1. finance
2. bank
3. bank account

Applied mathematics in Engineering, Management and Technology 2 (3) 2014:145-150
www.amiemt-journal.com
Studying the effective factors in performance of intellectual capital
in banks accepted in Tehran stock exchange
Hashem Eftekhare, *Nader Asgaryan, Seyyed Asgar Seyyedy
Department of Accounting, kharvana Branch, Islamic Azad University, kharvana, Iran
Tabriz Business Training Center
*corresponding author
Abstract
The purpose of this research is to examine some of the financial ratios on Value
added intellectual capital in the banking industry.for data analysis e-view software
is used. We use all banks accepted in Tehran stock exchange for statistical society
in period of 2005-2009.the used statistical model is multiple regression model (pls).
In this study, the variable delay value of intellectual capital that is used to express
delayed effects. We also used delay variable of the intellectual capital added value
to explain its delay effects. The results of the hypothesis test reveal that there is not
important and meaning full relationship between intellectual capital performance
and relative return of the bank but there is a negative and reveres relationship
between intellectual capital performance and entering barriers in banking and
employees costs ratios. Between intellectual capital performance and risk and
profitability of the bank.
Key words: intellectual capital, efficiency, risk, value added intellectual capital profitability.
1. Introduction
During two recent decades, societies have been moving forwards in order to form a knowledge-oriented,
changeable, and full of tensions society in which investment in human resources, information technology, and
research and development have been considerably evident. Regarding this fact, knowledge management and
intellectual capital strategies have become very critical for organizations in today's world. In organizations,
intellectual capital means the capital resulted from mind and knowledge forms the main part of assets. In fact
intangible assets and intellectual capital are considered as the main and not only important issue in
organizations and in governments, scientific centers, investors and other beneficiaries.
In an economic era based on knowledge and following great economic and social changes, the success of
organizations is not confined to financial and material resources but it is bound to access intangible capitals
through which they can reach a consistent superiority. In the new corporate governance setting, those
organizations will make progress that consider themselves as learner organizations whose goal is permanent
improvement of intellectual capital because an organization that is not able to increase its intellectual capital
will not be able to survive. But on the contrary to the increasing importance of intellectual capital as a critical
resource for competitive superiority of organizations, there has been a little understanding of it happened.
Meanwhile, intellectual capital management allows managers in organizations to create, grow, control, and
preserve a strong resource and a competitive advantage which can not be achieved by rivals very easily
(Mirkamali, 2008).
2.Research framework
In today's knowledge-oriented economic setting, intellectual capitals have gained more value and importance
for the organizations and entities compared to physical capitals. In other words, intellectual capitals are
considered as real capitals and are among the most strategic capitals of organizations in current era especially
for profit companies and knowledge–oriented organizations. Thus, today management of intellectual capitals in
organizations has changed into one of the most important tasks of organizations. However, this task is difficult
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due to the complexities in the definition, measurement, and strategic assessment of intellectual capital.
Management of intellectual capital enables organizations to develop and promote organizational merits. Since
organizational merits are achieved based on intellectual capitals, any type of improvement in merits depends on
effective management on intellectual capital and the result of it would be improving business performances and
creating values.
In the present research we are going to find an answer to the following fundamental question: "Do factors such
as: bank profitability, obstacles of entering into banking industry, bank efficiency, bank risk, and investment
return in intellectual capital affect the performance of intellectual capital of banking industry in Tehran Stock
Exchange?"
3.Prior studies
Hemmati & Mehrabi (2010) studied the relationship between intellectual capital and financial return of firms
accepted in Tehran Stock Exchange. Results of their research showed that:
1- there is a positive correlation between intellectual capital and financial performance of the company and a
firm's future performance. 2- Intellectual capital has different amount of roles in a firm's future performance in
different industries. And 3- There is not a relationship between intellectual capital growth rate and a firm's
future performance.
Hemmati & Mozaffari (2010) studied about the relationship between intellectual capital and market value and
financial performance of non-financial companies accepted in Tehran Stock Exchange.
