Syntax
Literate: Jurnal Ilmiah
Indonesia p�ISSN: 2541-0849 e-ISSN: 2548-1398
Vol. 8, No.
12, December 2023
THE ROLE OF THE CEO'S EDUCATIONAL
BACKGROUND ON THE RELATIONSHIP BETWEEN INTELLECTUAL CAPITAL AND PERFORMANCE
AMONG INDONESIAN LISTED BANKS
Samantha Agnesia Lidya Br. Gultom,
Arief Wibisono Lubis
Faculty Economics and Business
Universitas Indonesia, Jakarta, Indonesia
Email: [email protected]
Abstract
The
transition from a physical resource-based economy to a knowledge-based economy
has encouraged researchers to look for new ways to measure intangible assets
such as intellectual capital. This study tests and analyzes the effect of
intellectual capital on company performance and the role of educational
background in the influence of intellectual capital on the performance of
banking companies listed on the Indonesian stock exchange for the period
2018-2022. This study uses secondary data obtained from the official website of
the sample company. The number of samples in this study was 47 banks listed on
the Indonesian Stock Exchange (IDX). The value-added intellectual coefficient
(VAIC) method was used to measure the added value of intellectual capital. This
study uses quantitative methods with panel data regression to analyze the
effect of intellectual capital on company performance and the effect of
managing directors� educational background on the relationship between
intellectual capital and company performance. These findings show how IC
elements of intellectual capital affect financial performance. We discover that
IC improves the ROA and ROE of Banking Companies Listed in Indonesia, data
analysis results indicate that the educational background of the managing
director has a varying impact on the relationship between intellectual capital
(IC) and company performance, as measured by return on assets (ROA) but not to
return on equity (ROE). To the best of the author�s knowledge. This is the
first empirical study to evaluate the Role of a CEO's educational background in
affecting Intellectual Capital in the performance of banking companies listed
in Indonesia.
Keywords: Firm Performance, Intellectual Capital, VAIC, Educational Background of CEO
Introduction
Intellectual Capital is a predictor of
firm performance and a source of competitive advantage (Faruq et al. 2023). IC
creates value in this global era to achieve efficiency, increase financial
performance, and maintain financial stability. They argue that in the global
economy, largely and increasingly, the ability to compete depends on value
creation through investments in IC (Ullah et al. 2021). The focus on IC and
intangible assets that have arisen in the last few years is opening up a series
of questions that may reform business and economics in an environment of global
interdependency, environmental concerns, and a larger responsibility. In this
study, intellectual capital is linked to expenses related to the company's
operations and management. Intellectual capital encompasses intangible assets
that augment the company's value.
IC and intangible assets offer a
possible pathway for reconciling business and economic models with a better
understanding of the interrelationships between the impact of economic activity
and the potential health and well-being of society and the environment (Jardon
& Dasilva, 2017). According to a study conducted by Ulum et al.
(2014), the performance of intellectual capital in the banking industry in
Indonesia is observed. The research findings indicate that the average VAIC
score in the sample used for this study is 2.07, which falls within the group
of good performers.
The VAIC model calculation yields
results that can be categorized into four groups based on the VAIC score of
each bank. These groups include: (1) top performers, which are banks with a
VAIC score above 3, (2) good performers, which are banks with a VAIC score
between 2.0 and 2.99, (3) common performers, which are banks with a VAIC score
between 1.5 and 1.99, and (4) bad performers, which are banks with a VAIC score
below 1.5.
Indonesia has a bank-centric economy,
with banks controlling 80% of the country's total financial industry assets
The decision-making process of
directors significantly impacts the determination of whether or not to invest
in intellectual capital within a corporation. Many scholarly investigations
tend to focus on specific dimensions of intellectual capital (IC) and primarily
examine its operational dynamics within the realm of business. Limited research
has been conducted into the distinct characteristics exhibited by senior
management, particularly directors, who hold significant influence in
determining the allocation of an organization's resources.
