Pixel

Impact of Intellectual Capital on Financial Performance of Banks in Tanzania

0

Citation Download PDF

Journal of International Business Research and Marketing
Volume 1, Issue 1, November 2015, Pages 16-23


Impact of Intellectual Capital on Financial Performance of Banks in Tanzania

DOI: 10.18775/jibrm.1849-8558.2015.11.3002
URL: http://dx.doi.org/10.18775/jibrm.1849-8558.2015.11.3002

Janeth N. Isanzu

School of Management, Wuhan University of Technology, Wuhan, P.R.China, 430070

Abstract: Since the financial sector reforms took place in the last two decades, Banks in Tanzania have continued to play the major role in reshaping the economy of the nation. With the emergence of knowledge based economy many firm have changed their way of doing business instead of relying more on physical capital they have shifted to intellectual capital. This is no exception for the banks operating in developing counties Tanzania included. Many studies have been done in the area of intellectual capital and its contribution to the value of the firm. This study sets out to extend the evidence by investigating the intellectual capital of banks operating in Tanzania for the period of four years from 2010 to 2013. Annual reports, especially the profit and loss accounts and balance sheets of the selected banks have been used to obtain the data. The study uses Value Added Intellectual Capital model (VAICTM) in determining intellectual capital and its three major components like Human Capital Efficiency (HCE) Structural capital efficiency (SCE) and Capital Employed Efficiency (CEE). The results revealed that Intellectual capital has a positive relationship with financial performance of banks operating in Tanzania and also when the VAICTM was divided into its three components it was discovered that the financial performance is positively related to Human capital efficiency and Capital employed efficiency but is negatively related to Structural capital efficiency.

Keywords: Intellectual Capital, Banks, Value Added Intellectual Capital (VAICTM), financial performance

Impact of Intellectual Capital on Financial Performance of Banks in Tanzania

1. Introduction

The 21st century is more dominated by knowledge economy, as more and more firms are trying to finding better ways to use their resources efficiently in order to sustain in the dynamic changing business environment, hence there is a huge move by many firms from production era to knowledge era and from production labor to knowledge worker (Lipunga, 2014). It is no secret that the firm that continues to invest in new skill and technology will continue to be successful. Thus being said intangible assets especially Knowledge are gaining prominence than ever before as a matter of survival and of achieving competitive advantage for the firm to compete strategically (Latif et al., 2012).In today’s fast moving economy with the rapid growth of knowledge and technology innovation the growth of organization has changed in order to cope with the changing environment. With big changes in the global economy intellectual capital has become the main ingredient and vital for the organization to sustain the competitive world in which they operate and to create more values as insisted by (Bontis, 2001) intellectual capital has become the critical driver for sustainability.

While the grounded framework of intellectual capital have been put in place and Intellectual capital being studied in many countries to give their firms competitive advantage over rivals still there is a wide gap in understanding if the firms investing and use intellectual capital they view it as a critical asset. Therefore there is still a need to measure intellectual capital of the firm and its impact on financial performance, so the firm can become more aware. Furthermore, despite the popularity of intellectual capital among the research community in the developed world, there have been very few studies that have used emerging developing worlds especially in Sub Saharan Africa as a case for evaluating the implications of intellectual capital for specific industries (Kamath, 2007). This is a gap that needs filling, because with the globalization, all organizations [both in developed and developing economies]are increasingly confronted with worldwide competition (Muhammad and Ismail, 2009), which is making intellectual capital equally important to all of them to survive. Thus being mentioned there is equally a need to promote studies in developing countries.

This study uses the bank sector to find the impact of intellectual capital and financial performance, since the bank sector is one of the high knowledge intensive sectors and therefore it provide a rich environment for the research and the availability of the reliable data from the audited annual reports of banks. The study uses VAICTM model to analyze if the intellectual capital has impact on financial performance of Tanzanian banks.

