The Role of Intellectual Capital in Creating Value in the Banking Industry Sarayuth Saengchan

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1 The Role of Intellectual Capital in Creating Value in the Banking Industry Sarayuth Saengchan Abtract: In recent years, financial institutions, especially those in the banking industry, have experienced a dynamic and competitive environment. Competition at a cross-border scale make local banks adjust their competitive position to sustain their financial performance. The banking industry is one of the most knowledge-intensive industries. Intellectual Capital (IC) generally represents the critical resource in the value creation process. The purpose of this study is to investigate empirically the relation between the value creation efficiency and firms' financial performance by capturing the perception of intellectual capital in the banking industry and identifying perceived value of this organizational variable in the bank. In the intellectual capital measurement model, elements of intellectual capital are defined in such dimensions as human capital and structural capital Using data drawn from Bank of Thailand and the Stock Exchange of Thailand, the Pulic's Value Added Intellectual Coefficient (VAIC TM ) are employed as the efficiency measure of capital employed and intellectual capital. The focus is on the used human capital (HC), structural capital (SC) and physical capital (CA) of the Thai banking industry and their impact on firms' performance. The regression models are used to examine the relationship between corporate value creation efficiency and financial performance, i.e. profitability, to see their potential impact of intellectual and physical capital. The study confirms the existence of Intellectual Capital in the performance of the Banking Industry in Thailand. Keywords: Banks, Intellectual Capital, Financial Performance, Cost efficiency. 1. Introduction and Background 1.1. Rationale Globalization, which is essentially a process driven by economic forces, has brought the increasing division of production into separate stages carried out in different locations. It is becoming increasingly effective in integrating goods and services markets at the global level. The globalization processes today facilitate, indeed, accelerate change in innovation driven economies. Also, it is also related to free movement of goods, services, labor and capital, thereby creating a single market in inputs and outputs. Globalization leads to transactions in financial products. In recent years, financial institutions, especially those in the banking industry, have experienced a dynamic and competitive environment. Competition at a cross-border scale make local banks adjust their competitive position to sustain their financial performance. The value created

2 depends far less on their physical assets than on their intangible ones. These assets, often described as intellectual capital, are being recognized as the foundation of organizational competitiveness in the twenty-first century. The banking industry is one of the most knowledge-intensive industries. Intellectual Capital (IC) generally represents the critical resource in the value creation process. 2. Literature Review There are several definitions for intellectual capital. Intellectual capital can be viewed as knowledge, in formation, intellectual property and experience that can be put to use to create wealth (Stewart, 1997). Intellectual capital includes all employees, organizational knowledge and their abilities to create value added and led to sustainable competitive advantage. Intellectual capital has been identified as a set of intangibles (resources, capabilities and competences) that drives the organizational performance and value creation. (Bontis,1998) This suggests causal relationships between intellectual capital and organizational value creation. At least three elements are common in almost all definitions: (i) intangibility: (ii) knowledge that creates value and; (iii) effect of collective practice (Maria do Rosario Cabrita and Jorge Landeiro Vaz, 2005) It is assumed that competitive advantage depends on how efficient the firm is in building sharing, leveraging and using its knowledge. Increasing attention on the pivotal role played by intellectual capital in value creation process has resulted in the method of measuring intellectual capital. Pulic (1998) proposed the Value Added Intellectual Coefficient (VAIC TM ) to provide information about the value creation efficiency of tangible and intangible assets within a company. VAIC TM is an analytical procedure designed to enable management, shareholders and other relevant stakeholders to effectively monitor and evaluate the efficiency of Value Added (VA) by a firm's total resources and each major resource component. Value added (VA) is the difference between sales (OUT) and inputs (IN): OUT - IN = VA. Output (OUT) represents the overall income, all the products and services sold on the market. Inputs (IN) contain all the expenses, everything that came

