The Illomata International Journal of Management Ilomata International Journal of Tax & Accounting (IJTC) P-ISSN: 2714-9838; E-ISSN: 2714-9846 Volume 2, Number 3 July 2021 Page No. 222-235 https://www.ilomata.org/index.php/ijtc 222 | Ilomata International Journal of Tax & Accounting Volume 2 Number 3, July 2021 Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya State University of Jakarta Submitted : June 22, 2021 Revised : July 15, 2021 Published : July 31, 2021 ABSTRACT Return is one of the factors that investors pay attention in determining their investment policies. For this reason, this study analyzes the effect of several conventional financial performance indicators such as total asset turnover, current assets, debt to equity ratio, and return on assets to stock returns. Other variables that are seen as new indicators such as economic value added, human economic value added, and value added intellectual capital are also examined for their effects on stock returns. Companies engaged in the energy sector in Indonesia and Malaysia were made as objects in this study. OLS regression is used to analyze the effect of independent variables on the dependent variable. The results of an analysis of energy company data in Indonesia show that debt to equity ratio and human economic value added have a negative and significant effect on stock returns, while economic value added and value added intellectual capital have a positive and significant effect on stock returns. As for the object of research on energy companies in Malaysia, the results showed that total asset turnover, economic value added and value added intellectual capital had a positive and significant effect on stock returns. Keyword: Stock Return, Economic Value Added, Value Added Intellectual Coefficient INTRODUCTION Energy is one industry sector that has a significant effect on increasing the company's production specifically and the economic output of a country in general. Economic growth will highly depend on the availability of adequate energy considering the production process of goods or services will always need support for energy supply. Economic improvement is always associated with energy use, while the developing global economy will result in increased demand for energy (Rashid, et al., 2016). The World Economic Forum notes that developed and developing countries are the biggest energy providers and contributors of carbon dioxide emissions in the world in 2016 (WEF, 2019:18). For Southeast Asia region, Indonesia ranks highest from the perspective of energy use when compared to other countries in the same region. The Central Intelligence Agency on its official website noted that Indonesia consumed as much energy as 213 billion kwh in 2016, followed by Thailand with 187 billion kwh, Vietnam 143 billion kwh, and Malaysia 136 billion kwh. The amount of energy consumption for Indonesia, Vietnam, and Thailand is considered reasonable given the three have the largest population in Southeast Asia. However, it is different with Malaysia. With a population of only around 12% of the total population of Indonesia, Malaysia is able to absorb 64% of Indonesia's total energy consumption The comparison of Indonesian and Malaysian data is interesting to study considering that https://www.ilomata.org/index.php/ijtc Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 223 | Ilomata International Journal of Tax & Accounting Volume 2 Number 3, July 2021 the two countries are in the same region and even have neighbors, with almost the same historical background, and have relatively similar geographical conditions, but in fact have very different levels of energy consumption and economic performance. On the other hand, based on data I obtained from marketwatch.com, the return of energy company shares on the Indonesia Stock Exchange and the Malaysian Stock Exchange has seen significant differences in the last three years. The average stock return per year of energy companies in Indonesia has the same trend as the CSPI, which increased 36% per year in 2015-2016, an increase of 18% in 2016-2017, but decreased by 12% in 2017-2018. On the other hand, the average annual stock return of energy companies in Malaysia increased 75% in 2015-2016, decreased 39% in 2016- 2017, and increased again by 71% in 2017-2018. Changes in prices and stock returns are strongly influenced by internal and external factors of the company (Utami et al, 2015). Where when viewed from the perspective of company internal factors, a picture of company performance can be analyzed from financial data contained in the company's financial statements (Khadaffi and Heikal, 2014: 219). Some financial ratios that have long been known as tools for analyzing corporate financial performance include activity ratios, liquidity ratios, solvency ratios, and profitability ratios. In the context of performance analysis, several recent studies also discuss Economic Value Added (EVA) or economic added value as an alternative that can be used to measure the effectiveness of the company's financial performance. Another contemporary measurement tool related to company performance is Human Economic Value Added (HEVA). HEVA is a development of the EVA concept that was popularized by the Sten Steward & Co. organization and is useful for measuring the wealth of companies created per employee. Pulic in 1998 made a new concept to measure the Intellectual Capital (IC) of a company and in 2004 Pulic introduced the concept of Value