2. Literature review

2.1 Intellectual capital definition

Intellectual capital is the critical value driver of the firm to succeed in the fierce competitive world; it still has many issues remain to be cleared regarding its definition. Up to now the definition of intellectual capital is not uniform among different sectors. Itami (1987) was the early contributor of intellectual capital definition sees intellectual capitals as intangible asset that comprises of technology, customer loyalty, brand name loyalty and goodwill etc. Stewart (1997), also contributed to definition of intellectual capital by defining as a concept that involves human capital, structural capital and customer capital. He defines human capital as the sum of innovations, employees’ mindsets, seniority, turnover rate, experiences, and learning capacities; structural capital as the existing knowledge collected using a highly efficient method and tested, organized, integrated, with the irrelevant part sifted out before distribution; customer capital as the relationships a given organization forges with all parties it deals with, including customer satisfaction, retention rate, and loyalty. At the same time Edvinsson and Malone (1997) defined intellectual capital as the sum of human, structural, and customer capitals.

On the other study Sveiby (1998) noted, components of intellectual capital are individual competence, internal structure and external structure, with the individual competence being an employee’s ability to take actions under various situations, which involves explicit knowledge, skills, experiences, value-related judgments, and social network; internal structure being the sum of patents possessed, concepts, patterns, computer/management systems; external structure being the relations with customers and suppliers, which involves the brand, reputation and trademarks.

Johnson (1999) tries to define as intellect, or wisdom, as the combination of human capital, structural capital and relationship capital, where human capital means the idea capital (i.e., the human resources for knowledge-based task sand employees’ talent/attitude) combined with leadership capital (i.e., the qualities befitting an expert/manager); structural capital means the innovation capital (i.e., patents, trademarks, copyrights and knowledge database) combined with process capital (i.e., work procedures and trade secrets); relationship capital means the sum of relationships with customers, suppliers and members of network communities.

In a simplified definition, Edvinsson (2003) expressed intellectual capital as what would become what supports any company in the future as well as an indicator of whether that company will be operated effectively. It is impossible for a company to gain momentum for reforms unless it invests in intangible assets (Tsen and Hu, 2010). Meanwhile Cabrita and Vaz (2006) simply stated that intellectual capital is a matter of creating and supporting connectivity between all sets of expertise, experience and competences inside and outside the organization.

The latest definition of intellectual capital Mondal and Ghosh (2012) described intellectual capital as “intangible assets or intangible business factors of the company, which have a significant impact on its performance and overall business success, although they are not explicitly listed in the balance sheet (if so, then under the term goodwill).”

There are many researchers who divided the intellectual capital into three main components of human capital, structural capital and relation capital Edvinsson and Malone (1997); human capital is the personal competencies, knowledge, technologies, and experiences of the entire staff and management of a company, including the creativity and innovation capacities of the corporate organization. The structural capital is a supportive framework that gives physical form and power to human capital, as well as an organized capacity that includes the tangible system intended for communications or the storage of intellectual materials. Customer capital, they refer to the sum of customer satisfaction, durability, price sensitivity, and the financial soundness of long-term clients.

2.2 Intellectual capital and firm performance

There have been prior studies around th world which show the intellectual; capita; and firm performance. Among these studies Goh (2005) investigated the intellectual capital of Malaysian commercial banks based on VAIC™ model and found that there is significant relationship between VAIC™ performance and Human Capital Efficiency (HCE) and also the study shows that HCE has relatively larger contribution in measuring VAIC™ performance as compare to SCE and CEE. Same findings are revealed by Joshi et al (2010) also in the same manner the empirical results examined while exploring the Intellectual Capital and banks performance of Australian Owned Banks for the period of 2005-2007 through VAIC™ model. They showed same findings that Human Capital Efficiency (HCE) is positive and significant VAIC to be a key determinant to enhance the IC performance of Australian banks which means investment on Human Cost (HC) is more returnable as compare to other determinant of VAIC™.

Studying the relationship of intellectual capital to firm performance, in recently study Joshi et al., (2013) investigated relationship between intellectual capital and their components and financial performance in Australia context for the time of 2006-2008. The results show human capital efficiency, capital utilized efficiency and structural efficiency was all important but they differ in utilization. It was found that intellectual capital is critical in connection with human efficiency and worth expansion of Australian banks. Human capital efficiency is higher than capital utilized efficiency and structural efficiency on Australian claimed banks.

