Research Article | Volume 5 Issue 2 (April-June, 2024) | Pages 1 - 7
The Influence Of Financial Distress, Firm size, And Leverage On Earnings Management With Industry Type As A Moderating Variable In Affected Companies Covid-19
 ,
 ,
1
Master of Accounting, Postgraduate Program, Faculty of Economics and Business, University of Jember, Indonesia
Under a Creative Commons license
Open Access
Received
July 15, 2024
Revised
Aug. 17, 2024
Accepted
Sept. 19, 2024
Published
Nov. 25, 2024
Abstract

This research aims to empirically test and analyze whether financial distress, company size, leverage influence earnings management with industry type as a moderating variable in industries affected by COVID-19. This research uses a quantitative type of research. The population in this research is the quarterly reports of companies in the health, information and communications, transportation and logistics sectors as well as accommodation and food/drinks registered on the IDX in 2020-2022 during the COVID-19 pandemic. The number of samples used in this research was 63 companies obtained through purposive sampling. The data analysis methods used are multiple linear regression and Moderated Regression Analysis (MRA). The results of this study show that financial distress and leverage have a significant positive effect on earnings management. The research results also show that financial distress and leverage on earnings management which are moderated by industry type show a significant positive influence. Meanwhile, company size on earnings management shows an insignificant influence.

Keywords
INTRODUCTION

Financial reports are used as a means of communication between internal parties (the company) and external parties (investors). Management has been given the trust to operate the company well [1] Of the large amount of information presented, profit information is a component that is the center of attention in financial reporting for decision making.

In Indonesia, there are several cases of earnings management. [2] wrote down several earnings management practices carried out by companies in Indonesia from 2016-2019. In 2016 PT Hanson Internasional Tbk recognized income which caused overstated financial statements. In 2017 PT Tiga Pilar Sejahtera Food Tbk inflated its revenue and EBITDA. In 2018 PT Garuda Indonesia recognized income from Mahata even though the income was still in the form of receivables or bills for Garuda Indonesia. In the same year, namely 2018, PT Sunprima Nusantara Pembinaan (SNP Finance) failed to pay MTN interest. In 2018, what PT PLN did was that the compensation income post did not appear on the 2017 financial balance but was recorded in the compensation income account. In 2018, Bank Bukopin revised the allowance for impairment losses on financial assets, causing the company's expenses to increase. In 2019 PT Bank Maybank Indonesia Tbk increased its net profit due to an increase in provisions.

 

Coronavirus Disease Of 2019 (COVID-19) was designated by WHO as a Global Pandemic since March 11 2020. COVID-19 was also designated as a public health emergency according to Presidential Decree No. 11 of 2020 and a non-natural disaster according to Presidential Decree No. 12 of 2020. Determination of status The pandemic only ended after the President issued Presidential Decree No. 17 of 2023 which was stipulated on June 21 2023. Pandemic COVID-19 is disrupting the economy because business and daily activities are hampered [3]. This impact was also experienced by Indonesia, where Indonesia's economic growth experienced a decline due to a decline in GDP from various sectors, especially the transportation and warehousing sector which fell by -15.05% and accommodation and food/drinks fell by -22.02%. However, not all sectors experienced a decline due to the COVID-19 pandemic, one example is the health sector which recorded rapid growth during the COVID-19 pandemic. The Central Statistics Agency (BPS) health sector in 2020 grew 11.56% followed by the information and communication sector grew by 10.61%.

Earnings management can occur due to several factors, including financial distress, firm size, leverage and industry type. [4,2] show that financial distress has a significant effect on earnings management. This is different from research conducted [5,6] which shows that financial distress does not have a significant effect on earnings management.

Apart from financial distress, earnings management is influenced by firm size, because a large company must be able to maximize the expectations of investors and shareholders [7]. Firm size is defined as a comparison of the size of an object [8]. Firm size will influence the funding structure of a company. Research conducted [9,10] states that firm size influences earnings management. These results are inversely proportional to research conducted [6] which states that firm size has no significant effect on profit management..

