (Hartantri and
Hatane 2017). KOM_AUDIT= ∑ Audit Committee Period t
4. Company Size
The size of the company is a variable that describes the size of the company. Firm
Size is used to determine large and small companies in this study by means of average total
assets. If the results are above the average, it is classified as a large company. If it is below,
then it is said to be a small company (Hartantri and Hatane 2017). Meanwhile, the definition
of company size, according to Putu Ayu and Gerianta (2018), states that company size is a
scale where the size of the company can be classified as measured by total assets, number
of sales, value of shares, and so on. Company size = Ln (Total Assets)
RESULT AND DISCUSSION
Data Description
The population that is the object of this study is all transportation sector companies listed
on the Indonesia Stock Exchange (IDX) during the 2018-2021 period. Sample selection was
carried out by purposive sampling so as to obtain a sample of 19 companies or 76 observations
(the number of companies selected multiplied by four years of the observation period). Sample
data were processed using Statistics Program for Social Science (SPSS) version 23 (Scott
2015).
Descriptive Statistical Analysis
Table 1
Overall Descriptive Statistics of the Sample
N
Minimum
Maximum
Mean
Std.
Deviation
DD
76
2,000
8,000
4,263
1,635
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PKI
76
0,200
1,000
0,415
0,175
KA
76
3,000
4,000
3,092
0,291
KEPINST
76
35,820
96,760
72,031
16,317
DISTRESSED
76
0,000
1,000
0,4736
0,502
VALID N
(listwise)
76
Source: Data Processed
The table above shows that the number of observations in this study within the 2018-
2021 period was 76 observations from 19 company samples. The largest standard deviation is
found in the Institutional Ownership variable (KEPINST) of 16,317. This standard deviation
shows that the data used from these variables is not too clustered around the average. And the
lowest standard deviation is found in the variable Proportion of Independent Commissioners
(PKI) of 0.175.
This study's Financial Distress (DISTRESSED) variable has a minimum value of 0, a
maximum value of 1, a mean or average value of 0.4736, and a standard deviation of 0.502.
The Dieksi Council Variable (DD) has a minimum value of 2,000, a maximum value of 8,000,
a mean value of 4,263, and a standard deviation of 1,635. The Variable Proportion of
Independent Commissioners (PKI) has a minimum value of 0.200, a maximum value of 1.000,
a mean value of 0.415, and a standard deviation of 0.175. The Audit Committee (KA) variable
has a minimum value of 3,000, a maximum value of 4,000, a mean value of 3,092, and a
standard deviation of 0.291. The Institutional Ownership Variable (KEPINST) has a minimum
value of 35,820, a maximum value of 96,760, a mean value of 72,031, and a standard deviation
of 16,317.
Table 2
Descriptive Statistics of Financial Distress Company Samples
N
Minimum
Maximum
Mean
Std.
Deviation
DD
36
2,000
8,000
4,944
1,689
PKI
36
0,200
0,500
0,368
0,077
KA
36
3,000
4,000
3,083
0,280
KEPINST
36
35,820
86,453
67,174
15,193
DISTRESSED
36
1,000
1,000
1,000
0,000
VALID N
(listwise)
36
Source: Data Processed
The table above shows a descriptive statistical table of a sample of companies with the
category of Financial Distress. The number of observations in table 4.3 was 36 observations
from 19 company samples. The Board of Directors (DD) variable has a minimum value of
2,000, a maximum value of 8,000, a mean value of 4,944, and a standard deviation of 1,689.
The Variable Proportion of Independent Commissioners (PKI) has a minimum value of 0.200,
a maximum value of 0.500, a mean value of 0.368, and a standard deviation of 0.077. The
Audit Committee (KA) variable has a minimum value of 3,000, a maximum value of 4,000, a
mean value of 3,083, and a standard deviation of 0.280. The Institutional Ownership Variable
(KEPINST) has a minimum value of 35,820, a maximum value of 86,453, a mean value of
67,174, and a standard deviation of 15,193 (Handriani, Ghozali, and Hersugodo 2021).
