How Financial Performance and State-Owned Enterprise (SOE) Values Are Affected by Good Corporate Governance and Intellectual Capital Perspectives

Abstract

The implementation of good governance and attention to resources will affect company survival. The purpose of this study was to examine the effect of good corporate governance and intellectual capital on financial performance and company value through statistical and econometrical tests on SOEs in Indonesia. This is quantitative research with state-owned enterprises (SOEs) listed on the Indonesia Stock Exchange. The total study population was 16 SOEs. This study used a saturated sample. Furthermore, the exogenous variables in this study were good corporate governance (GCG) and intellectual capital, whereas the endogenous variables were the company and financial performance. This study used the statistical analysis inferential because the variables used indicators and were formative. The results indicated that GCG and financial performance have positive effects on firm value, intellectual capital does not affect company value, and GCG and intellectual capital have positive effects on financial performance. The evaluation of indirect effects in this study showed that financial performance mediates the effect of intellectual capital and GCG on company value.

1. Introduction

‘Being concern’ indicates that a company, especially an SOE, will operate as a contributor of foreign exchange in terms of profit (Purba 2009). Several studies on going concern include Javaid and Javid (2018) and Tagesson and Öhman (2015). An entity can be considered as going concern if it can continue its operations and fulfil its obligations (Irfana 2012). Altman and McGough (1974) argue that going concern issues are divided into two: those related to finance and those related to operations. Continuity is an important factor that companies must maintain. Various efforts can be made so that investors do not doubt the sustainability of the company in terms of finances and operations (Altman and McGough 1974). One of the objectives of establishing a company is to maximize its value, which is reflected in its share price (Wiagustini 2010). Company value is the price a buyer is willing to pay if the company is sold (Husnan and Pudjiastuti 2006). If investors’ perceptions are positive, then the company’s value is high. This condition may increase the shareholders’ prosperity, assuming ceteris paribus conditions for the external environment. In this study, the company’s proxy value is Tobin’s Q because the Q ratio shows its opportunity to grow in the future through investment policies. The greater the value of Tobin’s Q, the higher the growth prospects are (Vo and Nguyen 2014). Another reason for choosing company value is that, based on

Table 1. SOE value based on Tobin’s Q in 2015.

No	Name of SOE	Tobin’s Q
1	Adhi Karya	0.68
2	Aneka Tambang	0.48
3	Bukit Asam	0.74
4	Cement Baturaja	0.89
5	State Gas	0.86
6	Garuda Indonesia	0.52
7	Indo Farma	0.59
8	Jasa Marga	0.98
9	Chemical Farma	1.35
10	Krakatau Steel	0.40
11	Development Housing	0.99
12	Semen Indonesia	1.60
13	Telkom Indonesia	1.61
14	Tin	0.58
15	Wijaya Karya	1.20
16	Waskita Karya	0.85
17	BNI	0.56
18	BRI	0.32
19	BTN	0.52
20	Mandiri	0.58
	∑ Percentage above 1	20%

Source: SOE Financial Report.

, it can be inferred that 80% of SOEs’ values are below 1.

To implement going concern as a corporate goal, the company’s value becomes very important. A company is considered sustainable if it is: (a) able to create profits and investment; and (b) trustworthy and supported by customers, suppliers, the government, the community, the media, and non-governmental organizations (NGOs) (Mardikanto 2014). This study took SOEs as the research object because of a paradigm shift. Before 1998, SOEs were managed entirely by the government. However, since 2003, they have been managed by professionals. SOEs also support the Indonesian economy and contribute to foreign exchange from the profits. Especially due to the COVID-19 pandemic, the government needs a considerable amount of funds for mitigation efforts. Other than that, SOEs also empower micro, small, and medium enterprises (MSMEs) through fostering partners and building a strong economic structure through sound and ethical business practices (Zulmawan 2019).

The cause of company value fluctuation is the implementation of good corporate governance, intellectual capital, and financial performance. The GCG variable was chosen because good governance also increases stakeholders’ confidence in a company. GCG ensures a clear separation of duties and responsibilities and the disclosure of both financial and non-financial information. Another background of this study is inconsistent results from previous research. Ali et al. (2018), Halim et al. (2017), and Bohdanowicz (2015) found that corporate governance influences company performance. Meanwhile, Bashir et al. (2018) found that corporate governance does not significantly influence company value.