In other study Mention and Bontis (2013) performed a study using data from 200 banks from Belgium and Luxembourg the empirical results found that human capital was both a direct and an indirect contributor to business performance. Structural and relational capitals were found to be positively related to business performance; however results suggested statistically insignificant relationship. Consistent results were found by Mohiuddin et al. (2006) in the study of 17 sampled commercial banks operating in Bangladesh for the period from 2002 to 2004. In another study Mavridis (2004) found that Japanese banks with the greatest performance were those who were most efficient in the use of their Human capital, whereas efficiency in physical assets utilization was less important. Yolama and Coskun 2007 conducted a study on the effect of intellectual capital profitability of Turkish banks and found out the VAICTM model can be used as a benchmark for level of intellectual efficiency.

In other hand Jalilian, et.al (2013) examined a case study to investigate the impact of intellectual capital on the financial and non-financial performance of West Cement Company of Kermanshah, Iran. The variable integrated were intellectual capital as measured through human capital, structural capital and relational capital, organizational leavening capability and firm performance; which were measured through financial and non-financial performance. The study found an inter-relation between all three components of intellectual capital. And they also had a direct correlation with organizational leaning capability, financial and non-financial performance.

In the study involving different financial sectors Muhammad and Ismail (2009) examined the impact of intellectual capital efficiency on the performance of financial sector firm of Malaysia( ie banking sector insurance sector brokerage firms). By using VAICTM to measure intellectual capital efficiency and ROA along with profitability to measure performance, the study found a strong and positive impact of intellectual capital efficiency on the financial performance of the financial sector of Malaysia. Moreover, it was also found that within financial sector banking sector of Malaysia relies more heavily on the intellectual capital efficiency, which is followed by insurance sector and brokerage firms in a subsequent manner.

Zehri, et.al (2012) investigated a study in Tunisia to measure the intellectual capital and financial performance. The study used VAIC model to measure intellectual capital efficiency, while performance of the organization was measure in three ways financial performance (return on assets), economic performance (operating margin) and market performance (Market to book ratio). On the whole, the results of the study confirm presence of a direct impact on financial and economic performance of the company. The direct relationship between intellectual capital and market performance however, was not confirmed.

Ahangar (2011) examined intellectual capital and firm performance in Iranian corporate sector. The study used VAICTM model to measure intellectual capital efficiency and used profitability, sales growth and employee productivity as performance proxies. The study indicated that human capital is most important component of intellectual capital and all three dimensions as proposed by VAICTM are significant explanatory variables for profitability as measured by return in asset.

Kamal et al. (2012) on another hand using 18 commercial banks in Malaysia investigated the relationship between the level of intellectual capital efficiency in terms of human capital, capital employed and structural capital with the commercial banks performance from the traditional accounting based perspective that comprised return on assets and return on equity. The overall results revealed the relationship between intellectual capitals and performance of banks. Additionally, the results revealed significance impact of intellectual capital variables namely capital employed efficiency, human capital efficiency towards bank performance. Thus the study concluded that intellectual capital do matters and should be linked to firm productivity.

Ting and Lean (2009) further more in Malaysia conducted the study on financial sector to examine the intellectual capital performance and its relationship with financial performance for the period 1999 to 2007. They also used VAIC TM, the results insist that Intellectual capital and return on assets are positively related. Further to that the results also revealed that the three components of VAIC TM were associated with profitability with the explanatory power of 71.6 per cent.

Tan et al. (2007) conducted a similar kind of study to examine the relationship between the intellectual capital of firms and their financial performance. Using data from 150 publicly listed companies on the Singapore Exchange They used VAIC TM methodology The results showed that intellectual capital and firm performance were positively related, in particular intellectual capital was found to be correlated to future company performance and the rate of growth of a company’s intellectual capital was positively related to the company’s performance. However it was found out the contribution of intellectual capital to company performance differs by industry.

Chan (2009) using a sample of all companies listed on Hang Seng stock exchange for the period 2001 to 2005, examined the relationship between the efficiency of the Intellectual Capital of these companies and its components (human and structural) with measures of firm performance: market valuation, return on assets, and return on equity and productivity measurement. The results showed that only structural capital has a significant and positive relationship with profitability measures (ROA and ROE).