The competencies
and expertise possessed by an organization's leaders can serve as an indicator
of the company's performance and quality. When selecting their CEOs, firms
consider this factor to maintain a competitive edge
However,
further investigation is needed to explore this relationship in greater depth. This
study examines the impact of intellectual capital on firm performance (ROA,
ROE) and how the CEO�s educational background affects the relationship between
intellectual capital and firm performance. The study conducted by
This can
be attributed to the underdeveloped financial structures prevalent in
developing countries, resulting in limited emphasis on the intangible assets or
intellectual capital of companies. The assertion made by
Research Methods
This study utilizes data from financial companies that have
been selected based on specific criteria. Utilize the dataset to acquire
comprehensive knowledge regarding the research variables. The IDX website
offers audited financial and annual reports of banking firms for this inquiry.
The data spans the years 2018 to 2022. The final sample consists of 235
bank-year observations.
This research centers around the dependent variable. This
study primarily assesses the financial performance of a corporation. The Return
on Assets (ROA) and Return on Equity (ROE) indices serve as measures of a
company's total performance in Faruq et al. (2023). ROA = [Profit after
tax/Total Assets], ROE = [Profit after tax/Total Equity]. This study employs Pulic's (2000) Value Added Intellectual Coefficient (VAIC)
as a metric for quantifying intellectual capital. VAIC is determined by summing
together the efficiencies of human capital (HCE), structural capital (SCE), and
capital employed (CEE). �VAIC is
calculated using a methodology:
VAIC = Human Capital Efficiency + Structural
Capital Efficiency + Capital Employed Efficiency
Human capital efficiency (HCE) is one of the computations
included in the computation of VAIC.��
Human Capital Efficiency (HCE) is determined by assessing the ratio of
added value to human capital. The key factors included in the computation of
HCE include total employee expenditures and salary expenses (Mondal &
Ghosh, 2012).�� The formulation of HCE
can be expressed using the following equation:�
HCE = VA/HC
Value Added (VA) refers to the additional value
that is generated within a company to enhance its overall performance.�� The calculation of value added is based on
the research conducted by Faruq et al. (2023) and is determined using the
following formula:
VA = TS (Total Sales) - COMSC (Cost of Materials, Services,
and Components) = OP (Operating Profit) + EC (Employment Cost) + (Total
Depreciation and Amortization)
Structural Capital Efficiency (SCE) is a
quantitative measure used to assess the effectiveness of the value generated by
the structural capital. It is determined by comparing the value of the
Structural Capital (SC) to the Value Added (VA).�� The success of value-added creation by
structural capital can be attributed to the efficiency of its structural
capital.�� Faruq et al. (2023). The
formula for SCE is as follows:�
SCE = SC/VA
Capital employed efficiency (CEE) represents the
final component of the Value Added Intellectual
Coefficient (VAIC). This mathematical analysis quantifies the amount of value
added (VA) that is produced from the capital employed, encompassing both
monetary capital and tangible assets. Faruq et al. (2023) stated that CEE can
be determined by comparing the new value with the capital employed. The
subsequent procedure is employed to determine the CEE:
CEE = VA/CE
This variable can be utilized to mitigate the
potential for computation bias when determining the correlation between the
independent variable and the dependent variable (Nimtrakoon,
2015)�firm Size. The size of a firm is determined by taking the natural
logarithm of its total assets. DER. The debt-to-equity ratio is calculated by
dividing the total leverage by the total equity.��
����������� NPL. The
formula for calculating the Non-Performing Loan ratio is as follows: NPL =
Total NPL divided by Total Credit. Covid-19. The COVID-19 variable is derived using
a binary variable.�� Faruq et al. (2023)
assign a value of 1 to the epidemic period (2020-2022) and a value of 0 to the
period preceding the pandemic (2018-2019).
Apriadi et al. (2017) found that directors with formal education
in economics and business possess a more profound comprehension of the
complexities of the banking sector, along with an enhanced awareness of company
financial reporting. Measurement is conducted using dummy variables. The
assigned value is 1 for individuals with a Master of Business Administration
(MBA) educational background and 0 for individuals with any qualification other
than an MBA.