Intellectual capital was chosen because good human resources lead to investor confidence in the company, increasing the company value (Mouritsen et al. 2001). There is also an increasing demand for transparency in the capital market. Adequate information about a company’s intellectual capital helps investors to better assess the company’s ability. Similarly, there are also inconsistencies in previous research. Anifowose et al. (2018) found that intellectual capital has a significant effect on company value. In contrast, however, Sunarsih and Mendra (2012) and Badingatus Solikhah and Meiranto (2010) did not find that intellectual capital affects the company’s market value.

Research by Chakrawal (2006) on company’s governance in India indicated that more companies understand that GCG is essential in an effective market to achieve the organization’s goals. Their research reveals the importance and existence of accountability in GCG. Furthermore, Olaison’s research (2018) on Swedish companies’ governance showed that corporate governance differences might result in more or less strict evaluation criteria when transplanted. Sripada (2019) studied aspects of human resources in relation to company governance in India. They point out the importance of revitalizing the functions of human resource management as an organ that shapes and directs the future of company governance. Several aspects which must be emphasized are compliance, compensation, competence and culture, by putting humans at the center of company governance. Sripada’s results are in line with Busrai’s (2019), who pointed out that company governance is not only the CEO’s responsibility, but also that of other human resources in the company.

The purpose of this study was to assess financial performance and company value from the perspective of good corporate governance and intellectual capital. This research is expected to make a practical contribution so that companies can increase their value and financial performances, which can benefit the stakeholders. This research is also expected to provide empirical evidence regarding the factors affecting financial performance and corporate value from the theoretical perspective. It can also serve as a reference for further research to determine the factors influencing the company’s value and financial performance.

Ultimately, this research aimed to determine the impact of companies that implement good governance and pay attention to human resources so that companies can grow sustainably or operated with going concern (Purba 2009). This research’s novelty is that it is a modification of the research model that puts financial performance as a mediation variable (Pertanian 2006). In addition, the measurement indicators for GCG used five principles of transparency, accountability, responsibility, independence, and fairness (TARIF).

Literature Review

A company uses information to give positive or negative signals to the stakeholders (Signaling Theory). As outsiders, potential investors obtain information from company executives through annual reports (Scott 1997). According to Signaling Theory, investors can distinguish between high-value and low-value companies (Brigham and Houston 2006). In addition to Signaling Theory, this research also used the Reference Stakeholder Theory. Stakeholder Theory states that organizations voluntarily disclose information about their environmental, social, and intellectual performance that exceeds or is above the demands to meet the stakeholders’ expectations (Ulum 2017).

Regulation of the Indonesian Minister of SOE, Number PER-01/MBU/2011, explains the five pillars of GCG, namely: (1) Transparency; (2) Accountability; (3) Responsibility; (4) Independence; and (5) Fairness, abbreviated as TARIF. ‘Transparency’ is openness in the decision-making process, the disclosure of information and materials related to the company (including the company’s vision and mission), and employees’ career path process. ‘Accountability’ is the responsibility of implementing the organization so that it can run effectively. ‘Responsibility’ is the company management’s compliance with the laws and regulations and healthy corporate principles. ‘Independency’ is the professional management of the company. It should be without any conflict of interest and free from pressure from any party which is not in accordance with the laws and regulations as well as healthy corporate principles. ‘Fairness’ is the fairness and equity in fulfilling the rights of stakeholders arising under agreements, laws, and regulations.

The difference between market value and the book value of a company is called the intellectual capital value (Ulum 2017). A company that manages intellectual capital well will improve their market value. Likewise, if the capital market is efficient, investors will assign higher values to companies with greater intellectual capital (Riahi-Belkaoui 2003). Financial statements have limitations in explaining the value of the company. Thus, the source of economic value is no longer in the production of material goods, but in the creation of intellectual capital (Wu et al. 2005). Its activities are often related to employee development, organizational restructuring, and the development of marketing activities. The calculation of intellectual capital begins with the difference between output and input, where output is the total income. In contrast, the input is the entire burden used by the company in addition to employee salary expenses. The measurement of intellectual capital in this study was taken from Human Capital (HC), Structural Capital (SC), Capital Employed (CA), and Relational Capital (RC).