Phusavat et al., (2011) targeted manufacturing firms in Thailand conducted a study on the effects of intellectual capital, and integrated its key components (e.g. human capital, structural capital, and innovation capital) and performance using VAICTM. The study reveals that intellectual capital, positively and significantly affects a manufacturing firm’s performance, having impacts on the all four performance indicators under study, i.e. return on equity, return on assets, revenue growth, and employee productivity.

On another perspective, some used to measure the interrelationship between intellectual capital elements. Generally empirical evidence indicates existence of interrelationships. For instance, Maditinos et al. (2009) using data from Athens Stock Exchange (ASE) and the companies operating in service and non-service industries conducted a study to investigate the four components of intellectual capital namely human capital, customer capital, structural capital and innovation capital and their relationship with business performance The study found out structural capital had a positive relationship to business performance in both industries, however relatively stronger in non-service industries. Furthermore was found that human capital was important and positively associated to customer capital; customer capital had an influence on structural capital and innovation capital had an important and positive relationship to structural capital.

In addition to the interrelations, literature documents the relative dominance of human capital in influencing other intellectual capital components and the overall value added intellectual coefficient. For instance, Wang and Chang (2005) found that even though human capital did not have a direct impact on business performance, it had a direct impact on the other intellectual capital elements, which in turn affected performance. Furthermore, Joshi et al., (2010) revealed that VAICTM has a significant relation with human costs and that all Australian owned banks had relatively higher human capital efficiency than capital employed efficiency and structural capital efficiency.

The finding of these studies yield mixed results for example firer and Williams(2003) studied the intellectual capital of south Africans the results only supported intellectual capital and capital employed furthermore he examined the relationship between IC and traditional measures of firm performance (ROA, ROE) and failed to find any relationship, The opposite research result also, studied by Iswati (2007) show that no influence between intellectual to bank’s performance in Jakarta Stock Exchange.

The studies highlighted above are mostly related to the developing economies which show still there is a need to study intellectual capital and financial performance of banks in other countries especially in African local context. The studies show the concepts using various definitions of intellectual capital, methods and proxies of performance. Most of the studies indicated towards a direct impact of the various dimensions of intellectual capital on internal as well as market performance of the firms.

2.3 Proposed Model and Hypothesis

The model for the study can be presented based on the review of literature on intellectual capital and performance of banks the framework is shown below

1-2

Figure 1: Proposed model

This study proposed the following hypothesis

H1: There is a significant positive relationship between the VAIC and financial performance of banks

H2: There is a significant positive relationship between the HCE and financial performance of banks

H3: There is significant positive relationship between the SCE and financial performance of banks

H4: There is significant positive relationship between the CEE and financial performance of banks

3. Research methodology

3.1 Sample and data collection

The sample of the present study consists of 31 banks and is based on secondary data collected from annual report of the mentioned banks .Banks were selected on the basis of availability of information necessary for conducting the study and the readiness of Annual Reports for the financial year 2010-2013. Hence the applied sampling procedure could be defined as convenience sampling. Data was collected from the annual reports of the banks consistent with other related studies (Goh, 2005;Mavridis, 2005; Tan et al., 2007;Joshi et al., 2010; Joshi et al., 2013;Lipunga,2014).

3.2. Variables and empirical models

Firm Performance = f (Intellectual Capital)

Or

FP it = β 0 + β 1 IC it + µ

Where,

FP = Firm performance

IC = Intellectual Capital

The regression model used

ROA= α + β1 VAIC+ ε                                                (1)

ROA= α+β1HCE+ β2SCE+ β3CEE+ ε                     (2)

VAIC TM Method

Although the measurement of intellectual capital is still a debatable issue, numerous methods have been developed to measure it. In this study, the Value Added Intellectual Capital (VAICTM) method, developed by Public (1997, 1998, 2001, 2002a, 2002b, 2004), was used.

VAICTM method is formulated as follows:

Equation (1) formalizes the VAICTM

VAIC=HCE+SCE+CEE

where:

VAICTM = value added intellectual coefficient for bank i,

CEE = capital employed efficiency coefficient for bank i,

HCE = human capital efficiency coefficient for bank i,

SCE = structural capital efficiency for company i.