Table 1
Variable description
|
Variable
Name |
Label |
Description |
Source
of Data |
Source |
|
Dependent
Variables |
||||
|
Return On
Asset |
ROA |
The ratio
of profit after tax/Total Asset |
Annual
reports |
(Faruq et
al., 2023) |
|
Return On
Equity |
ROE |
The ratio
of profit after tax/Total Equity |
Annual
Reports |
(Faruq et
al., 2023) |
|
Independent
Variable |
||||
|
Intellectual
Capital |
VAIC |
HCE + SCE
+ CEE |
Author�s
Calculation |
|
|
Human
Capital Efficiency |
HCE |
VA / HC |
Author�s
Calculation |
(Tran & Vo, 2018) |
|
Structural
Capital Efficiency |
SCE |
SC / VA |
Author�s
Calculation |
(Tran & Vo, 2018) |
|
Capital
Employed Efficiency |
CEE |
VA / CE |
Author�s
Calculation |
(Tran & Vo, 2018) |
|
Moderating
Variable |
||||
|
Director�s
Educational Background |
CEO EDU |
Directors
with formal education in Master of Business Administration (MBA) |
Annual
report |
Author�s
idea |
|
Control
Variables |
||||
|
Firm Size |
SIZE |
Natural
logarithm of total assets |
Author�s
Calculation |
|
|
Debt to
Equity Ratio |
DER |
Total
Leverage / Total Equity |
Author�s
Calculation |
|
|
Non-Performing
Loan |
NPL |
Total NPL
/ Total Credit |
Author�s
Calculation |
|
|
Covid-19 |
COV-19 |
The period
the company began to be affected by the covid-19 |
Annual
Report |
|
Empirical model
Intellectual capital is determined by aggregating the financial and physical capital of a corporation (Pulic, 2000).� Companies employ their tangible and monetary resources, whereas the company's intangible assets affect the efficiency of utilizing these tangible and monetary resources.�� The regression equation used to assess the impact of intellectual capital (IC) on corporate performance, as referenced in the study by Nadeem et al. (2019), is as follows:
Regression model 1 examines the impact of intellectual capital on the success of a corporation:
1a. ROAi,t = α + β1ICi,t + β2SIZEi,t + β3DERi,t + β4NPLi,t + β6COV19i,t + e�
1b. ROEi,t = α
+ β1ICi,t + β2SIZEi,t
+ β3DERi,t + β4NPLi,t +
β6COV19i,t + e�
Regression model 2 examines the impact of the CEO's educational background on the correlation between intellectual capital
2a. ROAi,t = α + β1ICi,t + β2EDUi,t� +β2IC*EDUi,t + β3SIZEi,t + β4DERi,t + β5NPLi,t + β7COV19i,t + e�
2b. ROEi,t = α + β1ICi,t + β2EDUi,t� +β2IC*EDUi,t + β3SIZEi,t + β4DERi,t + β5NPLi,t + β7COV19i,t + e�
In the above models, IC is an independent variable; ROA and ROE are the dependent variables of financial performance; IC*EDU is the interaction variable between IC and the director�s educational background; SIZE, DER, NPL, and COV19 are the control variables; α and β are the coefficients of each variable and e represents the random error.
Results and Discussion
Descriptive
statistics
Table 2 presents the findings of a descriptive statistical analysis on many factors related to business performance, including return on assets (ROA) and return on equity (ROE), intellectual capital, CEO education, firm size, non-performing loan, debt to equity ratio, and the impact of the Covid-19 pandemic.
Table 2
Descriptive statistics
|
Variable |
Mean |
Std. Dev |
Min |
Max |
|
ROA |
0.0041 |
0.01993 |
-0.0544 |
0.0311 |
|
ROE |
0.0312 |
0.9643 |
-0.2262 |
0.1667 |
|
IC |
3.1989 |
1.8002 |
7.1341 |
|
|
CEO EDU |
0.4468 |
0.4982 |
0.0000 |
1.0000 |
|
FIRM SIZE |
31.1896 |
1.8284 |
27.2184 |
35.2282 |
|
NPL |
0.0384 |
0.0542 |
0.0000 |
0.7740 |
|
DEBT TO
EQUITY |
5.3586 |
3.0009 |
0.0809 |
17.0714 |
|
COVID19 |
0.6000 |
0.4909 |
0.0000 |
1.0000 |
The findings of the descriptive
statistical analysis indicate that the IC (VAIC) variable has a minimum value
of -0.6529 and
a maximum value of 7.1341.�� The mean value of IC is 3.1989, with a standard
deviation of 1.8002.�� Ulum (2008) categorizes the calculation
results of the VAIC model for each bank into four groups depending on the VAIC
score of each bank. With an average value of 3.1989, it is evident that banking companies in
Indonesia are highly successful.