Leverage also affects earnings management. According to [11] leverage is measuring how much a company is financed with debt. The research results of [7] states that leverage has a positive effect on earnings management. The results of this research are different from who stated that leverage has no effect on earnings management. 

One thing that influences earnings management is the type of industry. According to [12] this type of industry is a business activity or company activity that produces goods or services and is bought and sold by companies to gain profits for the continuity of a company. [13] shows that the type of industry influences earnings management. This is different from the research results of [14] which stated that industrial diversification does not have a significant effect on profit management.. 

Based on the results of previous studies, there are still inconsistencies in the research results. Therefore, researchers want to conduct research on the influence of financial distress, firm size, leverage and industry type on earnings management. The research objects used are companies that are included in industries that have been positively and negatively affected by the COVID-19 pandemic. The researcher's reason is that the COVID-19 pandemic has had an impact on the condition of companies in various sectors. This impact not only has a negative impact where companies experience financial chaos, but there are also several sectors that experience a positive impact due to the COVID-19 pandemic. This research also adds an independent variable, leverage and a moderating variable, industry type.

LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

Agency Theory

Agency theory, also known as agency theory, was introduced [15] According to Jensen & Meckling, agency theory is a relationship involving two parties, namely the agent and the principal. Agency theory is based on the dissimilarity of interests held and is the basis for the views between the agent and the principal. According to [16] in agency theory, agency exists due to a contract from the party giving the order to the party given the order to carry out their duties.

Conflicts of interest can arise between managers and the government, society, and the media that highlights the company. This conflict is what underlies the emergence of the political cost hypothesis. Political costs are company political costs that arise from conflicts of interest between managers and the government, society, and the media that highlight the company. The political cost hypothesis explains that large companies are predicted to be more sensitive to political costs than small companies [17]

 

Signalling Theory 

Signaling theory is a signal given by management to convey relevant information about financial reports so that it is used for decision making by external parties to the company. Signaling theory shows the importance of companies providing information to the public, because this theory provides assumptions regarding the existence of information asymmetry that occurs between managers and investors or creditors. Signal theory discusses how the agent's signals of success or failure should be conveyed to the principal [18]

 

Hypothesis

[16] explain that financial distress has a significant effect on earnings management. The COVID-19 pandemic means that companies that experienced financial distress before the pandemic will have a more severe level of financial distress. Fitriyah et al.'s research. (2022) shows that the financial condition of the transportation and tourism sector has experienced a decline in financial health since the onset of COVID-19 and has experienced an increase in the level of distress and its safe position has decreased.. 

H1: Financial distress affects earnings management

Firm size is related to the size of the company which is measured based on total assets. According to research results from [10], firm size influences earnings management. This is in line with the results of Tsaqif's (2021) research that firm size has a negative effect on earnings management. During the COVID-19 pandemic, it could be said that companies with large sizes were able to stabilize. [19] stated that before the pandemic, firm size had a negative effect and during the pandemic it had a positive effect on financial performance.

H2: Firm size influences earnings managementLeverage can be calculated using the ratio of debt to assets. [20] found that leverage has an effect on earnings management. The COVID-19 pandemic of course has an impact on companies, because companies may be 'unprepared' to face the effects and for an undetermined time period. [21] states that leverage has a significant effect on earnings management during the COVID-19 pandemic. state that the DER ratio influences earnings management before and during the COVID-19 pandemic.

 

H3: Leverage influences earnings management

The type of company industry refers to the type of operations carried out by the company, each particular type of industry can require a level of expertise and require more time and effort than other types of industry [22,13] show that the type of industry influences earnings management. 

 

H4: Financial distress's effect on earnings management is moderated by industry type

Large companies that have more complex operational activities can give rise to earnings management practices compared to smaller companies [9] state that industry type, managerial ownership, operating profit margin, and dividend payout ratio together influence profit smoothing in companies listed on the Indonesia Stock Exchange in 2012-2014. [23] research also states that industry classification has an effect on earnings management.