In this research they first used intellectual capital value added coefficient method (Palic's model) of
performance of intellectual capital in sample firms to measure and then analyzed the relationship between
intellectual capital and market value and financial performance of intended firms. Results of their research were
as follows:
1. There is a meaningful relationship between intellectual capital and market value, current financial
performance, and future financial performance of firms being tested.
2. There is a meaningful relationship between intellectual capital growth rate and financial performance of
firms being tested.
3. There is a meaningful difference between information content of intellectual capital elements in
predicting financial performance of firms being tested.
Kiong Ting & Leon (2009) studied intellectual capital performance and its relationship with financial
performance of financial institutions in an investigation about intellectual capital performance in financial
institutions in Malaysia. The main results they got were as follows:
1. There is a positive relationship between intellectual capital value added and owners' equity in financial
sector in Malaysia.
2. The amount of relationship between three elements of intellectual capital value added and profitability
of financial sector in Malaysia was about %71.6.
Joshi & Cahill & Jasvinder (2010) assessed the performance of intellectual capital in banking in Australia and
investigated about the relationship between different elements of intellectual capital performance. The most
important results they got were as follows:
1. There is a meaningful relationship between human force costs and human force value added and
intellectual capital value added.
2. Efficiency of human capital is relatively higher than structural capital efficiency.
3. Bank size regarding total assets, number of staffs, and owners' equity do not affect intellectual capital
performance or they have a weak effect on it.
Maditinos –Chatzoudes, Tsairidis, and Theriou (2011) studied about the effect of intellectual capital on market
value and financial performance of companies in a research paper. The most important research findings were
as follows:
1. There is a statistically meaningful relationship between human capital return and financial performance
of companies.
2. There is a meaningful relationship between intellectual capital of companies and their market values.
4. Research Hypothesis
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4.1. First hypothesis: there is a positive relationship between efficiency (relative return) of bank and
intellectual capital performance in banks enlisted in Tehran Stock Exchange.
4.2. Second hypothesis: there is a negative relationship between obstacles of entering banking industry and
intellectual capital performance in banks enlisted in Tehran Stock Exchange.
4.3. Third hypothesis: there is a positive relationship between staffs' costs and intellectual capital performance
in banks enlisted in Tehran Stock Exchange.
4.4. Fourth hypothesis: there is a positive relationship between bank's profitability and capital performance in
banks enlisted in Tehran Stock Exchange.
4.5. Fifth hypothesis: there is a positive relationship between bank risk and human capital performance in
banks enlisted in Tehran Stock Exchange.
5.Sample selection
The statistical population for the present research entails all firms enlisted in Tehran Stock Exchange that have
been active in a period of 5 years during the time period between 2005 and 2009. Since the society being
investigated in this research was a limited one, we decided to investigate about the whole population and avoid
sampling. Banks that were chosen to be investigated were 7 as follows:
1-Parsian bank, 2- Eghtesad-e-Novin bank, 3- Sina bank, 4- Tejarat bank, 5- Saderat-e-Iran bank, 6- Mellat
bank, and 7- Karafarin bank
6.Research model
In this research we have used correlation analysis method to test hypotheses and we used the following multiple
regression model to study the effect of correlation between dependent variable and independent variables.
VAICit   0  1hass it   2 FASSit   3 SREVit
  4 ROEit  5 ITAGAssit  U it
VAICit = value added of (performance) intellectual capital in bank i during year t
HASSit = efficiency of bank i during year t
FASSit = obstacles to enter in bank i during year t
SREVit = return of investment in intellectual capital in bank i during year t
ROEit = profitability of bank i during year t
ITAGASSit = bank i risk during year t based on intangible assets to total assets
Where VAICit and VAHC7 and VACA6 are dependent variables and the model's independent variables were
8HASSit, 9 FASSit, 10 SREVit, 11 ROEit, 12 ITAGASSit.
7.Research hypothesis test
7.1.Testing normality of the dependent variable
In statistical methods the normality of data especially the dependent one has a certain importance. To test the
normality of data we have used Kolomogorov-Smirnov's test. This test is a simple non-parametric method to
determine convergence of experimental information and selected statistical distributions.