The financial performance was assessed from the financial statements compared to the previous year; thus, the company’s quality development could be measured. Measurements of financial performance are usually conducted through financial ratios. Financial ratios are useful for showing comparisons and investigations in financial information (Safitri 2015). The measurements of financial ratios used in this study were profitability ratios, namely, Return on Assets (ROA). Company value is the company’s selling value, which is reflected in the stock market price or the price of shares traded on the capital market (Rachmawati and Triatmoko 2007). This study used the measurement of company value by Tobin’s Q, namely, by comparing the ratio of the market value of shares with the book value of the company’s equity (Wright and Smithers 2000).

Research on 150 companies registered with Egyptian Listed Companies in 2008 showed no significant relationship between corporate governance and company performance (Shahwan 2015). On the other hand, a study of 37 financial companies listed on the Bursa Malaysia, both before the revision of the corporate governance criteria in Malaysia and before the global financial crisis, showed that the company’s performance affected Tobin’s Q (Kallamu 2016). Hacyl’s research is also supported by Lassoued (2018), who showed that corporate governance does affect the company’s value. Lin et al. (2020) show the importance of SOEs in China’s economic success in the past and for the future. Research from Abramov et al. (2017) showed that SOEs listed in Russia have much higher productivity compared to SOEs which are not listed. Manes-Rossi et al. (2021), in their research on SOEs in eight European countries (The Netherlands, Germany, Italy, Finland, Poland, England, Sweden and Austria), showed that government ownership and profitability have a positive influence on integrated reporting disclosure (IRD).

Research on information communication technology companies in Vietnam showed that intellectual capital, which is proxied by organizational capital, human capital, and social capital, positively affects company performance (Nhon et al. 2018). This research was also supported by (Scafarto et al. 2016) and (Nkundabanyanga et al. 2014). However, different results were obtained from studies on pharmaceutical and textile companies in the CMIE (Center for Monitoring Indian Economy). These results indicate that intellectual capital does not affect the company’s performance (Pal and Soriya 2012). Meanwhile, other research by Sucuahi and Cambarihan (2016) and Veronica (2013) showed that financial performance has a significant positive effect on company value, which was proxied by Tobin’s Q.

Research on commercial banks in Jordan in 2005–2014 showed the results of corporate governance, which is proxied by the concentration of ownership (both government and foreign), and positively influences the bank’s performance proxied by ROA and ROE (Jarbou et al. 2018). This research is in line with 29 Mai-listed firms and 65 listed SETs, which showed that corporate governance, proxied by the directors of the company and the composition of the board, affects the financial performance proxy by ROA (Laoworapong et al. 2015). Meanwhile, the research results on companies listed on the Bursa Malaysia show that the board of directors does not affect financial performance (Shukeri et al. 2012).

Research on 18 agribusiness industry companies in 2010–2014 showed a significant positive effect between relational capital and process capital on financial performance proxy by ROA, ROE, and ROI. However, Human Capital does not correlate with financial performance (Scafarto et al. 2016). A study by Nimtrakoon (2015) on 213 technology companies registered in Asian countries showed that intellectual capital has a positive effect on financial performance, especially ROA, and on market performance. Research on manufacturing companies listed on the Stock Exchange of Thailand in 2006–2009 showed that intellectual capital’s results had a positive and significant effect on financial performance, which was proxied by ROE and ROA (Phusavat et al. 2011).

Based on the above data, the research hypotheses are:

H₁. 

GCG has a positive effect on the company value;

H₂. 

Intellectual capital has a positive effect on the company value;

H₃. 

Financial capital has a positive effect on the company value;

H₄. 

GCG has a positive effect on financial performance;

H₅. 

Intellectual capital has a positive effect on financial performance.

The research model is shown in Figure 1.

2. Methodology

This study was designed to explain the influence of variables by testing hypotheses, i.e., explanatory research (Solimun and Fernandes 2017). This research was a quantitative study because it aimed to assess the hypotheses using statistical tests. The sample in this study was SOEs registered at BEI in 2012–2017, totaling 16 companies. This study’s sampling technique was saturated because all available samples were taken (Sugiyono 2010). This study’s exogenous variables were GCG and intellectual capital, whereas the endogenous variables were financial performance and firm value. GCG and intellectual capital are referred to as exogenous variables because they can be controlled by the internal company. GCG is defined as a system designed to direct the management of SOEs professionally, based on the principles of transparency, accountability, responsibility, independence, and fairness (TARIF), with the criteria mentioned in Appendix A (Effendi 2009). A calculation was performed, comparing reports that met the criteria compared to the number of report criteria required by SOE ministerial regulations. The GCG measurement indicators were:

Transparency (TRA) measured by = (∑ Reports that meet the Transparency criteria: ∑ Transparency Report Criteria) × 100%.