 

H5: Firm size influences earnings management, moderated by industry type

The greater the leverage, the greater the risk the owner will face. [21] states that leverage has a significant effect on earnings management during the COVID-19 pandemic. [13] show that the type of industry influences earnings management.

H6: Leverage's effect on earnings management is moderated by industry type.

RESEARCH METHODS

This research is quantitative research which aims to test predetermined hypotheses or test the relationship between variables [24]. This research uses an explanatory research method which aims to explain the relationship between the variables studied, as well as the influence between one variable and other variables. The data used in this research was obtained via the website (www.idx.co.id) in the form of quarterly financial reports of companies in the health, information and communications, transportation and logistics sectors as well as accommodation and food/drinks listed on the IDX during 2020-2022. The sample in this study was determined using the purposive sampling method. The total number of companies in the sample was 63 companies. There are 12 health sector companies, 9 information and communications sub-sector companies, 34 food/beverage sub-sector companies, and 8 transportation and logistics sector companies.

RESULTS AND DISCUSSION

Result

Descriptive Statistics 

Descriptive Statistics in [25] explains that descriptive statistics provides a description or description of data seen from the average value (mean), standard deviation, variance, maximum, minimum, sum, range, kurtosis, and skawness (skewness of distribution). ). The results of descriptive statistical data processing for research variables appear in Table below:

Table 1

Descriptive Statistics Results

Research Variable 

N

Min

Max

Mean

Deviation Standard

Financial Distress (X1)

189

-3,58

3,27

-0,22

1,34

Firm Size (X2)

189

28,98

34,93

31,40

1,32

Leverage (X3)

189

0,15

17,07

2,16

2,90

Type industry (Z)

189

1

2

1,79

0,40

Earning Management (Y)

189

-6,37

2,94

0,34

1,77

Source: Data is processed, 2024.

 

Classical Assumption Test

Data Normality Test

This test aims to test whether in a regression model, the confounding variable (error) or residual has a normal distribution [25]. In this study, to test the normality of residuals using the non-parametric Kolmogorov-Smirnov statistical test. If asymp.sig>0.05 means the sample data taken is normally distributed and conversely if asymp.sig<0.05 means the sample data taken is not normally distributed [25]. The results of the normality test are as follows:

Table 2 Data Normality Test Result

Variabel

Nilai Kolmogorov Smirnov

Keterangan

Unstandardized Residual

0,200

Berdistribusi Normal

Source: Data is processed, 2024

Autocorrelation Test

The autocorrelation test aims to determine whether in the linear regression model there is a correlation between confounding errors in period t and confounding errors in period t-1. In this research, to test whether there are symptoms of autocorrelation, the Durbin Watson (DW) Test is used. The results of the autocorrelation test are as follows: 

Table 3 Autocorrelation Test Result 

DU

Nilai Durbin-Watson

4-DU

Keterangan

1,805

1,844

2,195

Tidak terjadi auotokorelasi

Source: Data is processed, 2024

Multicollinearity Test

This test aims to test whether in a regression model a correlation is found between independent variables. Whether there is multicollinearity or not can be done by analyzing the correlation matrix of the independent variables, there is a fairly high correlation (generally above 0.90). The multicollinearity test can also be seen from the tolerance value and Variance Inflation Factor (VIF). In general, the cutoff value used to indicate the presence of multicollinearity is a tolerance value of less than 0.10 or the same as a VIF value of more than 10 [25]. The results of the multicollinearity test are as follows:

 

Variabel 

Collinearity Statistics

Keterangan

Tolerance

VIF

Financial Distress (X1)

0,121

4,256

Non-multicollinearity

Firm Size (X2)

0,837

1,195

Non-multicollinearity

Leverage  (X3)

0,441

2,266

Non-multicollinearity

Type Industry (Z)