The Effect Of Corporate Governance Mechanisms On
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Table 3
Descriptive Statistics of Samples of Non-Financial Distress Companies
N
Minimum
Maximum
Mean
Std.
Deviation
DD
40
2,000
6,000
3,650
1,331
PKI
40
0,200
1,000
0,457
0,222
KA
40
3,000
4,000
3,100
0,303
N
Minimum
Maximum
Mean
Std.
Deviation
KEPINST
40
39,860
96,760
76,402
16,232
DISTRESSED
40
0,000
0,000
0,000
0,000
VALID N
(listwise)
40
Source: Data Processed
The table above shows a descriptive statistical table of a sample of companies with the
category of Non-Financial Distress. The number of observations in table 3 was 40 observations
from 19 company samples. The Board Dieksi (DD) variable has a minimum value of 2,000, a
maximum value of 6,000, a mean value of 3,650, and a standard deviation of 1,331. The
Variable Proportion of Independent Commissioners (PKI) has a minimum value of 0.200, a
maximum value of 1.000, a mean value of 0.457, and a standard deviation of 0.222. The Audit
Committee (KA) variable has a minimum value of 3,000, a maximum value of 4,000, a mean
value of 3,100, and a standard deviation of 0.303. The Institutional Ownership Variable
(KEPINST) has a minimum value of 39,860, a maximum value of 96,760, a mean value of
76,402, and a standard deviation of 16,232.
Based on tables 1, 2, and 3, it can be concluded that the size of the Board of Directors
(DD) shows that the average (mean) size of the Board of Directors in companies that experience
Financial Distress is greater than that of companies that do not experience Financial Distress.
The variable proportion of Independent Commissioners shows that the average (mean)
Proportion of Independent Commissioners in companies that do not experience Financial
Distress is greater than that of companies that experience Financial Distress. The Audit
Committee (KA) variable shows that the average (mean) number of Audit Committees in
companies that do not experience Financial Distress is greater than that of companies that
experience Financial Distress. The Institutional Ownership Variable (KEPINST) shows that
the average (mean) Institutional Ownership in companies that do not experience Financial
Distress is greater than that of companies that experience Financial Distress (Darmiasih,
Endiana, and Pramesti 2022).
Regression Model Feasibility Test
Table 4
Hosmer & Lemeshow's Test Results
Step
Chi-Square
df
Sig
1
8,007
8
0,
433
Source: Data Processed
The table above shows that the value of the Hosmer & Lemeshow's Goodness of Fit Test
Chi-square value is 8.007 with a significance of 0.433. With a significance value greater than
the α level of 0.05, the regression model is feasible to use in its next analysis, since there is no
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noticeable difference between the predicted and observed classifications. In other words, a
model is acceptable because it matches its observational data.
Table 5
Test Result -2 Log likelihood (block number 1 result)
Iteration
-2 Log Likelihood
Step 1 1
87,357
2
86,896
3
86,893
4
86,893
Source: Data Processed
Testing on block number 0, where the logistic regression model only has a constant,
obtained an initial Log Likelihood value of -2 of 105.148. When compared to the value of -
2Log Likelihood in block number 0 with block number 1, the value has decreased until it
reaches -2Log Likelihood in the fourth iteration of 86.893 in block number 1. The decrease in
the value of -2 log-likelihood allows for a relationship between an independent variable and its
dependent variable (Shidiq and Khairunnisa 2019).
The decrease in the value of -2 log-likelihood is presented in the chi-square value in the
omnibus test of the model coefficient as follows.
Table 6
Omnibus Test of Model Coefficient Results
Chi-Square
Df
Sig.