Added Intellectual Coefficient (VAIC) consisting of several main components namely Capital Employee Efficiency (CEE), Human Capital Efficiency (HCE ), and Structural Capital Efficiency (SCE) (Sirapanji and Hatane, 2015: 46). Furthermore, an analysis of company performance is also important not only as an evaluation material in the context of the country's macroeconomic context, but also as an input for stakeholders in making all decisions related to company operations. For example, the decision of creditors in giving or not giving credit to a company, the company's managers in making decisions related to the company's future going forward, and investors in making investment decisions, one of them by buying a company's shares. In general, good company performance will increasingly attract the interest of creditors to provide loans that can be used as one of the inputs in order to expand the company. On the other hand, a good company performance will also increasingly attract new investors to invest their funds in the company, which is in accordance with the company's goal which is to increase the wealth of shareholders. In determining investment decisions, there are two methods that can be used by investors in evaluating company performance, namely technical analysis and fundamental analysis (Abdulmannan and Faturohman, 2015: 580). This research refers more to fundamental analysis by focusing on some conventional financial ratios such as the ratio of activities represented by Total Asset Turnover (TATO), liquidity ratios represented by Current Ratio (CR), solvency ratios represented by Debt to Equity Ratio (DER) , profitability ratios represented by Return on Assets (ROA). In addition, several other analytical tools such as Economic Value Added, Human Economic Value Added, and Value Added Intellectual Capital Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 224 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 which are all represent the tools of performance analysis of contemporary companies are also the focus of discussion in this study. All these performance analysis tools will be evaluated for their effect on stock returns (SR) of companies engaged in the energy sector in Indonesia and Malaysia. Referring to the results of previous studies discussing the variables used in this study, it can be concluded that there is no uniformity of results regarding the effects of conventional financial performance, economic value added, human economic value added, and value added intellectual capital on stock returns. The variety of research results is possible because of differences in the database used, the method used, and the period of research conducted. In addition, researchers see that there is still a research gap where there is no research comparing the effect of conventional financial performance, economic value added, human economic value added, and value added intellectual capital on company stock returns in the energy sector between Indonesia and Malaysia. In investing, every investor must expect a maximum return on his investment activities (Oktavia and Norita, 2016: 56). The return on investment can also be referred to as return or return on investment which is usually calculated over a certain period of time and measured by a percentage of the value of the investment made. Stock returns generally have two components, namely dividend yield and capital gain / loss (Tandelilin, 2010: 10). Dividend yield is any profit received by investors over share ownership which is usually called a dividend. While the capital gain/loss is the difference between changes in stock prices when bought with stock prices when sold. Oktavia and Norita (2016: 58) define the activity ratio as the efficiency level of a company in using its assets or resources to support the company's activities and achieve the expected goals. Total asset turnover as an indicator used in this study to represent the ratio of company activity is a ratio that illustrates the level of efficiency of the company in using its assets in order to increase sales and profits of the company (Aziz, Pahlavi, and Toaha, 2018: 33). Furthermore, liquidity ratios are used to measure a company's ability to meet short-term financial obligations that must be resolved (Robinson, 2009; Medyawati and Yunanto, 2017: 5) and meet unexpected needs for cash (Weygrandt, Kimmel, and Kieso, 2013: 695 ). One of the liquidity ratios used in this study is the current ratio, which is a ratio that describes how much the company's current liabilities can be covered by assets that are predicted to be converted into cash in a short time (Asmirantho & Somantri, 2017: 95). The solvency ratio is used to measure the company's ability to meet its long-term obligations (Robinson, 2009: 277). In other words, this ratio can be used to measure the company's ability to survive in the long run (Weygrandt et al., 2013: 703). Based on Putra, Nurlaela, and Samrotun (2018: 134), Debt to Equity Ratio is a measure of a company's ability to pay short-term and long-term debt. Profitability ratios measure the income or operating success of a company within a certain period of time, where company income will affect the company's ability to obtain debt and equity financing (Weygrandt et al., 2013: 699). Return on Assets that indicate a company's ability to generate profits from assets owned (Atidhira & Yustina, 2017: 130) are used in this study to represent profitability ratios The concept of economic value added or