0,119

4,411

Non-multicollinearity

Moderated 1 (X1.Z)

0,126

7,950

Non-multicollinearity

Moderated 2 (X2.Z)

0,583

1,714

Non-multicollinearity

Moderated 3 (X3.Z)

0,128

4,784

Non-multicollinearity

Source: Data is processed, 2024

 

Heteroscedasticity Test

In the regression model, the heteroscedasticity test is carried out to determine whether there is inequality in the residual variations. If the residual variation from one observation to another is constant, it is called homoscedasticity, whereas if the variation changes and is different. Homoscedasticity or the absence of heteroscedasticity is a sign of a good regression model [25]. The results of the heteroscedasticity test can be seen as follows:

 

Table 5 Heteroscedasticity Test Result

Variable

Sig

Keterangan

Financial Distress (X1)

0,335

Not Heteroscedasticity

Firm Size (X2)

0,052

Not Heteroscedasticity

Leverage  (X3)

0,765

Not Heteroscedasticity

Type Industry (Z)

0,468

Not Heteroscedasticity

Moderated 1 (X1.Z)

0,084

Not Heteroscedasticity

Moderated 2 (X2.Z)

0,824

Not Heteroscedasticity

Moderated 3 (X3.Z)

0,376

Not Heteroscedasticity

Source: Data is processed, 2024

 

Moderated Regression Analysis (MRA)

Moderated regression analysis (MRA) to identify the presence or absence of moderator variables. A moderating variable is an independent variable that will strengthen or weaken the relationship between the independent variable and the dependent variable [25]. The results of multiple linear regression analysis of the research hypothesis can be seen in the table: 

 

Table 6 MRA Result 

Variabel

  Koef.

   Regresi

Sig.

Keterangan

Konstanta

0,035

-

-

Financial Distress (X1)

0,414

0,000

Significant

Firm Size (X2)

0,064

0,136

Not- Significant

Leverage  (X3)

0,163

0,004

Significant

Type Industry (Z)

0,471

0,000

Significant

Moderated 1 (X1.Z)

0,442

0,031

Significant

Moderated 2 (X2.Z)

-0,092

0,076

Not-Significant

Moderated 3 (X3.Z)

0,355

0,001

Significant

Source: Data is processed, 2024.

 

Hypothesis testing

T-Test

In this study, the significance level used was 5% (0.05). Thus, if the significance level is more than 0.05 and the calculated t value is greater than the table, then the hypothesis is rejected. Conversely, if the significance level is less than 0.05 and the calculated t value is less than t, then the hypothesis is accepted [25]. The t test results are as follows:

Table 7 T-test Result

Variabel

Sig

Financial Distress (X1)

0,000

Firm Size (X2)

0,136

Leverage  (X3)

0,004

Moderated 1 (X1.Z)

0,031

Moderated 2 (X2.Z)

0,076

Moderated 3 (X3.Z)

0,001

Source: Data is processed, 2024.

 

Coefficient of Determination Test (R2)

To determine the percentage influence of the independent variable whose relationship is closer to the dependent variable, analysis of the coefficient of determination, or R2 test, is used [25]. The R2 test results are as follows:

Teble 8 R2 Test Result 

R

R Square

Adjusted R Square

0,850

0,722

0,712

F-test

The F test is used to determine whether the independent variable and dependent variable have a significant influence on each other. The degree of confidence used is 0.000 to 5% (0.05). In the alternative hypothesis, each independent variable has a significant impact on the dependent variable simultaneously, with degrees of freedom, or F table df (n-k). The F value from the calculation must be greater than the F value from the table [25]. The results of the F test can be seen at: 

Table 9 F-Test Result

Variable

Sig.