Correlation
analysis
Table 3 presents the results of the
correlation test, indicating that the regression model employed does not
exhibit multicollinearity among the independent variables. Specifically, each
independent variable used demonstrates a correlation coefficient value below
|0.8|. Basuki & Prawoto (2015) state that a correlation coefficient over
|0.8| between independent variables signifies the presence of
multicollinearity.�
Table 3
Correlation Test
Results
|
|
IC |
CEOEDU |
IC_EDU |
SIZE |
NPL |
DER |
COV-19 |
|
IC |
1.0000 |
|
|
|
|
|
|
|
CEOEDU |
0.0689 |
1.0000 |
|
|
|
|
|
|
IC_EDU |
0.4127 |
0.8257 |
1.0000 |
|
|
|
|
|
SIZE |
0.2750 |
-0.0229 |
0.0396 |
1.0000 |
|
|
|
|
NPL |
-0.2100 |
0.0887 |
-0.0503 |
-0.1215 |
1.0000 |
|
|
|
DER |
0.0296 |
-0.0108 |
0.0315 |
0.4237 |
-0.0009 |
1.0000 |
|
|
COV-19 |
0.0274 |
-0.0175 |
-0.0205 |
0.1025 |
-0.0912 |
-0.0487 |
1.0000 |
Regression results
After conducting
several tests, such as the Chow test and Hausman test, to analyze panel data,
Models 1a, 1b, 2a,
and 2b are estimated using a one-way
individual-specific fixed effect model. This study uses a one-tailed hypothesis
test.
Table 4
Regression results
|
Variables |
Model
1a |
Model 1b |
Model 2a |
Model 2b |
|
C |
0.057* |
0.0980* |
0.0270** |
0.1020 |
|
IC |
0.0145** |
0.0100** |
0.000*** |
0.0540* |
|
IC_EDU |
|
|
0.0210** |
0.0315** |
|
SIZE |
0.2200 |
0.0525* |
0.0150** |
0.0505* |
|
NPL |
0.475 |
0.3255 |
0.4395 |
0.3535 |
|
DER |
0.4830* |
0.1345 |
0.4950 |
0.1020 |
|
COV-19 |
0.0275** |
0.0120** |
0.0025*** |
0.0135** |
|
R-Squared |
0.4059 |
0.4985 |
0.3939 |
0.4761 |
|
Adj
R-Squared |
0.3093 |
0.4120 |
0.3085 |
0.4079 |
|
F-stat |
9.96 |
12.67 |
7.12 |
22.69 |
|
Prob >
F |
0.000 |
0.000 |
0.000 |
0.000 |
Note:
*,**,*** denote statistical sig at the 0.1, 0.05, 0.01
The
Figure in the parentheses are the t-statistics
Model 1a. The IC variable has a probability value
of 0.000, indicating that this value is statistically significant at the 1%,
5%, and 10% confidence levels. Therefore, the null hypothesis (Ho) is rejected.
�Given
that the estimated F value of 9.03 exceeds the F table value of 2.137, with a
probability value of 0.000 <0.05, we can accept the alternative hypothesis
(Ha) which states that the independent variable (IC) has a significant effect
on firm performance (ROA). Therefore, it may be inferred that there is a notable
and favorable impact exerted by IC on ROA.
Model 1b. The IC variable has a probability value
of 0.0100, indicating that this
value is statistically significant at the 5% and 10% confidence levels, leading
to the rejection of Ho.�� Upon comparing
the estimated F value of 12.67 to
the F table value of 2.137, with a probability value of 0.000 <0.05, it can
be concluded that Ha is accepted. This indicates that the independent variable
(IC) has a significant effect on the company's performance (ROE).�� Therefore, it may be inferred that there is
a notable and favorable impact exerted by IC on ROE.
The results of this study are in line
with the results of research from Ur Rehman et al. (2022) state that there is a
positive and significant effect of IC on ROA, ROE, and TQ in banking companies.