economic value added began in the early 1990s when Stern Stewart & Co. created a trademark on economic value added. Economic value Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 225 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 added includes a relatively new company performance analysis tool compared to conventional financial ratios such as activity ratios, liquidity ratios, ratios, solvency, and profitability ratios. This added economic value will ensure that management operates the company consistently with the concept of increasing shareholder value (Brigham & Ehrhardt, 2011: 69). Economic value added is then developed into human economic value added by considering the perspective of human capital (Kumar and Basu, 2013: 64). Human economic value added is useful for measuring the added value created by companies per employee. Pulic in 1998 created a new concept to measure a company's intellectual capital and in 2004 Pulic introduced the concept of Value Added Intellectual Coefficient (VAIC) which consisted of several main components namely Capital Employee Efficiency (CEE), Human Capital Efficiency (HCE), and Structural Capital Efficiency (SCE) (Sirapanji and Hatane, 2015: 46). The concept of intellectual capital put forward by Pulic is motivated by the assumptions of the majority of economic and financial models that view employees as costs and not as resources. Intellectual capital itself is useful in measuring the company's non-physical resources such as human capital (skills, experience, training, etc.), relational capital (relationships with customers and stakeholders, brands, company agreements, etc.), and structural capital (culture organization, work environment, and system) (Stahle, Stahle, and Aho, 2011: 532). METHOD The object of this research is the data of 32 companies engaged in the energy sector which are listed on the Indonesia Stock Exchange and data on 22 companies engaged in the energy sector which are listed on the Malaysia Stock Exchange between 2014 and 2018. The research method used is quantitative research methods. by describing the effect of each independent variable on the dependent variable examined through the process of collecting, processing, and interpreting the data obtained using statistical analysis. The data analysis method used in this study is multiple regression of panel data using the Ordinary Least Squares (OLS) method with the help of Eviews software version 9.0. Several tests were carried out to support the regression analysis, including chow test, normality test, multicollinearity test, heterocedasticity test, autocorrelation test, and t test for regression results. Next In order to analyze the effect of independent variables on the dependent variable, multiple regression equations are made as follows: Y = α + β1TATO + β2CR + β3DER + β4ROA + β5EVA + β6HEVA + β7VAIC + e Variables Stock return is the difference in the current investment value with the initial investment value for a certain period. Stock returns can be calculated using the following formula: Stock Return = Capital Gain/Loss + Dividend Yield Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 226 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 Total asset turnover is a financial ratio that is used to measure a company's ability to generate sales by utilizing its assets. The formula for calculating total asset turnover is as follows: Total Asset Turnover = SaSec TotaS Æccet In order to calculate the current ratio, the data of current assets and current liabilities are obtained from each company's financial statements with the following formula: Current Ratio = Current Æccet Current LiabiSitiec Debt to equity ratio is a measure of a company's ability to pay short-term debt and long- term debt. The formula for calculating the debt to equity ratio is as follows: Debt to Equity Ratio = TotaS Debt TotaS Equity Return on assets is calculated by dividing the company's net income by the average total assets (Weygrandt et al., 2013: 699; Robinson, 2009: 292). From this description, it can be seen the formula for calculating return on assets is as follows: Return on Asset = Net IncoNe TotaS Æccet Æverage Economic value added is calculated by reducing NOPAT to the value of cost of capital, so the formula for calculating economic value added is as follows: EVA = NOPAT – ( Invested Capital x WACC ) In which: WACC = wd kd (1-T) + we ke Notes: WACC = Weighted Average Cost of Capital EBIT = Earning Before Interest and Taxes NOPAT = EBIT (1-T) Invested Capital = Total Equity – (Total Debt-Current Debt) wd = Debt proportion kd (1-T) = Debt costs after taxes we = Equity proportion ke = Equity costs The amount of the cost of equity used can be calculated using the formula Capital Asset Pricing Model (CAPM) with the following formula: Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 227 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 CAPM = krf + β ( km - krf ) Notes: krf = Risk free rate km = Market return β = Company Beta (non diversifiable risk) Jones, Utama, Frensidy, Ekaputra, and Budiman (2009: 239) define a company beta as a relative measurement of a company's risk to the market portfolio for all shares. To calculate company beta, Jones et al. (2009: 239) explain that the equation of the single index model as follows can be used: Ri = αi + βi Rm + e Notes: Ri : the return on security i Rm : the return on market index αi : intercept βi : slope e : error term To calculate human economic value