Accountability (ACC) measured by = (∑ Reports that meet the Accountability criteria: ∑ Accountability Report Criteria) × 100%.

Responsibility (RES) measured by = (∑ Reports that meet the Responsibility criteria: ∑ Responsibility Report Criteria) × 100%.

Independency (IND) measured by = (∑ Reports that meet the Independence criteria: ∑ Independent Report Criteria) × 100%.

Fairness (FAI) measured by = (∑ Reports that meet the Fairness criteria: ∑ Fairness Report Criteria) × 100%.

The number of reports that met the tariff criteria is in Appendix A.

The definitions of operational variables in this study were valuable resources for competitive advantage that could contribute to SOEs’ financial performance. Intellectual capital in this study was measured using the following indicators:

VA (value added): the difference between the output and the input. Output was obtained from total sales and other income, whereas the input was obtained from the total selling expenses and other expenses without including the employee salary expense.

CE (capital employed): available funds (equity, net income) or assets—liabilities.

Human capital efficiency (HCE): VA/HC (Pulic 1998).

HC (human capital): employee expenses in this study were salaries and wages, as well as employee training listed in the SOE.

Structural capital efficiency financial report (SCE): SC/VA (Pulic 1998).

SC: structural capital obtained from VA—HC.

Relational capital efficiency (RCE): VA/RC (Nazari and Herremans 2007).

RC: relational capital obtained from the marketing costs.

The operational definitions of financial performance variables in this study were the achievement of SOE performance reflected in the financial statements or the ROA (Kasmir 2011). In this study, operational definitions of variables of the company’s value were the prospective investor’s price if the SOEs were sold. The price was measured by Tobin’s Q indicator, which is the value of SOEs assessed by investors and reflected in the price of the yearly stock. The Tobin’s Q calculation formula is as follows (Wright and Smithers 2000):

$$\mathrm{Q}=\frac{\left(\mathrm{EMV}+\mathrm{D}\right)}{\left(\mathrm{EBV}+\mathrm{D}\right)}$$

where Q is the value of Tobin’s Q, EMV is the equity market value obtained from the closing price multiplied by the number of outstanding shares, EBV is the equity book value, and D is the book value of total debt (debt).

The data collection technique employed in this research was the use of internet access to download the annual report of an SOE company. The webpage was http://www.idx.co.id (accessed on 6 October 2020), whereas the data were analyzed using inferential statistical analysis. Inferential statistical analysis is used to test research models, assumptions, feasibility models, and hypothesis testing (Sugiyono 2018). In this study, inferential statistical analysis was performed in WrapPLS 6.0. software (Ghozali 2008).

The research model was divided into two:

Model 1: the effect of GCG, intellectual capital and financial performance on company value.

NPE = β₁ GCG + β₂ ICA + β₃ KKE + e …

Model 2: the effect of GCG and intellectual capital on financial performance.

KKE = β₄ GCG + β₅ ICA + e …

where KKE is the financial performance, GCG is good corporate governance, ICA is the intellectual capital, NPE is the company value, β is a constant, and e is the error.

Testing the direct influence hypothesis assessed whether there was a direct influence of exogenous variables on endogenous variables. Test criteria state that if the path coefficient has a p-value ≤ level of significance (alpha = 5%) with a positive value, it means that there is a significant influence between the exogenous variables and endogenous variables.

Hypothesis testing of indirect effects was carried out to test whether there was an indirect effect of exogenous variables on endogenous variables through mediating variables. The test criteria state that if the indirect effect has a p-value ≤ level of significance (alpha = 5%), it is stated to have a significant influence (Ghozali and Latan 2017).

3. Results

3.1. Evaluation Results of Measurement Model (Outer Model)

This latent variable indicator is a variable with a formative indicator model because it is characterized by composite variables and is usually found in economics (Solimun and Fernandes 2017). Evaluation of the outer model for formative constructs can be performed by considering the significance of weight. The indicator meets the criteria indicator reliability if it has a weight value significant at p < 0.05. The outer model test results in

Table 2. Results of the measurement model evaluation—outer model.