This is also in line with research conducted by Ullah et al. (2021), Soewarno
& Tjahjadi (2020), Ghozali et al. (2020), Bontis et al. (2018), Chowdhury
et al. (2018) [Model 1 and 2]. The study's findings suggest that the company's
intellectual capital (IC) can create extra value for the company. The inclusion
of this extra value will be advantageous in the establishment and improvement
of the company's competitive edge, as per the resource-based theory (1984).
Model 2a. The probability value of the interaction
variable between IC and the educational background of the managing director is
0.0210. This indicates that the
variable is statistically significant at the 5%, and 10% confidence
levels. Therefore, the null hypothesis (Ho) is rejected. Additionally, the
F-count in this regression result is 7.12,
which is greater than the F-table value of 2.137 with a probability value of
0.000, which is less than 0.05. Consequently, the alternative hypothesis (Ha)
is accepted.�� The positive coefficient
indicates that the educational background of the managing director enhances the
impact of IC on ROA.
Model 2b. The probability value of the interaction
variable between IC and the educational background of the CEO is 0.0315. This indicates that the
variable is statistically significant at the 5%, and 10% confidence
levels. Therefore, the null hypothesis (Ho) is rejected. Additionally, the
F-count in this regression result is 22.69,
which is greater than the F-table value of 2.137 with a probability value of
0.000, which is less than 0.05. Consequently, the alternative hypothesis (Ha)
is accepted.�� The positive coefficient
indicates that the educational background of the managing director enhances the
impact of IC on ROE.
Conclusion
The data analysis results indicate that the impact of Intellectual
Capital (IC), as assessed by �Value Added
Intellectual Coefficient (VAIC), on corporate performance, as represented by
Return on Assets (ROA) and Return on Equity (ROE), are both statistically
significant. The positive sign of the IC variable regression coefficient
suggests a positive influence exerted by IC. The company's performance is
directly proportional to the value of the IC it owns. Therefore,
the conclusion that can be inferred is that Ha is corroborated, which asserts
that IC has a favorable impact on both ROA and ROE.
The data analysis results indicate that the educational background of the
managing director has a varying impact on the relationship between intellectual
capital (IC) and company performance, as measured by return on assets (ROA) and
return on equity (ROE).�� The data
analysis results demonstrate the impact of moderating variables, specifically
the educational background of the managing director, on the correlation between
intellectual capital (IC) and company profitability (ROA, ROE). The p-value of
the interaction term between IC and the educational background of the managing
director on ROA and ROE is less than 0.05. These findings indicate that the
educational qualifications of the managing director have a substantial impact
on the profitability of the company. The regression coefficient in this model
is positive, indicating that the educational background of the managing
director enhances the correlation between intellectual capital (IC) and company
profitability. Therefore, it can be inferred that there is evidence to support
the hypothesis H2.
This study focuses exclusively on the analysis of the banking industry
and does not encompass other financial organizations, such as insurance firms
and investment trusts. Hence, forthcoming research endeavors could
encompass all enterprises functioning within the finance industry and employ
other methodologies to assess the intellectual capital performance of financial
institutions.
BIBLIOGRAPHY
Abatecola, G., & Cristofaro, M. (2020). Hambrick and
Mason�s �Upper Echelons Theory�: evolution and open avenues. Journal of
Management History, 26(1), 116�136.
https://doi.org/10.1108/JMH-02-2018-0016
Adawiyah, A. R., & Lisiantara, G. A. (2022). Pengaruh Pandemi COVID-19 Terhadap Kinerja Keuangan Perbankan. 15(2), 465�474. http://journal.stekom.ac.id/index.php/kompakpage465
AlQershi, N., Saufi, R. B. A., Ismail, N. A., Mohamad, M. R. Bin, Ramayah, T., Muhammad, N. M. N., & Yusoff, M. N. H. Bin. (2023). The moderating role of market turbulence beyond the Covid-19 pandemic and Russia-Ukraine crisis on the relationship between intellectual capital and business sustainability. Technological Forecasting and Social Change, 186. https://doi.org/10.1016/j.techfore.2022.122081
Bhagat, S., Bolton, B., & Subramanian, A. (2010). CEO Education, CEO Turnover, and Firm Performance. http://ssrn.com/abstract=1670219
Bontis, N., Ciambotti, M., Palazzi, F., & Sgro, F. (2018). Intellectual capital and financial performance in social cooperative enterprises. Journal of Intellectual Capital, 19(4), 712�731. https://doi.org/10.1108/JIC-03-2017-0049
Chevalier, J., & Ellison, G. (1999). Are Some Mutual Fund Managers Better Than Others? Cross-Sectional Patterns in Behavior and Performance. In THE JOURNAL OF FINANCE �: Vol. LIV (Issue 3).