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variable
model
n
AVG
Normal
parameters
STD
Absolute
Maximum
positive
differences
negative
k-s
Meaningful level
Table 1: Kolomogorov-Smirnov's test
Log of the
bank
value of
bank
bank
entering
intellectual
profitability
risk
obstacles
capital
35
35
35
35
8.34
0.44
0.32
0.33
1.89
0.27
0.23
0.21
0.09
0.11
0.19
0.23
0.33
0.27
0.23
bank
investment on
intellectual
capital
35
6.99
6.20
0.20
bank
efficiency
(return)
35
0.07
0.11
0.19
0.23
0.23
0.20
-0.09
-0.10
-0.14
-0.14
-0.17
-0.13
0.51
0.95
0.63
0.81
1.11
0.17
1.35
0.05
1.35
0.05
1.17
0.13
Regarding the results of KS test every variable which has had a meaningfulness level of higher than %5 is
accepted as a normal variable. But if it is less than %5, H0, or normality of variable distribution claim is not
accepted. Now regarding the explanations above and test results we conclude that intellectual capital variable
has had a normal distribution due to its meaningfulness level being higher than %5.
7.2.Regression model: Pooled least squares method (PLS)
To study the simultaneous effect of all financial variables mentioned in 5 hypotheses above we used a multiple
regression pattern using pooled least squares method. Regarding table 5, meaningfulness level of variables such
as bank risk, bank efficiency and the amount of latitude from base was in %95 assurance level and they were
meaningful regarding t statistic. Regarding the amount of beta coefficient of variables of bank risk, bank
efficiency coefficient approved the direction of the effect. It means that there is a positive and direct
relationship between bank risk and bank efficiency and intellectual capital value added. Other independent
variables do not have meaningful relationships with dependent variable.
Table 2: Coefficients of pooled least squares method regression model (PLS)
Beta
Standard
Meaningfulness
Model elements
t statistic
coefficients
error
level (Sig.)
fixed amount (latitude from
9.24
0.33
28.10
0.00
base)
bank i profitability in year t
-0.52
1.23
-0.42
0.67
bank i entering obstacles in year
-1.49
1.43
-1.04
0.31
t
bank i risk in year t
3.23
1.15
2.80
0.01
bank i efficiency (return) in year
1.01
0.29
-3.52
0.00
t
bank i investment on intellectual
-0.10
0.09
-1.19
0.25
capital in year t
AR(1)
0.16
0.08
2.09
0.05
Results in table 3 showed that about 0.28 of changes related to intellectual capital value added of 4 financial
variables mentioned above could be explained. Also Durbin-Watson statistic approved lack of correlation
between independent variables' variances. Table 4 approved the static nature of research variables if absolute
amount of Hardy statistic calculated is less than critical amounts (which is usually studied in %5 levels). The
dynamic nature of hypothesis is approved and as it can be observed the amounts of statistic calculated are less
than %5 in all variables' levels. Thus, data are static. F Limer test is used to recognize pool and panel methods.
In this test null hypothesis expresses that the use of pooled data by the model and its counter presupposition
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represent using tableau data. Since probability level is less than %10, the test shows that data are in pooled
pattern.
Table 3: Total model meaningfulness test
D-W F- limer test
Sig
1.35
0.00 1.35
0.0937
F
R2square
R2
0.17
0.28
8.Haussmann's test to recognize using fixed or random effects
8.1.For pooled data:
in this test null hypothesis claims that the model uses fixed effects method and the opposing presupposition
shows the utilization of random effects model. According to findings, in this test the probability is less than 0.1.
Thus, the test shows that we should use fixed effect method.
8.2.Regression model of pooled least squares method using fixed effects:
To study the simultaneous effect of all financial variables mentioned in 5 hypotheses above, we have used a
regression model of pooled least squares method using fixed effects. Regarding table 4, meaningfulness level of
variables such as bank risk, bank profitability, entrance obstacles, investment in human capital return, and the
amount of latitude from base were in an assurance level of %95 and regarding the amount of t statistic it was
meaningful. Regarding the amount of beta coefficient of variables of bank risk, bank profitability approved the
direction of the effect. It means that there is a positive and direct relationship between bank risk and bank
profitability and intellectual capital performance. Also the effect of beta coefficients of investment return of
human capital and obstacles to enter in banking industry do not approve the direction of effect. This means that
the relationship between investments return on intellectual capital and obstacles to enter in banking industry and
intellectual capital performance is negative (reversed). Finally there has not been any relationship observed
between bank efficiency and intellectual capital performance.