The first step is calculating CEE, HCE and SCE. These three components of VAIC are calculated as follows:

HCE = VA/ HC

SCE = SC/ VA

CEE = VA/ CE

Where

VA = Value added

HC = Human capital

SC = Structural capital

CE = Capital employed

The above variables of the model are calculated by following procedure:

VA=OUTPUT-INPUT

Output it is the total income generated by the firm from all products and services sold during the period t, and Input it represents all the expenses incurred by the firm during the period t except cost of labour, tax, interest, dividends and depreciation.

Although there are many ways to measure the performance of intellectual capital such as market value asset turnover employee productivity and Return on equity but for this study the ROA is picked as compared to ROE the ROA variable does take financial risk of banks into consideration.

Return on Asset (ROA)

Return on Asset is a profitability ratio that measures the firm’s ability to generate profit using its asset. The greater the ROA, a firm is more efficiency in using its assets. This is one of the commonly used ratios to measure firm’s financial performance, which is calculated by ROA

Return on Asset= Net Income /Total Asset

4. Findings and Discussion

The data collected has been analyzed using different statistical tests. First of all descriptive statistics relating to the variables of the study are presented. After that correlation analysis if provided and in the end regression analysis is provided in order to establish relationships between the variables.

Descriptive statistics in the study are used to compare the means and standard deviation of the variables which are being considered in the study . The variables considered in the study are return on assets (ROA), and value added intellectual capital coefficient (VAIC) and its components

Table 1: Descriptive Statistics for studies variables

N Minimum Maximum Mean Std. Deviation
ROA 117 -.25 .23 .0116 .04093
HCE 117 -1.6778 13.6373 2.058312 1.7019372
CEE 117 -.1419 .1058 .043591 .0301394
SCE 117 -1.5669 11.8036 .636440 1.5866086
VAIC 117 -1.1704 14.6063 2.738343 2.2109172

Table 1 above provides descriptive statistics of the variables considered in the study of banks operating in Tanzania. The minimum of the first dependent variable i.e. ROA is -.25 along with a maximum of .23. The mean and standard deviations of the variable are .0116 and .04093 respectively. The minimum and maximum for HCE, on the other hand are -1.6778 and 13.6373 respectively and mean for the variable is 2 .0583 along with a standard deviation 1.7019.The next variable of the study is CEE which has minimum of -.1419 and maximum of .1058 along with a mean of .0435 and standard deviation of .03013 SCE has a minimum of -1.5669 and a maximum of 11.80. The mean of the variable on the other hand is .6364 and a standard deviation of 1.5866 VIAC is the last variable has a minimum of -1.1704 and maximum of 14.6063 The mean average for this variable is 2.7383 and with a standard deviation of 2.21.To conclude it shows HCE has the highest mean among all the components of VAICTM. The mean of SCE and the one for CEE respectively, the CEE has the lowest mean among all the variables. 

Table 2: Correlations Matrix of banks

ROA HCE CEE SCE VAIC
ROA Pearson Correlation 1 .477** .685** -.228* .213*
Sig. (2-tailed) .000 .000 .014 .021
N 117 117 117 117 117
HCE Pearson Correlation .477** 1 .295** -.098 .703**
Sig. (2-tailed) .000 .001 .292 .000
N 117 117 117 117 117
CEE Pearson Correlation .685** .295** 1 -.271** .046
Sig. (2-tailed) .000 .001 .003 .622
N 117 117 117 117 117
SCE Pearson Correlation -.228* -.098 -.271** 1 .638**
Sig. (2-tailed) .014 .292 .003 .000
N 117 117 117 117 117
VAIC Pearson Correlation .213* .703** .046 .638** 1
Sig. (2-tailed) .021 .000 .622 .000
N 117 117 117 117 117
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).

 

The table 2 above, shows that ROA and HCE have moderate positive relation .So the ROA and HCE have correlation of 0.477 and are significant to each other. ROA and CEE also keep competitive strong correlation of 0.685 and are significant for both of them. The correlation between Structural Capital Efficiency (SCE) and ROA is -0.228 which is weak and negative. These two variables are also significant in relation to them. The correlation between ROA and VAIC is also positive and significant but weak at 0.213.This is lower compared to Human capital efficiency and capital employed efficiency.

The result describes that the CEE and HCE values are more significant to ROA than Structural Capital Employed Efficiency (SCE) and on the other hand SCE and HCE are more significant to VAICTM of Banks in operating in Tanzania. Regression analysis in the study is the final step of analysis which provides the estimation of the variables by considering performance related variables dependent variables and VAIC as independent variable.