Residual

0,000

 

DISCUSSIONS

The Effect of Financial Distress on Earnings Management

The results of multiple linear regression analysis in the t test on the first hypothesis (H1) show that Financial Distress has an effect on Earnings Management by looking at the significance level, which is 0.000 and the regression coefficient is positive, meaning that the higher the Financial Distress, the higher the Earnings Management will be (H1 is accepted). The results of this research are in line with previous research conducted shows that the financial condition of the transportation and tourism sector has experienced a decline in financial health since the onset of COVID-19 and has experienced an increase in the level of distress and its safety position has decreased. The results of this research are also in line with [26] which states that there are differences in financial distress in manufacturing companies before and during the COVID-19 pandemic

 

The Influence of Company Size on Earnings Management

The results of multiple linear regression analysis in the t test on the second hypothesis (H2) show that company size has no effect on earnings management by looking at the significance level, which is 0.136, meaning that the higher the company size, the profit management will not change (H2 is rejected). 

Company size does not determine opportunities or tendencies for earnings management, because it is more influenced by organizational culture, corporate governance, and external pressures (eg profit targets). This shows that company size does not necessarily reduce the possibility of earnings management

Larger companies have less incentive to carry out earnings management than small companies and large companies are viewed more critically by shareholders and outside parties. 

The results of this research are in line with the results of [27] research that company size has a negative effect on earnings management. [19] stated that before the pandemic, company size had a negative effect and during the pandemic it had a positive effect on financial performance

 

The Effect of Leverage on Earnings Management

The results of multiple linear regression analysis in the t test on the third hypothesis (H3) show that Leverage has an effect on Earnings Management by looking at the significance level, which is 0.004 and the regression coefficient is positive, meaning that the higher the Leverage, the higher the Earnings Management will be (H3 is accepted).

The results of this research are in line with previous research conducted [21] states that leverage has a significant effect on earnings management during the COVID-19 pandemic. The results of this research are also in line with  who stated that the DER ratio influenced earnings management before and during the COVID-19 pandemic.

 

The Effect of Financial Distress on Earnings Management is Moderated by Industry Type

The results of multiple linear regression analysis in the t test on the fourth hypothesis (H4) show that Financial Distress has an effect on Earnings Management by looking at the significance level, which is 0.000 and the regression coefficient is positive, meaning that the higher the Financial Distress, the higher the Earnings Management will be (H4 is accepted).

Financial distress will have an impact on the company's economy. The type of company industry refers to the type of operations carried out by the company, each particular type of industry can require a level of expertise and require more time and effort than other types of industry [22]. The results of this research are in line with previous research conducted [13] showing that the type of industry influences earnings management.

The Influence of Firm Size on Earnings Management is Moderated by Industry Type

The results of multiple linear regression analysis in the t test on the fifth hypothesis (H5) show that company size has no effect on earnings management by looking at the significance level, which is 0.076, meaning that the higher the company size, the profit management will not change (H5 is rejected).

The size of the company has no effect on earnings management. Large company size does not make companies reduce earnings management activities. The bigger the company, the tighter the supervision of the company's internal parties.  Company size shows the amount of information from the company's total assets, so companies are more careful in carrying out financial reporting.

The results of this research are not in line with previous research conducted which states that industry type, managerial ownership, operating profit margin, and dividend payout ratio together influence income smoothing in companies listed on the Indonesia Stock Exchange in 2012-2014

The Influence of Leverage on Earnings Management Is Moderated By Industry Type

Results of multiple linear regression analysis in the t test on the sixth hypothesis (H6) Leverage has an effect on Profit Management, moderated by Industry Type, looking at the significance level, which is 0.001 and the regression coefficient is positive, meaning that the higher the Leverage, the higher the Profit Management will be, moderated by Industry Type ( H6 accepted).

High leverage can encourage management to carry out earnings management to avoid violating debt agreements. This can happen because companies that have high leverage are at risk of being unable to pay their debts on time. Leverage is a ratio that shows how much of a company's assets are financed with debt. High leverage can be caused by management errors in managing company finances or implementing inappropriate strategies.

The results of this research are in line with previous research conducted [21] states that leverage has a significant effect on earnings management during the COVID-19 pandemic.