Variable	Indicator	Weight	p-Value
GCG	Transparency	0.302	<0.001
GCG	Accountability	0.257	0.004
GCG	Responsibility	0.274	0.002
GCG	Independence	0.205	0.018
GCG	Fairness	0.231	0.009
ICA	Structural Capital Efficiency	0.333	<0.001
ICA	Human Capital Efficiency	0.221	0.012
ICA	Relational Capital Efficiency	−0.336	<0.001
ICA	Capital Employed Efficiency	0.343	<0.001
KKE	Return On Assets	1.000	<0.001
NPE	Tobin’s Q	1.000	<0.001

Source: data processing.

show p-values < 0.05.

3.2. Results of Structural Model Evaluation (Inner Model)

The results of the structural model evaluation in this study used the feasibility of the model (goodness of fit). If there are one or two indicators, model fit and quality indices, this model can be used (Solimun and Fernandes 2017), as shown in

Table 3. Results of the feasibility model—goodness of fit.

Model Fit and Quality Indices	Criteria Fit	Results	Information
Average Path Coefficient (APC)	p < 0.05	p < 0.001	Fit
Average R-Squared (ARS)	p < 0.05	p = 0.006	Fit
Average Adjusted R-squared (AARS)	p < 0.05	p = 0.011	Fit
Average Block VIF (AVIF)	Acceptable if ≤ 5, ideality ≤ 3.3	1.215	Fit
Average Full Collinearity VIF (AFVIF)	Acceptable if ≤ 5, ideality ≤ 3.3	1.237	Fit
Tenenhaus GoF (GoF)	Small ≥ 0,1, Medium ≥ 0.25, Large ≥ 0.36	0.424	Fit
Simpson’s Paradox Ratio (SPR)	Acceptable if ≥ 0.7, Ideality = 1	0.8	Fit
R-Squared Contribution Ratio (RSCR)	Acceptable if ≥ 0.9, Ideality = 1	0.915	Fit
Statistical Suppression Ratio (SSR)	Acceptable if ≥ 0.7	1	Fit
Non-linear Bivariate Causality Direction Ratio (NLBCDR)	Acceptable if ≥ 0.7	0.5	Not Fit

Source: data processing.

.

Table 3 shows that only one criterion does not fit, namely, the Non-Linear Bivariate Causality Direction. Therefore, it can be concluded that the model meets the goodness of fit requirements.

3.3. Results of Hypothesis Testing

Hypothesis testing is used to test whether there is an indirect effect of exogenous variables on endogenous variables. If the coefficient path has a p-value ≤ level of significance (alpha = 5%), it can be declared that there is a significant influence of exogenous variables on endogenous variables. The results of hypothesis testing are presented in

Table 4. Results of direct hypothesis tests.

Exogenous	Endogenous	Path Coefficient	p-Value	Description
GCG	NPE	0.419	<0.001	Accepted
ICA	NPE	0.116	0.123	Rejected
KKE	NPE	0.228	0.010	Received
GCG	KKE	0.299	0.001	Received
ICA	KKE	0.423	<0.001	Accepted

Source: data processed.

.

The effect of GCG on company value (NPE) shows a path coefficient of 0.419 with a p-value < 0.001. The test results show that the path coefficient has a p-value ≤ level of significance (alpha = 5%). This result means that there is a significant influence of good corporate governance on the corporate value in a positive direction. Thus, the hypothesis stating that GCG has a significant effect on firm value (H₁) is accepted. This finding is in line with research by Siagian et al. (2013), Rashid and Islam (2013), and Eberhart (2012). The intellectual capital (ICA) effect on firm value produced a path coefficient of 0.116 with a p-value of 0.123. The test results show that the path coefficient has a p-value > level of significance (alpha = 5%). This result means that there is no significant effect of intellectual capital on firm value. Therefore, the hypothesis which states that intellectual capital has a significant effect on firm value (H₂) can be rejected. This result is in line with Hamdan’s (2018) research, which shows that intellectual capital does not affect market performance. This result is supported by Carlucci et al. (2014) and Britto et al. (2014). The influence of financial performance on firm value produces a path coefficient of 0.228 with a p-value of 0.010. The test results show that the path coefficient has p-value ≤ level of significance (alpha = 5%). This means that there is a significant influence on financial performance on firm value in a positive direction. Therefore, the hypothesis that financial performance significantly influences the value of the company (H₃) is accepted.