Table 3: Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate
1 .213a .046 .037 .04016
a. Predictors: (Constant), VAIC

Table 3 above provides model summary for the regression estimates relating to the model 1 which sought to establish the impact of VAIC on return on assets (ROA) for banks operating in Tanzania The R square of the model is .213 which is quite low as it associates only 21% explanation of variation in ROA with VAIC. The adjusted R square of the model on the other hand is 4.6%. along with a standard error of .0401.This show the model has no good explanatory power.

Table 4 provides the ANOVA results of the model 1 which considers ROA as dependent variable and VAIC as independent variable. The F statistics of the model is 5.484 which is quite low and indicates that model is not a good fit.

Table 4:ANOVAa
 
Model Sum of Squares df Mean Square F Sig.
1 Regression .009 1 .009 5.484 .021b
Residual .185 115 .002
Total .194 116
a. Dependent Variable: ROA
b. Predictors: (Constant), VAIC

Table 5 above provides the regression coefficient of the regression model 1 which assumes ROA dependent variable and VAIC as independent variable. The beta coefficient of VAIC is found to be .004 along with a t statistics of 2.342 which confirms that VAIC has a positive and significant impact on return on assets of banks in Tanzania. That leads us to accept our first hypothesis H1 There is a significant positive relationship between the VAIC and financial performance of banks.

The results of the present study are in confirmation with the other studies by Chen et al. (2005), Tan et al. (2007), Ting and Lean (2009), Sharabati et al. (2010) in which it is clearly revealed that there was a significant positive relationship between VAIC and ROA.

Table 5: Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) .001 .006 .128 .898
VAIC .004 .002 .213 2.342 .021
a. Dependent Variable: ROA

Table 6 on provides the model summary of the model 2 which estimates the impact of VAIC components on Return on Asset. R square for the model is .744% which indicates that independent variable i.e. VAIC components ie (CEE, SCE, HCE) causes almost 74% variation in the dependent variable i.e. Return on Asset. The adjusted R square and standard error of the model are .554 and 2.7702 respectively.

Table 6:Model Summaryb
Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics
R Square Change F Change df1 df2 Sig. F Change
2 .744a .554 .542 2.7702 .554 46.746 3 113 .000
a. Predictors: (Constant), CEE, SCE, HCE

Table 7 provides the ANOVA results of the model 2. The F statistics of the model 2 is found to be 46.74 which indicate that

model is a good fit at the significance level of 5%.

Table 7: ANOVAa
 
Model Sum of Squares df Mean Square F Sig.
2 Regression .108 3 .036 46.746 .000b
Residual .087 113 .001
Total .194 116
a. Dependent Variable: ROA
b. Predictors: (Constant), SCE, HCE, CEE

The table 8 above shows Human capital and capital employed they are significant and positively with financial performance but the structural capital is not significant and is negatively influence with financial performance this may be because bank may fail to utilize full their structural capital. That leads us to accept our hypothesis H2and H4 and reject hypothesis H3

H2: There is a significant positive relationship between the HCE and financial performance of banks

H3: There is significant positive relationship between the SCE and financial performance of banks

H4: There is significant positive relationship between the CEE and financial performance of banks

This can be summarized in table below:

Table 8 :Coefficientsa
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta
1 (Constant) -.037 .005 -6.873 .000
HCE .007 .002 .300 4.567 .000
CEE .796 .092 .586 8.614 .000
SCE -.001 .002 -.039 -.598 .551
a. Dependent Variable: ROA

5. Conclusion

The present study attempted to investigate the relationship between intellectual capital (IC), and financial performance of the banks operating in Tanzania. The methodology adopted is the one of “Value Added Intellectual Coefficient” (VAICTM) and its components described into HCE SCE and CEE that has been previously utilized by similar studies (Chen et al., 2005; Firer and Williams, 2003; Williams, 2001) . Despite the fact that Intellectual Capital is increasingly recognized as an important strategic asset for sustainable competitive advantage, the results of the present study fail to support such a claim in all the when the components are tested separately. Empirical results failed to support one of the proposed, Hypothesis three. Only verifying the relationship between Human capital efficiency and capital employed efficiency. The finding shows there is still higher emphasis on physical asset than intellectual capital.