3 into the company. Labour expenses were not calculated into input due to the active role in the value creating process, intellectual potential, represented by labour expenses) Value added grows out of physical capital and intellectual potential.. Instead of valuing the intellectual capital of a firm, the VAIC method mainly measures the efficiency of firms' three types of inputs: physical and financial capital, human capital, and structural capital, namely the Capital Employed Efficiency (CEE) indicator of VA efficiency of capital employed, the Human Capital Efficiency (HCE) indicator of VA efficiency of human capital, and the Structural Capital Efficiency (SCE) indicator of VA efficiency of structural capital. The sum of the three measures is the value of VAIC. The higher VAIC value results in better companies ' value creation potential. Banking sector is one of the sectors, utilizing intensive Intellectual Capital. With regards to bank performance and intellectual capital, there are some researches that study the role of Intellectual Capital on banks performance. Pulic (1997, 2002) used VAIC TM model, which he developed, measured intellectual capital performance of Austrian banks in and Croatian banks in They revealed significant differences in bank ranking based on efficiency and performance. Dimitrios G. Mavridis (2004) applied the VAIC TM method in order to analyze the data of Japanese banks for the financial period 1 April March 2001, analyze the intellectual or human (HC) and physical capital (CA) of the Japanese banking sector and discussed their impact on the banks value-based performance. The study confirmed the existence of significant performance differences among the various groups of Japanese banks but also the differences between the Japanese and some European banks. Pek Chen Goh (2005) measured the intellectual capital performance of commercial banks in Malaysia for the period 2001 to 2003, using efficiency coefficient called VAIC" developed by Ante Pulic. As a whole, all banks have relatively higher human capital efficiency than structural and capital efficiencies. Domestic banks were generally less efficient compared to foreign banks. There were significant differences between rankings of bank according to efficiency and traditional accounting measures.

4 G. Barathi Kamath (2007) estimate and analyze the Value Added Intellectual Coefficient (VAIC TM ) for measuring the value-based performance of the Indian banking sector for a period of five years from 2000 to The study confirms the existence of vast differences in the performance of Indian banks in different segments, and there is also an improvement in the overall performance over the study period. There is an evident bias in favour of the performance of foreign banks compared with domestic banks. With regards to bank performance in Thailand, Saovanee Chantapong (2001) examined the impact of the crisis and the financial sector restructuring introduced after 1997 financial crisis in Thailand on Thai banking Industry. It is found the domestic banks experienced larger negative impacts from the financial crisis than foreign banks and foreign banks performance rebounded faster than that of domestic banks. Hidenobu Okuda and Suvadee Rungsomboon (2004) investigated the impact of foreign bank entry on Thai domestic banks by using panel data on 17 domestic commercial banks from 1990 to An increase in foreign bank presence leads to a rise in overhead expenses, a decline in profits, and an increase in the interest spreads of domestic banks. In the short run, increased competition from foreign banks negatively affects domestic banks but domestic banks' performance should improve in the long run. Saovanee Chantapong (2005) estimated and compared cost efficiency of domestic and foreign banks in Thailand by using bank-panel data between 1995 and The estimated results suggest that the unit costs of production of domestic and foreign banks are indistinguishable, although the two types of banks focus on different areas of the banking business. However, there are very few studies on intellectual capital performance in Thailand. 3. Statement of Problem The Banking industry was hardly hit by the economic crisis during Its financial performance has been turned into profit since All banks were found to have reduced their credit exposure during the crisis years. They have gradually improved