The influence of GCG on financial performance (KKE) produces a path coefficient of 0.299 with a p-value of = 0.001. The test results show that the path coefficient has a p-value ≤ level of significance (alpha = 5%). This result means that there is a significant influence of GCG on financial performance in a positive direction. Therefore, the hypothesis that the GCG effect on financial performance (H₄) is accepted, according to the research of Adedeji et al. (2020), Fidanoski et al. (2014), and (Alipour 2012). The effect of ICA on financial performance produces a path coefficient of 0.423 with a p-value of <0.001. The test results show that the path coefficient has a p-value ≤ level of significance (alpha = 5%). This result means that there is a significantly positive influence of intellectual capital on financial performance. Thus, the hypothesis stating that intellectual capital has a significant effect on financial performance (H₅) is accepted, in line with the research of Ozkan et al. (2017) and Janošević et al. (2013).

3.4. Results of the Evaluation of Indirect Effects

An evaluation of indirect effects was performed to test whether there is an indirect effect of exogenous variables on endogenous variables through mediating variables. Results of the evaluation of indirect influence are summarized in

Table 5. Evaluation of indirect influence.

Exogenous	Mediation	Endogenous	Indirect	p-Value	Description
GCG	KKE	NPE	0.068	0.01	Accepted
ICA	KKE	NPE	0.097	0.04	Accepted

Source: data processed.

.

Based on the test results listed in Table 5, it can be observed that the effect of GCG on firm value through financial performance produces a path coefficient of 0.068 with a p-value of 0.01. The test results show that the path coefficient has a p-value ≤ level of significance (alpha = 5%). Thus, the hypothesis stating that financial performance mediates the effect of GCG on firm value is accepted. This model has a partial mediation effect (Ghozali and Latan 2017). Intellectual capital’s effect on firm value through financial performance produces a path coefficient of 0.097 with a p-value of 0.04. The test results show that the path coefficient has a p-value ≤ level of significance (alpha = 5%). In Table 5, it is known that the indirect effect of ICA has a significant effect on firm value. On the other hand, the direct effect is not significant, i.e., there is a significant influence of intellectual capital on firm value through financial performance. Thus, the hypothesis that financial performance mediates the effect of intellectual capital on firm value is accepted. This model has a full mediation effect (Ghozali and Latan 2017).

Based on the table above, the structural model formed is:

KKE = 0.3 GCG + 0.42 ICA

(1)

NPE = 0.42 GCG + 0.116 ICA + 0.23 KKE

(2)

For more details, statistical calculations are summarized in Figure 2.

4. Conclusions

This study proved several things. Firstly, GCG has a positive effect on financial performance and company value. This finding is in line with research by Adedeji et al. (2020), Mishra and Kapil (2018), and (Sircar et al. 2015). The novelty which differentiates this research from previous studies is that GCG uses a measure of transparency, accountability, responsibility, independence, and fairness (TARIF). Secondly, intellectual capital does not affect company value. This finding is in line with the research of Hamdan (2018), Britto et al. (2014), and (Carlucci et al. 2014). The third finding is that based on financial performance, both GCG and intellectual capital affect the company value. This discovery is a novelty in the research model by using financial performance as a mediating variable. The fourth finding shows that intellectual capital has a positive effect on financial performance, which is in line with research by Chowdhury et al. (2018), Ghosh and Maji (2015), and Deep and Narwal (2014). This research was conducted on state-owned companies listed on the Indonesia Stock Exchange from 2012 to 2017, in the fields of telecommunications, transportation, cement production, construction, the gas sector, the pharmaceutical sector, steel production, building planning and construction, tin and tin mining, and coal. This study did not use SOEs in the financial sector because they have different characteristics; thus, the calculations of their financial performance are also different. The implications of this research is that SOE managers have more of a moral responsibility in implementing GCG and paying attention to intellectual capital. The existence of GCG implemented by SOE managers makes their performance more open and accountable to interested parties. This research was limited by using only internal influences. Therefore, it is hoped that subsequent studies will examine external factors such as interest rates, market growth, and dividend policy. Further research could also be conducted on non-SOEs to provide an overview of the application of government regulations relating to corporate governance. Another suggestion for future research is to use other financial performance indicators, such as the return on equity (ROE) and economic value added (EVA). This study also did not perform sensitivity tests. These are analyses to determine the effects which will occur if the objects and variables change (Gittinger 1986). Therefore, if the study were to be conducted on a different sample, it will not necessarily produce the same findings.