CONCLUSIONS AND RECOMMENDATIONS

Conclusions

  1. The results of multiple regression testing on the influence of Financial Distress on Earnings Management show a significant positive influence. This proves that the higher Financial Distress will increase Earnings Management. 

  2. The results of multiple regression testing on the influence of company size on earnings management show that the influence is not significant. This proves that the higher the company size, the profit management does not change.

  3. The results of multiple regression testing on the influence of Leverage on Earnings Management show a significant positive influence. This proves that the higher Leverage will improve Profit Management. 

  4. The results of multiple regression testing on the influence of Financial Distress on Earnings Management moderated by Industry Type show a significant positive influence. This proves that the higher Financial Distress will increase Earnings Management which is moderated by Industry Type. 

  5. The results of multiple regression testing on the effect of company size on earnings management moderated by industry type show an insignificant effect. This proves that the higher the Company Size, the Profit Management which is moderated by Industry Type does not change.

  6. The results of multiple regression testing on the influence of Leverage on Earnings Management moderated by Industry Type show a significant positive influence. This proves that the higher Leverage will increase Profit Management which is moderated by Industry Type.

Recommendations

  1. Future researchers can use other earnings management calculations that use numbers in audited financial reports.

  2. It is hoped that future researchers can add samples of companies from other sectors.

Conflict of Interest:

The authors declare that they have no conflict of interest

Funding:

No funding sources

Ethical approval:

The study was approved by the University of Jember, Indonesia.

BIBLIOGRAPHY
  1. Darmawati, D. "Pengaruh Manajemen Laba, Jaminan dan Umur Obligasi terhadap Peringkat Obligasi." Prosiding Seminar Nasional Cendekiawan 1.1 (2016), pp. 1-13.

  2. Ernadi, Sani, & Kamil, Krishna. "Pengaruh Financial Distress, Ukuran Perusahaan dan Komite Audit Terhadap Manajemen Laba Pada Perusahaan Kompas 100 yang Terdaftar di BEI 2016-2019." Jurnal Akuntansi 8.3 (2020), pp. 45-59.

  3. Fauzi, M. A., & Paiman, N. "COVID-19 Pandemic in Southeast Asia: Intervention and Mitigation Efforts." Asian Education and Development Studies 10.2 (2020), pp. 123-139.

  4. Damayanti, Carolina Reni, & Kawedar, Warsito. "Pengaruh Profitabilitas Mekanisme Pemantauan dan Financial Distress terhadap Manajemen Laba." Diponegoro Journal of Accounting 7.4 (2018), pp. 1-9.

  5. Melinda, & Widyasari. "Faktor yang Mempengaruhi Manajemen Laba Perusahaan Manufaktur yang Terdaftar di BEI." Jurnal Multiparadigma Akuntansi 1.2 (2019), pp. 452-459.

  6. Sucipto, Hadi, & Zulfa, Umi. "Pengaruh Good Corporate Governance, Financial Distress dan Ukuran Perusahaan Terhadap Manajemen Laba." Jurnal Riset Akuntansi dan Keuangan Dewantara 4.1 (2021), pp. 13-22.

  7. Astuti, A. Y., Nuraina, E., & Wijaya, A. L. "Pengaruh Ukuran Perusahaan dan Leverage terhadap Manajemen Laba." The 9th FIPA: Forum Ilmiah Pendidikan Akuntansi 5.1 (2017), pp. 501-514.

  8. Lidiawati, N., & Asyik, N. F. "Pengaruh Kualitas Audit, Komite Audit, Kepemilikan Institusional, Ukuran Perusahaan terhadap Manajemen Laba." Jurnal Ilmu dan Riset Akuntansi (JIRA) 5.5 (2016), pp. 1-12.

  9. Amelia, W., & Hernawati, E. "Pengaruh Komisaris Independen, Ukuran Perusahaan, dan Profitabilitas terhadap Manajemen Laba." NeO~Bis 10.1 (2016), pp. 62-77.