Chowdhury, L. A. M., Rana, T., Akter, M., & Hoque, M. (2018). Impact of intellectual capital on financial performance: evidence from the Bangladeshi textile sector. Journal of Accounting and Organizational Change, 14(4), 429�454. https://doi.org/10.1108/JAOC-11-2017-0109
Colvin, R. M., Witt, G. B., & Lacey, J. (2020). Power, perspective, and privilege: The challenge of translating stakeholder theory from business management to environmental and natural resource management. Journal of Environmental Management, 271. https://doi.org/10.1016/j.jenvman.2020.110974
Erlim, K. W., & Juliana, R. (2017). Pengaruh Tingkat Edukasi dan Spesialisasi Pendidikan CEO terhadap Performa Perusahaan di Indonesia. Jurnal Manajemen Maranatha, 16(2), 177. https://doi.org/10.28932/jmm.v16i2.388
Faruq, M. O., Akter, T., & Mizanur Rahman, M. (2023). Does intellectual capital drive a bank�s performance in Bangladesh? Evidence from static and dynamic approach. Heliyon, 9(7), e17656. https://doi.org/10.1016/j.heliyon.2023.e17656
Garc�a Castro, J. P., Duque Ram�rez, D. F., & Moscoso Escobar, J. (2021a). The relationship between intellectual capital and financial performance in Colombian listed banking entities. Asia Pacific Management Review, 26(4), 237�247. https://doi.org/10.1016/j.apmrv.2021.03.002
Garc�a Castro, J. P., Duque Ram�rez, D. F., & Moscoso Escobar, J. (2021b). The relationship between intellectual capital and financial performance in Colombian listed banking entities. Asia Pacific Management Review, 26(4), 237�247. https://doi.org/10.1016/j.apmrv.2021.03.002
Ghozali, I., Harto, P., Susanto, H., & Zainuddin, F. (2020). Intellectual capital and financial performance of state-owned banking: evidence from Indonesia. In Int. J. Learning and Intellectual Capital (Vol. 17, Issue 1).
Hambrick, D. C., & Mason, P. A. (1984). Upper Echelons: The Organization as a Reflection of Its Top Managers. In Source: The Academy of Management Review (Vol. 9, Issue 2).
Jardon, C. M., & Dasilva, A. (2017). Intellectual capital and environmental concern in subsistence small businesses. Management of Environmental Quality: An International Journal, 28(2), 214�230. https://doi.org/10.1108/MEQ-05-2015-0085
King, T., Srivastav, A., & Williams, J. (2016). What�s in an education? Implications of CEO education for bank performance. Journal of Corporate Finance, 37, 287�308. https://doi.org/10.1016/j.jcorpfin.2016.01.003
Miles, S. (2012). Stakeholder: Essentially Contested or Just Confused? Journal of Business Ethics, 108(3), 285�298. https://doi.org/10.1007/s10551-011-1090-8
Mondal, A., & Ghosh, S. K. (2012). Intellectual capital and financial performance of Indian banks. Journal of Intellectual Capital, 13(4), 515�530. https://doi.org/10.1108/14691931211276115
Mun, S., Han, S. H., & Seo, D. (2020). The impact of CEO educational background on corporate cash holdings and value of excess cash. Pacific Basin Finance Journal, 61. https://doi.org/10.1016/j.pacfin.2020.101339
Nadeem, M., Zaman, R., Suleman, T., & Atawnah, N. (2021). CEO ability, career concerns, firms� lifecycle, and investment in intellectual capital. International Review of Economics and Finance, 237�251.