Step 1 Step
18,255
4
0,001
Block
18,255
4
0,001
Model
18,255
4
0,001
Overall regression coefficient testing of four independent variables as a whole was
performed using the omnibus test of the model coefficient. The results of the omnibus test
obtained a chi-square value (decrease in the value of -2 log-likelihood) of 18.255 with a
significance level of 0.001. This value is smaller than the α level of 0.05, indicating a significant
influence of the four independent variables, namely the Board of Directors, Proportion of
Independent Commissioners, Audit Committee, and Institutional Ownership together, can
explain the occurrence of Financial Distress in the company (Suteja 2018).
Table 7
Cox and Snell's R Square and Nagelkerke's R Square Test Results
Step
-2 Log
Likelihood
Cox & Snell R Square
Nagelkerke
R Square
1
86,893
a
0,214
0,285
Table 8
Classification
Observed
Predicted
Distressed
Percentage
Correct
0,00
1,00
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Step 1 Distressed 0,00
27
13
67,5
1,00
13
23
63,9
Overall Percentage
65,8
The table above shows that of the 40 companies that did not experience Financial
Distress, 24 companies, or 67.5%, could be correctly predicted by this logistic regression
model, while 16 companies or 32.5%, did not match the estimates. Then of the 36 companies
that experienced Financial Distress, 22 companies, or 63.9%, could be predicted precisely by
this logistic regression model, and 14 companies or 36.19% of their observations did not match
their estimates. Overall means 50 samples from 76 samples, or 65.8% of samples, can be
predicted precisely by this logistic regression model (Prihatini and Purbawati 2021).
Pengujian Hipotesis
Tabel 9
Hasil Pengujian Hipotesis
B
S.E
Wald
df
Sig
Exp(B)
Step 1
a
X1
1,457
0,719
4,105
1
0,043
4,291
X2
-3,438
2,297
2,240
1
0,135
0,032
X3
5,893
4,821
1,494
1
0,222
362,630
X4
-3,733
1,661
5,048
1
0,025
0,024
Constant
-4,659
4,962
0,882
1
0,348
0,009
Based on the hypothesis testing table above, it can be seen that the significance value of
the Institutional Ownership variable (X4) is the smallest, with a value of 0.025. This shows that
the Institutional Ownership variable has the greatest influence on Financial Distress of all the
variables studied (Prihati and Khabibah 2022).
The variable size of the Board of Directors (DD) obtained a coefficient value of 1.457,
meaning that for each unit of increase in the size of the Board of Directors (DD), then the
company's Financial Distress increases by 1.457, assuming other independent variables are
considered constant. This Board of Directors size variable has a significance value of 0.043. A
significance value below 0.05 with a positive coefficient value indicates a significant influence
on the direction of the positive relationship of the Board of Directors (DD) variable to Financial
Distress, so H1 is accepted.
For the variable proportion of Independent Commissioners (PKI), a coefficient value of
-3.438 is obtained, meaning that each unit of increase in the proportion of Independent
Commissioners (PKI) will reduce the company's Financial Distress by 3,438 assuming other
independent variables are considered constant. However, the proportion variable of the
Independent Commissioner has a significance value of 0.135. A significance value above 0.05
indicates an insignificant influence of the variable Proportion of Independent Commissioners
on Financial Distress, so H2 is rejected.
For the Audit Committee (KA) variable, a coefficient value of 5.893 is obtained, meaning
that each unit of increase in the size of the Audit Committee will reduce the company's
Financial Distress by 5,893, assuming other independent variables are considered constant.
This Audit Committee (KA) variable has a significance value of 0.222. A significance value
above 0.05 indicates an insignificant influence of the Audit Committee (KA) variable on
Financial Distress, so H3 is rejected.
For the Institutional Ownership variable (KEPINST), a coefficient value of -3.733 is obtained,
meaning that each unit of increase in Institutional Ownership will reduce the company's
Financial Distress by 3,733, assuming other independent variables are considered constant.
This Institutional Ownership Variable (KEPINST) has a significance value of 0.0425.