added, full time equivalent data is obtained from each company's financial statements. The formula for calculating human economic value added is as follows: Human Economic Value Added = EconoNic VaSue Ædded FuSS tiNe EquivaSent Value added intellectual coefficient is the sum of the value of Intellectual Capital Efficiency (ICE) and Capital Employed Efficiency (CEE), where ICE itself is the sum of the Human Capital Efficiency (HCE), and Structural Capital Efficiency (SCE). These explanations can be summarized in the formula: VAIC = HCE + SCE + CEE or VAIC = HCE + SCE + CEE Referring to the explanation of Pulic (2004: 64), the detailed formula used to calculate the value added intellectual coefficient is as follows: HCE = VÆ KC In which VA = OUT – IN Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 228 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 or VA = OP + EC + D + A In which SC = VA – HC HCE = VÆ KC SCE = SC VÆ CEE = VÆ CE Notes: VA = Value Added HC = Human Capital CE = Book value of the net assets (total assets – total liabilities) OUT = Total sales IN = Cost of Bought-in Materials, Components, and Services OP = Operating EC = Employee Costs D = Depreciation A = Amortization RESULT AND DISCUSSION Regression Model Approach Test Table 1 Chow Test Results of Energy Company Data in Indonesia Effects test Statistic d.f. Prob. Cross-section F 2.907014 (15,8) 0.0657 Cross-section Chi-square 57.789611 15 0,0000 Table 2 Chow Test Results of Energy Company Data in Malaysia Effects test Statistic d.f. Prob. Cross-section F 2.427026 (9,2) 0.3258 Cross-section Chi-square 47.088711 9 0.0000 From the results of the Chow test as presented in tables 1 and 2 above, it can be seen that the probability value of the two Chow tests is more than 0.05. These results indicate that in this test the best model that can be used in regression analysis is the common effect.Uji Normalitas, Multikolinearitas, Heterokedastisitas, dan Autokorelasi Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 229 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 For energy company data in Indonesia, the probability value of the Jarque-Bera test results using residual data is 0.3611, while for the energy company data in Malaysia is 0.728417, where both values are greater than the test probability set which is equal to 0.05. From this information it can be seen that the residual data has been normally distributed or in other words it can be concluded that there is no normality problem in the existing data. Multicollinearity test is performed to detect the linear relationship between independent variables. The close relationship between independent variables causes one of the assumptions to not be fulfilled in an effort to obtain estimators that are not biased, linear, and have minimum variants. From the multicollinearity test results on energy company data in Indonesia and Malaysia, there is no correlation between independent variables above 0.85, so it can be concluded that from the data there are no multicollinearity problems in the analysis. Table 3 Heterokedasticity Test Results for Energy Companies in Indonesia Dependent Variable: RESABS Table 4 Heterokedasticity Test Results for Energy Companies in Malaysia Dependent Variable: RESABS From tables 3 and 4 above, it can be seen that the probability value of each independent variable coefficient of the glacial test results is insignificant or more than 5%, so it can be said that there is no heterocedasticity problem in the data used in the analysis in this study. To test whether there is an autocorrelation problem, the Durbin-Watson test can be used by referring to the Durbin-Watson table. The value of d was obtained from the regression results in the amount of 2,066, with the amount of data processed in the regression of 160 for energy company data in Indonesia and the d value of 2,022, with the amount of data processed in the regression of 105 for the energy company data in Malaysia. Referring to the existing data, the Durbin-Watson table sets the d value limit where there is no autocorrelation problem at Variable Coefficient Prob TATO -0.142200 0.6692 CR -0.014397 0.7699 DER 0.207363 0.3052 ROA 0.268867 0.8753 EVA -5.818794 0.7523 HEVA -1.534235 0.8358 VAIC -0.005795 0.3659 Variable Coefficient Prob TATO -0.047525 0.8467 CR 0.072356 0.8199 DER 0.088064 0.8535 ROA 0.705433 0.3359 EVA 0.051327 0.8534 HEVA -0.180772 0.5267 VAIC -0.006784 0.9223 Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 230 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 approximately 2. Furthermore, given that the d value obtained from the regression results is 2,066 and 2,022, it can be concluded that the analyzed data there is no autocorrelation problem. Regression Result Based on panel data regression analysis using the OLS method with the common effect model as the chosen model, a regression result is obtained that illustrates the effect of total asset turnover, current assets, debt to equity ratio, return on assets, economic value added, human economic value added, and value added intellectual capital to stock returns as shown in table 5 as follows: Table 5 Regression Results of Energy Company Data in Indonesia and Malaysia Dependent Variable SR (Indonesia) SR (Malaysia) Independent Variable C 0.472936 - 10.16090 TATO - 1.303983 1.333708 *** CR 0.133041 - 0.873381 DER - 0.893373 ** - 0.303474 ROA 1.731458 - 1.827673 EVA 0.524723 *** 1.022512 ** HEVA - 0.628547 ** - 0.779515 VAIC 0.032690 *** 0.296690 *** Note: ** and *** show significant level of 5% dan 10% respectively The results of data analysis of energy companies in Indonesia show that total asset turnover has no significant effect on stock returns, while in Malaysia it shows a positive and significant effect. This positive and significant influence in Malaysia further confirms the results of previous studies which have been conducted by several researchers such as Zamzami and Afif (2015), Yuliantari and Sujana (2014), and Medyawati and Yunanto (2017). The insignificant effect of the current ratio variable on stock returns is equally shown by data in both the two countries of Indonesia and Malaysia. The limited number of population of companies engaged in the energy sector is indicated as one of the causes of this significant result, where there are no more than 40 companies in Indonesia and no more than 30 companies in Malaysia engaged in the energy sector, and not the entire population meets the criteria of purposive sampling to be analyzed as a sample. For the debt to quity ratio variable, the negative sign on the coefficient is shown by all the data in Indonesia and Malaysia, only for the regression results in Indonesia the effect of the debt to quity ratio on stock returns is proven significant, while data in Malaysia shows the Conventional Financial Performance, Economic Value Added, Human Economic Value Added, Value Added Intellectual Coefficient And Its Impact On Stock Return Of Companies Operating In Energy Sector In Indonesia And Malaysia Anton Wijaya 231 | Ilomata International Journal of Tax & Accounting Volume 2 Issue 31, July 2021 opposite. The insignificant effect of the variable return on assets on stock returns is equally shown by data in both the two countries of Indonesia and Malaysia. As with the current ratio, the limited number of samples is indicated to be a cause of insignificant results. Another factor that may be the cause of the insignificant influence of return on assets on stock returns is the existence of other variables in the data processing. As is known, the existence of a control variable will also determine the value and significance of the variable being studied. In this case, researchers have tried to do a regression by eliminating other variables that are indicated to be affiliated with the variable return on assets, including economic value added variables, human economic value added, and value added intellectual coefficient. From the results of trials conducted by researchers, proven return on assets has a positive and significant effect on stock returns. The results of the analysis of the data of companies engaged in the energy sector both in Indonesia and Malaysia produce the same conclusions related to the influence of economic value added, namely there is a positive and significant influence of economic value added variables on stock returns. Some previous studies that have the same conclusions, among others, conducted by Awan et al. (2014), Worthington & West (2004), Akbar, Khan, and Ali (2010), Amyulianthi and Ritonga (2016), Babatunde & Evuebie (2017), and Nugroho (2018). The results of an analysis of data from companies engaged in the energy sector in Indonesia have concluded that there is a negative and significant influence from the human economic value added variable on stock returns. The negative coefficient is similar to the data in Malaysia, only the difference in the data in Malaysia shows insignificant results. From the author's analysis, the difference in the coefficient symbol between economic value added and human economic value added is caused by an increase or decrease in the number of employees of the company within the five years of the study. The majority of companies show a declining trend in the number of employees in the 2014-2015 period. In the case that the number of employees has not changed, then economic value added and human economic value added should have the same effect on stock returns. The results of research on energy companies both in Indonesia and Malaysia show the same conclusions related to the effect of the value added intellectual coefficient, namely the value added intellectual coefficient has a positive effect on stock returns at a significance level of 5%. These results reinforce the conclusions of a number of previous studies that have been carried out by Ahmed, Khurshid and Yousaf (2019) and Firmansari, Migdad and Kustono (2019). This positive coefficient illustrates that the more efficient a company is in utilizing its resources, the greater the potential of the company to generate profits, where it should further encourage increased profits, dividends, as well as the attractiveness of investors to invest in the company. CONCLUSION The results of an analysis of energy company data in Indonesia show that debt to equity ratio and human economic value added have a negative and significant effect on stock returns, while economic value added and value added intellectual capital have a positive and significant effect on stock returns. As for the object of research on energy companies in Malaysia, the results showed that total asset turnover, economic value added and value added intellectual capital had a positive and significant effect on stock returns. Further research can add other factors both internal and external sources of the company that have the potential to influence stock returns in order to obtain better research results. 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