The results reveals the banks can get benefit by investing in more intellectual capital, as it shows the value added and Intellectual capital components were able to increase firm profitability. Investing in human capital is essential to achieve banks goals. The capital employed is found as the most important variable it shows the use of physical and financial assets must be effective and efficiency. The banks should put greater efforts in investing in Structural capital by being more innovative with high technology and supportive infrastructures.

References

  • Ahangar, R. G. (2011). The relationship between intellectual capital and financial performance: an empirical investigation in an Iranian company. African Journal of Business Management, 5(1), 88-95.
  • Alipour, M.(2012) The effect of intellectual capital on firm performance: an investigation of iran insurance companies, Measuring Business Excelent,16(1),53-66, CrossRef
  • Bontis, N. 2001. Assessing knowledge assets: a review of the models used to measure intellectual capital. International Journal of Management Review, 3(1), 41-60, CrossRef
  • Chan, K. (2009). Impact of Intellectual Capital on organizational performance. The Learning Organization, 16(1), 4-21, CrossRef
  • Bontis, N. (2001). Assessing knowledge assets: a review of the models used to measure intellectual capital, International Journal of Management Reviews, 3(1),41-60, CrossRef
  • Cabrita, M. and Vaz, J. 2006. Intellectual capital and value creation: Evidence from the Portuguese Banking Industry. The Electronic Journal of Knowledge Management, 4(1), 11-20.
  • Edvinsson, L. (2003), Corporate Longitude: What You Need To Know To Navigate The Knowledge Economy, Financial Times Prentice Hall, Pearson Education, Inc., Upper.
  • Edvinsson, L. & Malone, M. (1997). Intellectual Capital: Realizing Your Company’s True Value by Finding Its Hidden Brainpower. New York: HarperCollins.
  • Firer, S. & Williams, S.M. (2003). Intellectual capital and traditional measures of corporate performance. Journal of Intellectual Capital, 4 (3), 348-60, CrossRef
  • Goh, P.C. (2005). Intellectual capital performance of commercial banks in Malaysia, Journal of Intellectual Capital, 6 (3), 385-96, CrossRef
  • Itami, H. (1987). Mobilizing Invisible Assets. Boston: Harvard University Press
  • Iswati, S., and Muslich A. The Influence of Intellectual Capital to Financial Performance at Insurance Companies in Jakarta Stock Exchange (JSE). Proceedings of the 13th Asia Pacific Management Conference, Melbourne, Australia, 2007, 1393-1399.
  • Jalilian, O., Hassani, S. R., Ghanbari, M., Jalilian,H.R. &Moradi, M. (2013). The Relationship between Intellectual Capital and Financial and Non-Financial Performance in West Cement Company in Kermanshah, Journal of Basic and Applied Scientific Research,3(6), 427-432
  • Johnson, K. (1999), Making loyalty program more rewarding, Direct Mark, 61 (11), 24-27.
  • Joshi, M., Cahill, D., & Sidhu, J. (2010). Intellectual capital performance in the banking sector: An assessment of Australian owned banks. Journal of Human Resource Costing & Accounting, 14(2), 151–170, CrossRef
  • Joshi, M., Cahill, D., Sidhu, J., and Kansal, M. (2013). Intellectual capital and financial performance: an evaluation of the Australian financial sector. Journal of Intellectual capital, 14(2), 264-285, CrossRef
  • Kamal, M. H. M., Mat, R. C., Rahim, N. A., Husin, N., and Ismail, I. (2012). Intellectual capital and firm performance of commercial banks in Malaysia. Asian Economic and Financial Review, 2(4), 577–590
  • Kamath, G. B. (2007). The intellectual capital performance of Indian banking sector. Journal of Intellectual Capital, 8(1), 96–123, CrossRef
  • Latif, M., Malik, M. S., & Aslam, S. (2012). Intellectual capital efficiency and corporate performance in developing countries: A comparison between Islamic and conventional banks of Pakistan. Interdisciplinary Journal of Contemporary Research in Business, 4(1), 405–420.