  10. Agustia, Yofi Prima, & Suryani, Elly. "Pengaruh Ukuran Perusahaan, Umur Perusahaan, Leverage, dan Profitabilitas Terhadap Manajemen Laba (Studi Pada Perusahaan Pertambangan yang Terdaftar di Bursa Efek Indonesia Periode 2014-2016)." Jurnal Aset (Akuntansi Riset) 10.1 (2018), pp. 63-74.

  11. Kustiyaningrum, D., Nuraina, E., & Wijaya, L. A. "Pengaruh Leverage, Likuiditas, Profitabilitas, Dan Umur Obligasi Terhadap Peringkat Obligasi (Studi Pada Perusahaan Terbuka Yang Terdaftar Di Bursa Efek Indonesia)." ASSETS: Jurnal Akuntansi dan Pendidikan 5.1 (2016), pp. 25-40.

  12. Novianingsih, E. "Pengaruh Jenis Industri Terhadap Audit Delay (Studi Empiris Pada Perusahaan Indeks LQ 45 Yang Terdaftar di Bursa Efek Indonesia Tahun 2014-2016)." Prodi Akuntansi Universitas PGRI Yogyakarta 10.1 (2018), pp. 20-28.

  13. Putro, R. G. A. "Pengaruh Profitabilitas, Leverage, Kualitas Good Corporate Governance dan Jenis Industri Terhadap Manajemen Laba (Studi Empiris Pada Perusahaan Go Publik Yang Terdaftar Dalam Penilaian CGPI Pada Tahun 2010-2013)." Doctoral dissertation Universitas Muhammadiyah Surakarta 9.1 (2016).

  14. Fatmawati, D., & Sabeni, A. "Pengaruh Diversifikasi Geografis, Diversifikasi Industri, Konsentrasi Kepemilikan Perusahaan, dan Masa Perikatan Audit terhadap Manajemen Laba." Diponegoro Journal of Accounting 5.3 (2013), pp. 306-317.

  15. Jensen, M. C., & Meckling, W. H. "Theory of the Firm: Managerial Behavior, Agency Costs and Ownership Structure." Journal of Financial Economics 3.1 (1976), pp. 305-360.

  16. Chairunesia, W., Sutra, P. R., & Wahyudi, S. M. "Pengaruh Good Corporate Governance Dan Financial Distress Terhadap Manajemen Laba Pada Perusahaan Indonesia Yang Masuk Dalam Asean Corporate Governance Scorecard." Jurnal Profita 11.2 (2018), pp. 232-245.

  17. Watts, R. L., & Zimmerman, J. L. Positive Accounting Theory 1986.

  18. Masdiantini, P. R., & Warasniasih, N. M. S. "Laporan Keuangan dan Prediksi Kebangkrutan Perusahaan." Jurnal Ilmiah Akuntansi 5.1 (2020), pp. 196-210.

  19. Dearidrani, I. "Pengaruh Struktur Modal dan Ukuran Perusahaan Terhadap Kinerja Keuangan Perbankan di Indonesia Sebelum dan Selama Pandemi COVID-19: Studi Empiris Pada Bank Persero Dan Bank Swasta Nasional Di Indonesia Tahun 2016-2021." Doctoral dissertation Universitas Gadjah Mada 12.1 (2022).

  20. Wijaya, V. A., & Christiawan, Y. J. "Pengaruh Kompensasi Bonus, Leverage, dan Pajak Terhadap Earning Management Pada Perusahaan yang Terdaftar di Bursa Efek Indonesia Tahun 2009-2013." Tax & Accounting Review 4.1 (2014), pp. 316-330.

  21. Siregar, H. A., Anita, D., Daeli, F. M., Irawati, I., & Frastuti, M. "Pengaruh Likuiditas, Leverage Dan Profitabilitas Terhadap Manajemen Laba Di Masa Pandemi COVID-19 Pada Perusahaan Sektor Hotel, Restoran Dan Pariwisata Yang Terdaftar Di Bursa Efek Indonesia." LUCRUM: Jurnal Bisnis Terapan 2.1 (2022), pp. 30-43.