5 their profitability during the post-crisis years. The results indicate that foreign bank profitability is higher than the average profitability of the domestic banks. (Table 1) After the eruption of its 1997 economic crisis, the group of foreign banks performed better than the group of the Thai banks when considering the return on assets. The group of the Thai banks experienced larger negative impacts from the financial crisis than the group of foreign banks and foreign banks performance rebounded faster than that of domestic banks. With the comparison between the group of Thai banks and the group of foreignowned banks, starting from 2001, it is found that the Thai banks has earn margins than the foreign banks because the Thai banks costs of the deposits are slightly cheaper. However, the return on assets for the foreign bank is on average higher that the Thai banks. The difference in financial performance between the two group results in the further study on how the intellectual capital plays the role on the different financial performances. 4. Research Objective This study aims to evaluate the relationship between intellectual capital capability and financial performance of commercial banks in Thailand. It is to examine interrelationships among intellectual capital components and organizational performance, with the level of human capital efficiency (HCE), capital employed efficiency (CEE) and structural capital efficiency (SCE). As an exploratory study, this study should indicate factors in determining the performance of commercial banks in Thailand, from the perspective of intellectual capital performance.

6 Table 1: Key Macroeconomics Data for Thailand, Unit: % of GDP, Otherwise as stated Gross Domestic Product at 1998 price (Billion Baht) 1. Macroeconomic Data 1.1 GDP Growth (%) - at constant 1988 price 1.2 Inflation: 2002 = 100 (% changes from the same of the previous year) 1.3 Current Account Balance 1.4 International Reserve (Billion USD) 1.5 External Debt (Billion USD) 2. Financial Sector Before Crisis Year Crisis Year After Crisis Year ,942 3,115 3,073 2,750 2,872 3,008 3,074 3,237 3,468 3,686 3,851 4, M Proportion of credits provided to: - Domestic Financial Institutions Business Banking Sector 3.1 Net Profit of commercial banks (Million Baht) 77,735 58,167-71, , ,983-1,764 84,097 20,236 50,373 96, ,418 68, NPLs (% of Total Loan) N/A N/A N/A Total Loans (% of Total Deposits) - At the end of period Foreign Liabilities of Commercial bank (Million Baht) 1, ,249,294 1,904,400 1,066, , , , , , , ,557.7 N/A Source: Bank of Thailand 5. Research Methodology 5.1. Model Estimation Regression models Model 1 and model 2 examine the relationships between Return on total assets and Cost to Assets and the aggregate measure of intellectual capital VAIC, and its three major components, Human capital efficiency (HCE) Capital employed efficiency (CEE) Structural capital efficiency (SCE) The regression models are as follows:

7 Model 1.1: ROA it = β 0 + β 1 VAIC it + GROUP it + ε it Model 1.2: ROA it = β 0 + β 1 HCE it + β 2 CEE it + β 3 SCE it + GROUP it + ε it Model 2.1: CTA it = β 0 + β 1 VAIC it + GROUP it + ε it Model 2.2: CTA it = β 0 + β 1 HCE it + β 2 CEE it + β 3 SCE it + GROUP it + ε it Variable definitions Dependent variables: Financial performance The two financial performance variables, reflecting firms efficiency on total assets are defined as follows: 1. Return on total assets (ROA) refers to Total income, including net interest income and non interest income, over total assets. 2. Cost to Assets (CTA) refers to operating costs over total assets Independent variables: 1. VAIC is a measure for corporate intellectual ability (Pulic, 2000b), providing an easy-to-calculate, standardised, and consistent basis of measure, enabling effective comparative analyses across firms. Data used in the calculation of VAIC are based on financial statements. The procedures calculating VAIC are as follows: VAIC TM i = CEE i + HCE i+ SCE i where VAIC TM = VA intellectual coefficient for firm i; CEE i = VA i /CE i VA capital employed coefficient for firm i; HCE i = VA i /HC i; human capital coefficient for firm i; SCE i = SC i /VA i; structural capital VA for firm i; VA i = Output Input (Total Income Operating Expenses excluding Salaries and employee benefits) CE i = book value of the net assets for firm i HC i = Salaries and employee benefits for firm i; SC i = VA i - HC i structural capital for firm i.