Table 4: Coefficients of pooled least squares method regression model using fixed effects method
Beta
Standard
t
Meaningfulness level
Model elements
coefficients
error
statistic
(Sig.)
fixed amount (latitude from base)
9.15
0.32
28.76
0.00
bank i profitability in year t
1.20
0.38
3.17
0.006
bank i entering obstacles in year t
-2.29
0.44
-5.16
0.0001
bank i risk in year t
2.13
0.77
2.78
0.01
bank i efficiency (return) in year t
-1.77
1.22
-1.45
0.17
bank i investment on intellectual
-0.10
0.03
-1.43
0.17
capital in year t
AR(1)
-0.33
0.23
-1.43
0.17
Results in table 5 showed that about 0.30 of changes related to intellectual capital value added of 5 financial
variables mentioned above could be explained. Also Durbin-Watson statistic approved lack of correlation
between independent variables' variances. Table 8 approved the static nature of research variables if absolute
amount of Hardy statistic calculated is less than critical amounts (which is usually studied in %5 levels). The
dynamic nature of hypothesis is approved and as it can be observed the amounts of statistic calculated are less
than %5 in all variables' levels. Thus, data are static.
F Limer test is used to recognize pool and panel methods. Data were entered in the form of pooled data. In this
test null hypothesis expresses the use of pooled data by the model and its counter presupposition represent using
tableau data (panel data). Since probability level is less than %10, the test shows that data are in pooled pattern.
In Haussmann's test null hypothesis expresses the use of fixed effects method by the model and its counter
presupposition represent using random effects method. Probability is less than 0.1. Thus, the test showed that
fixed effects method was better.
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Table 5: Total model meaningfulness test
D-W F- limer test
Sig
2.21
0.00 1.99
0.0937
F
R2square
R2
0.28
0.30
Regression results showed that obstacles to enter in banking industry and staffs' costs (return of investment in
intellectual capital) both have a negative effect on intellectual capital performance and this showed that the
required investment has not been done through encouraging staffs to carry out their duties or to create
incentives for innovation in banks under investigations in order to improve human capital performance that is a
part of intellectual capital. Also managers in banks studies did not pay attention to human capital and this
outlook of managers in banks may potentially reflect bad indexes. Additionally, profitability and risk of bank
were statistically meaningful. On the other hand, bank profitability and bank risk had positive effects on
intellectual capital performance. This may potentially reflect a good index regarding bank managers' outlooks.
In Iran there has not been any researches carried out in this regard to compare our research results with but out
of Iran the results of this research do not accord with those results in Elbanini's research and this results from
lack of paying attention to intellectual capital in Iranian banks. Thus, banks in Iran should pay more attention to
intellectual capital to promote efficiency and profitability of the organization through promoting human capital
(staffs) performance to improve intellectual capital performance.
References
Hemmati, Hassan; Mozaffari-e-Shams, Maryam (2010). Studying the relationship between intellectual capital and market
value and financial performance of non-financial companies. Quarterly Journal of Accounting and Finance, No. 7, 23-48.
Hemmati, Hassan; Mehrabi, Ali (2010). Studying the relationship between intellectual capital and financial return.
Quarterly Journal of Accounting and Finance, No. 4, 24-51.
Irene Wei Kiong Ting, Hooi Hooi Lean, (2009) "Intellectual capital performance of financial institutions in Malaysia",
Journal of Intellectual Capital, Vol. 10 Iss: 4, pp.588 – 599
Maditinos,D, Chatzoudes,D, Tsairidis,Ch, Theriou,T,(2011)” The impact of intellectual capital on firms’ market value and
financial performance”, Journal of Intellectual Capital Vol. 12 No. 1, 011pp. 132-151
Mirkamali, S.; Zohor-e-Parvandeh, V. (2008). Intellectual capital management as a necessity for organizations in
knowledge-based era. Journal of management message, No. 28, 81-105.
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