  • Lipunga A. M. (2014). A Longitudinal Assessment of Intellectual Capital of Companies Listed on Malawi Stock Exchange. European Journal of Business and Management, 6(9), 27–35.
  • Lipunga A. M. (2014). A Longitudinal Assessment of Intellectual Capital of Companies Listed on Malawi Stock Exchange. European Journal of Business and Management, 6(9), 27–35.
  • Mavridis, D. G. (2004). The intellectual capital performance of the Japanese banking sector. Journal of Intellectual Capital, 5(1), 92–115, CrossRef
  • Mohiuddin, M., Najibullah, S., & Shahid, A. I. (2006). An Exploratory Study on Intellectual Capital Performance of the Commercial Banks in Bangladesh. The Cost and Management, 34(6), 40–54.
  • Mondal, A., & Ghosh, S. K. (2012). Intellectual capital and financial performance of Indian banks. Journal of Intellectual Capital, 13(4), 515–530, CrossRef
  • Muhammad, N. M. N., and Ismail, M. K. A. (2009). Intellectual Capital Efficiency and Firm’s Performance: Study on Malaysian Financial Sectors. International Journal of Economics and Finance, 1(2), 206–212, CrossRef
  • Phusavat, K., Comepa, N., Sitko-Lutek, A., & Ooi, K. (2011). Interrelationships between intellectual capital and performance: Empirical examination. Industrial Management & Data Systems, 111(6), 810–829, CrossRef
  • Pulic, A. (2004) “Intellectual capital – does it create or destroy value?”, Measuring Business Excellence,8(1)62-8, CrossRef
  • Pulic, A. (2000). VAICe – an accounting tool for IC management. . Retrieved from www. measuring-ip.at/Papers/ham99txt.html
  • Pulic, A. (1998). Measuring the performance of intellectual potential in knowledge economy www.measuring-ip.at/OPapers/Pulic/ Vaictxt/vaictxt.html
  • Riahi-Belkaoui, A. (2003). Intellectual capital and firm performance of us multinational firms, Journal of Intellectual Capital, 4 (2), 215-26, CrossRef
  • Sharabati, A.A., Jawad, S.N. and Bontis, N. (2010). Intellectual capital and business performance in the pharmaceutical sector of Jordan. Management Decision, 48(1), 105-31, CrossRef
  • Shiu, H. (2006). The application of the value added intellectual coefficient to measure corporate performance: evidence from technological firms. International Journal of Management, 23(2), 356-65.
  • Stewart, T.A. (1997). Intellectual Capital: The New Wealth of Organizations Doubleday/Currency. New York: NY.
  • Sveiby, Karl-Erik (1998), Measuring Intangibles and Intellectual Capital–An Emerging First Standard, Internet version.
  • Tan, H.P., Plowman, D. and Hancock, P. (2007). Intellectual capital and financial return of companies. Journal of Intellectual Capital, 8 (1), 76-95, CrossRef
  • Ting, I.W & Lean, H.H. (2009). Intellectual capital performance of financial institutions in Malaysia. Journal of Intellectual Capital, 10 (4), 588-99, CrossRef
  • Tovstiga, G and Tulugurova, E. (2007). Intellectual capital practices and performance in Russian enterprises. Journal of Intellectual Capital, 8 (4), 695-707, CrossRef
  • Tsen, Shu-Hsiao and Hu, Hsiang-ling (2010). A Study of the organizational competitiveness and intellectual capital indicators of international tourist hotels, Human Resource Management Student Newspaper, 10 (1), 79-104
  • Wang, W., and Chang, C. (2005). Intellectual capital and performance in causal models Evidence from the information technology industry in Taiwan. Journal of Intellectual Capital, 6(2), 222–236, CrossRef
  • Williams, S.M. (2001). Is intellectual capital performance and disclosure practices related Journal of Intellectual Capital, 2 (3), 192-203, CrossRef
  • Yalama, A. and Coskun, M. (2007). Intellectual capital performance of quoted banks on the Istanbul stock exchange market. Journal of Intellectual Capital, 8 (2), 256-71, CrossRef
  • Zehri, C., Abdelbaki, A. &Bouabddellah, N. (2012). How Intellectual Capital affects firm’s performance? Australian Journal of Business and Management Research, 2 (8), 24-31
Share.

Comments are closed.