Nimtrakoon, S. (2015). The relationship between intellectual capital, firms� market value, and financial performance: Empirical evidence from the ASEAN. Journal of Intellectual Capital, 16(3), 587�618. https://doi.org/10.1108/JIC-09-2014-0104
Ozkan, N., Cakan, S., & Kayacan, M. (2017). Intellectual capital and financial performance: A study of the Turkish Banking Sector. Borsa Istanbul Review, 17(3), 190�198. https://doi.org/10.1016/j.bir.2016.03.001
Pontinha, V. M., Wagner, T. D., & Holdford, D. A. (2021). Point-of-care testing in pharmacies�An evaluation of the service from the lens of the resource-based theory of competitive advantage. In Journal of the American Pharmacists Association (Vol. 61, Issue 2, pp. e45�e54). Elsevier B.V. https://doi.org/10.1016/j.japh.2020.11.005
Popli, M., Ahsan, F. M., & Mukherjee, D. (2022). Upper echelons and firm internationalization: A critical review and future directions. Journal of Business Research, 152, 505�521. https://doi.org/10.1016/j.jbusres.2022.07.048
Pulic, A. (1998). Measuring the Performance of Intellectual Potential in Knowledge Economy (presented in 1998 at the 2nd McMaster World Congress on Measuring and Managing Intellectual Capital by the Austrian Team for Intellectual Potential).
Shahwan, T. M., & Fathalla, M. M. (2020). The mediating role of intellectual capital in corporate governance and the corporate performance relationship. International Journal of Ethics and Systems, 36(4), 531�561. https://doi.org/10.1108/IJOES-03-2020-0022
Soewarno, N., & Tjahjadi, B. (2020). Measures that matter: an empirical investigation of intellectual capital and financial performance of banking firms in Indonesia. Journal of Intellectual Capital, 21(6), 1085�1106. https://doi.org/10.1108/JIC-09-2019-0225
Subaida, I., & Mardiati, N. E. (2018). Effect of Intellectual Capital and Intellectual Capital Disclosure on Firm Value. Journal of Applied Management. https://doi.org/10.21776/ub.jam.2018.016
Tran, D. B., & Vo, D. H. (2018). Should bankers be concerned with Intellectual capital? A study of the Thai banking sector. Journal of Intellectual Capital, 19(5), 897�914. https://doi.org/10.1108/JIC-12-2017-0185
Ullah, A., Pinglu, C., Ullah, S., Qian, N., & Zaman, M. (2021). Impact of intellectual capital efficiency on financial stability in banks: Insights from an emerging economy abstract. International Journal of Finance and Economics. https://doi.org/10.1002/ijfe.2512
Ulum, I. (2008). Intellectual Capital Performance Sektor Perbankan di Indonesia. Jurnal Akuntansi Dan Keuangan , 10.
Ulum, I., Ghozali, I., & Purwanto, A. (2014). Intellectual Capital Performance of Indonesian Banking Sector: A Modified VAIC (M-VAIC) Perspective. Asian Journal of Finance & Accounting, 6(2), 103. https://doi.org/10.5296/ajfa.v6i2.5246
Ur Rehman, A., Aslam, E., & Iqbal, A. (2022). Intellectual capital efficiency and bank performance: Evidence from Islamic banks. Borsa Istanbul Review, 22(1), 113�121. https://doi.org/10.1016/j.bir.2021.02.004
Vo, D. H., & Tran, N. P. (2021). Intellectual capital and bank performance in Vietnam. Managerial Finance, 47(8), 1094�1106. https://doi.org/10.1108/MF-03-2020-0143
Yuan, Y., Tian, G., Lu, L. Y., & Yu, Y. (2019). CEO Ability and Corporate Social Responsibility. Journal of Business Ethics, 157(2), 391�411. https://doi.org/10.1007/s10551-017-3622-3
Zhang, Y., Hou, Z., Yang, F., Yang, M. M., & Wang, Z. (2021). Discovering the evolution of resource-based theory: Science mapping based on bibliometric analysis. Journal of Business Research, 137, 500�516. https://doi.org/10.1016/j.jbusres.2021.08.055
|
Copyright holder: Samantha Agnesia Lidya Br. Gultom, Arief Wibisono Lubis (2023) |
|
First publication right: Syntax Literate: Jurnal Ilmiah Indonesia |
|
This article is licensed under:
|
_files/image001.jpg){kind=small}