8 2. Human capital efficiency (HCE) refers to indicator of VA efficiency of human capital. 3. Capital employed efficiency (CEE) refers to indicator of VA efficiency of capital employed. 4. Structural capital efficiency (SCE) refers to indicator of VA efficiency of structural capital. 5. GROUP refers to types of commercial banks i.e. 0 = foreign banks branches and 1 = commercial banks registered in Thailand (Thai banks) Data The study of Thai banking industry will include investigating an evolutionary 8- year path of the industry from 2000 until 2007, which is the period that there are events, leading to changes in banks competitiveness. The data used in the model consist of half-year bank-level data which are acquired from the published statistics by the Bank of Thailand, which classifies the data into 2 groups, commercial banks registered in Thailand (Thai banks) and foreign banks branches. The variables are selected from the banks balance sheet and income statements. 6. Empirical Results Tables 2, 3, 4 and 5 represent descriptive statistics and correlation analyses for the dependent and independent variables. Table 2: Model 1.1: ROA it = β 0 + β 1 VAIC it + GROUP it + ε it ROA = VAIC GROUP

9 Coefficient Std. Error t-statistic Prob. VAIC GROUP Intercept R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic) From Table 2, the correlation analyses show that, under the correlation, ROA is positively related with VAIC, suggesting that banks financial performance is positively and significantly associated with the intellectual ability. The higher VAIC value, the better ROA the bank can obtain. However, the ROA-GROUP relationship is negative, indicating that different groups of the commercial banks provide different levels of ROA ratio. It is likely that the foreign banks branches have a better ROA ratio than the commercial banks registered in Thailand, providing that they have the same VAIC indicator. Table 3: Model 1.2: ROA it = β 0 + β 1 HCE it + β 2 CEE it + β 3 SCE it + GROUP it + ε it ROA = HCE CEE SCE GROUP Coefficient Std. Error t-statistic Prob. HCE CEE SCE GROUP Intercept R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid 6.86E-05 Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic)

10 From Table 3, ROA is positively related with CEE and SCE whereas it is negatively related with HCE and GROUP, suggesting that banks financial performance is positively associated with the intellectual ability s components, capital employed efficiency (CEE) and structural capital efficiency (SCE). The ROA-HCE is negatively correlated but with a small impact. The major contribution on ROA is from capital employed efficiency (CEE). Furthermore, the ROA-SCE relationship is not significant, supporting that it has less impact on ROA. In addition, the ROA-GROUP relationship is negative, indicating that different groups of the commercial banks provide different levels of ROA ratio. Table 4 Model 3.1: CTA it = β 0 + β 1 VAIC it + GROUP it + ε it CTA = VAIC GROUP Coefficient Std. Error t-statistic Prob. VAIC GROUP Intercept R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic) From Table 4, CTA is negatively and significantly related with VAIC, suggesting that banks financial performance is negatively associated with the intellectual ability. The higher VAIC value, the better cost-to-assets ratio can obtain. It is likely that the intellectual capital plays a major role in cost efficiency. In addition, the CTA-GROUP relationship is negative, indicating that different groups of the commercial banks provide different levels of ROA ratio. The commercial banks registered in Thailand have a better CTA ratio than the foreign banks branches, providing that they have the same VAIC indicator.

11 Table 5: Model 3.2: CTA it = β 0 + β 1 HCE it + β 2 CEE it + β 3 SCE it + GROUP it + ε it CTA = HCE CEE SCE GROUP Coefficient Std. Error t-statistic Prob. HCE CEE SCE GROUP Intercept R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid 7.04E-05 Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic) From Table 5, CTA is positively related with CEE and SCE whereas it is negatively related with HCE and GROUP, suggesting that banks cost efficiency depends on the intellectual ability s components, capital employed efficiency (CEE) and Human capital efficiency (HCE) Furthermore, the CTA-SCE relationship is not significant, supporting that it has less impact on CTA. In addition, the CTA-GROUP relationship is negative, indicating that different groups of the commercial banks provide different levels of CTA ratio. 7. Conclusions Empirical findings have some strong association between the efficiency of intellectual capital and banks financial performance. With regards to profitability, the efficiency of Intellectual Capital is to be significantly associated. When it is classified into major components, the efficiency of total assets (CEE) plays a major role in enhancing the returns. The total assets, both financial and physical assets, have been utilized importantly in generating highly valued returns. In terms of cost efficiency, the efficiency of intellectual capital also strongly related with the cost-to-assets ratio, indicating that the higher intellectual capability the bank has, the efficient cost can be