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Significance values below 0.05 and negative coefficients indicate a significant influence with
the direction of the negative relationship of the Institutional Ownership variable (KEPINST)
on Financial Distress, so H4 is accepted.
Effect of Board of Directors' Size on Financial Distress
The regression result value in table 4.9 for the Board of Directors size variable has a
positive coefficient value of 1.457. Thus, a company that has a larger Board of Directors size,
the greater the company will experience Financial Distress. The significance value for this
variable based on the logistic regression results in table 4.9 is 0.043. The significance value is
smaller than 0.05, so it can be concluded that the Board of Directors variable size significantly
influences the direction of a positive relationship to Financial Distress (Maghfiroh and Isbanah
2020).
These results support research from (Alexandra et al. 2022) which shows that the larger
the members of the Board of Directors, the greater the Likelihood of Financial Distress in the
company. A large number of the Board of Directors can affect the financial condition because
every decision result carried out by the company comes from the results of the decisions of the
Board of Directors. Companies that experience great financial stress usually require
consideration of the company's financial state from the directors. So, it is better for companies
that are experiencing financial difficulties to use the proportional amount of the average board
to suppress the occurrence of financial difficulties in a company.
Effect of Proportion of Independent Commissioners on Financial Distress
The regression result value for the Independent Commissioner Proportion (PKI) variable
has a negative coefficient value of -3.438. Thus, it means that companies with a larger
proportion of Independent Commissioners (PKI) will experience Financial Distress will
decrease or get smaller. However, the Proportion of Independent Commissioners (PKI)
variable has a significance value of 0.135. The value is greater than 0.05, so it can be concluded
that the Proportion of Independent Commissioners has an insignificant influence on Financial
Distress. This means that regardless of the Proportion of Independent Commissioners in a
company, the Likelihood of the company experiencing financial stress is the same (Rahmawati
and Khoiruddin 2017).
The insignificant relationship between the Proportion of Independent Commissioners and
the company's Financial Distress condition shows that the existence of an Independent
Commissioner has not been able to act as an effective supervisory mechanism to prevent the
company from financial Distress. This is supported by research (Damayanti and
Kusumaningtias 2020).
Effect of Audit Committee Size on Financial Distress
The regression result value for the Audit Committee (KA) variable has a negative
coefficient value of 5.893. Thus, it means that companies that have an Audit Committee (KA)
that is getting bigger, the company will experience Financial Distress will be smaller. However,
the Audit Committee (KA) variable has a significance value of 0.222. The value is greater than
0.05, so it can be concluded that the Audit Committee has an insignificant influence on
Financial Distress. This is supported by research) (Manan and Hasnawati 2022).
The Effect of Institutional Ownership on Financial Distress
The regression result value for the Institutional Ownership variable (KEPINST) has a
negative coefficient value of -3.733. Thus, for companies with larger Institutional
Ownership, the company experiences Financial Distress will decrease or get smaller. The
significance value for this variable based on the regression results is 0.025. The value is
smaller than 0.05, so it can be concluded that the Institutional Ownership variable
(KEPINST) significantly influences the direction of the negative relationship to Financial
Distress. This can also be seen from the average Institutional Ownership in companies that
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experience financial difficulties, which is 67,174 lower than the average institutional
Ownership in companies that do not experience financial difficulties, which is 76,402. This
research is supported by researchers (Adiyanto 2021).
CONCLUSION
Based on the results of the analysis and discussion, it can be concluded that the Board of
Directors has a significant favourable influence on Financial Distress, the Proportion of
Independent Commissioners has an insignificant effect on Financial Distress, the Size of the
Audit Committee has an insignificant effect on Financial Distress, and Institutional
Ownership has a significant negative effect on Financial Distress. and This study uses only
four variable controls that affect financial Distress: the size of the board of directors, the
proportion of independent commissioners, the size of the audit committee and institutional
Ownership. And also, researchers do not involve many sectors in manufacturing companies
listed on the Indonesia Stock Exchange.
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