  22. Sanusi, M. A., & Purwanto, A. "Analisis Faktor yang Mempengaruhi Biaya Audit Eksternal." Diponegoro Journal of Accounting 6.3 (2017), pp. 372-380.

  23. Ambarwati, R. "Analisis Pengaruh Ukuran Perusahaan, Profitabilitas, Siklus Operasi Perusahaan, Likuiditas, Leverage dan Klasifikasi Industri Terhadap Manajemen Laba (Studi Empiris pada Perusahaan Manufaktur yang Terdaftar di Bursa Efek Indonesia Periode 2010–2014)." Doctoral dissertation Universitas Muhammadiyah Surakarta 8.2 (2016).

  24. Sugiyono, P. D. Buku Sugiyono, Metode Penelitian Kuantitatif Kualitatif 5.1 (2019).

  25. Ghozali, Imam. Aplikasi Analisis Multivariate dengan Program SPSS. Badan Penerbit Universitas Diponegoro 11.1 (2011).

  26. Sari, T. N., & Setyaningsih, P. R. A. "Analisis Financial Distress dan Financial Performance Sebelum dan Selama Pandemi COVID-19 Pada Perusahaan Manufaktur." Jurnal Riset Akuntansi Mercu Buana 8.1 (2022), pp. 12-29.

  27. Tsaqif, Bahly Muhammad, & Agustiningsih, Wulandari. "Pengaruh Financial Distress dan Ukuran Perusahaan Terhadap Manajemen Laba dengan Kepemilikan Manajerial sebagai Variabel Moderasi." Jurnal Akuntansi dan Governance 2.1 (2021), pp. 53-65.

Advertisement
Recommended Articles
Research Article
The Influence of Information Adoption From Youtubers on the Purchase Intention of Skincare Products Among Gen Z in Jabodetabek
Published: 20/01/2025
Download PDF
Research Article
Influence of Leadership on Poverty Reduction in the Devolved Government in Trans-Nzoia County, Kenya
...
Published: 30/06/2021
Download PDF
Research Article
The Effect Of Esg On Company Value With Earnings Management As An Intervening Variable At Registered Coal Companiesat BEI 2020-2023
...
Published: 20/11/2024
Download PDF
Research Article
The Effect of Workload on Organizational Commitment of Service Section Employees at the Main Branch Office of PT. West Kalimantan Bank: Work-Life Balance (WLB) and Job Satisfaction as Mediation
...
Published: 27/07/2024
Download PDF
Chat on WhatsApp
Flowbite Logo
Najmal Complex,
Opposite Farwaniya,
Kuwait.
Email: kuwait@iarcon.org

Editorial Office:
J.L Bhavan, Near Radison Blu Hotel,
Jalukbari, Guwahati-India
Useful Links
Order Hard Copy
Privacy policy
Terms and Conditions
Refund Policy
Others
About Us
Contact Us
Online Payments
Join as Editor
Join as Reviewer
Subscribe to our Newsletter
Follow us
MOST SEARCHED KEYWORDS
scientific journal
 | 
business journal
 | 
medical journals
 | 
Scientific Journals
 | 
Academic Publisher
 | 
Peer-reviewed Journals
 | 
Open Access Journals
 | 
Impact Factor
 | 
Indexing Services
 | 
Journal Citation Reports
 | 
Publication Process
 | 
Impact factor of journals
 | 
Finding reputable journals for publication
 | 
Submitting a manuscript for publication
 | 
Copyright and licensing of published papers
 | 
Writing an abstract for a research paper
 | 
Manuscript formatting guidelines
 | 
Promoting published research
 | 
Publication in high-impact journals
Copyright © iARCON Internaltional LLP . All Rights Reserved.