12 managed. Furthermore, the human resources management is a major factor in determining the cost efficiency, resulting from the highly negative correlation between cost-to-assets and human capital efficiency (HCE). Intellectual capital is increasingly acceptable as an important factor for sustainable corporate advantages. The results underline the importance of intellectual capital in enhancing firm profitability and cost efficiency. Developing intellectual capital is no less important than capital investments for companies. Therefore, Intellectual capital should be increasingly recognized as one of the major investment for driving the company s sustainable growth, together with the other factors of production. In conclusion, the empirical findings, based on correlation and linear multiple regression analysis, indicate that the association between the efficiency of intellectual capital by banks major resource components and the dimensions of financial performance is limited. This application has a limitation in that the data for foreign banks employed in the model is a consolidated one. So, the model is not able to specify the performance of each particular commercial bank due to the limitation on the published data by the government agency. It would be better if the model can incorporate the more specific data for the model of regression to see the impact on each commercial bank. Despite the limitations of using data, the present study provides valuable insights into the association between intellectual capital and financial performance. Finally, this study helps to extend the current research agenda on the intellectual capital discipline in the area of value creation. 8. References: Bontis, N. (1998), Intellectual capital: an exploratory study that develops measures and models, Management Decision, Vol. 36 No. 2, pp Cabrita, Maria do Rosario and Landeiro Vaz, Jorge (2005), Intellectual Capital and Value Creation: Evidence from the Portuguese Banking Industry, Electronic Journal of Knowledge Management, Vol 4 Issue 1 Chantapong, S Comparative study of domestic and foreign bank performance in Thailand: The regression analysis. Economic Change and Restructuring, Vol. 38, pp

13 Goh, Pek Chen (2005), Intellectual capital performance of commercial banks in Malaysia, Journal of Intellecttual Capital Vol. 6 No. 3, pp Kamath, G. Barathi (2007), The intellectual capital performance of Indian banking sector, Journal of Intellectual Capital, Vol. 8 No. 1, pp Kubo, K The degree of competition in the Thai banking industry before and after the east Asian crisis. ASEAN Economic Bulletin, Vol. 23, No. 3, pp Mavridis, Dimitrios G. (2004), The intellectual capital performance of the Japanese banking sector, Journal of Intellectual Capital, Vol. 5 No. 1, pp Mussa, Michael Factors Driving Global Economic Integration, Federal Reserve Bank of Kansas City Proceedings, August. Okuda, H., & Rungsomboon, S. The Effects of Foreign Bank Entry on the Thai Banking Market: Empirical Analysis from 1990 to CEI Working Paper Series, No , Hitotsubashi University. 2004a. Pulic, A. (1997), The Physical and Intellectual Capital of Austrian Banks, available at: Pulic, A. (1998), Measuring the performance of intellectual potential in knowledge economy, available at: Pulic, A. (2002), Value Creation Efficiency of Croatian Banks , February, 2002 available at: Stewart, T.A. (1997), Intellectual Capital: The New Wealth of Organizations, Doubleday/Currency, New York, NY.

14 Appendix ROA: Gross Income / Assets H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks Cost to Assets H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks VAIC H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks

15 HCE: VA / HC H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks CEE: VA /CE H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks SCE: SC / VA H1-00 H2-00 H1-01 H2-01 H1-02 H2-02 H1-03 H2-03 H1-04 H2-04 H1-05 H2-05 H1-06 H2-06 H1-07 H2-07 Foreign Banks Thai Banks

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