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Association of Intellectual Capital with Return on Equity

Introduction: Concept of intellectual capital is not new to the managers, researchers and academicians but its measurement and reporting have always been a problem to them. With the growth of knowledge-intensive companies importance of intellectual capital has been realized by investors. But reporting standards are unable to cope up with the expectations of the investors by not providing the accurate picture of the organization. Measuring intangible assets are difficult because of its intangible nature. Guthrie, Petty & Johanson (2001) has drawn the attention towards the problem related to accounting and management of intellectual capital. It is widely accepted that intellectual capital should be measured and managed properly by the companies. But there is a lack of consistency among the researchers and academicians about any single measuring model (Bontis et al., 1999).

To have a transparent position of the company, intellectual capital should be reported accurately in the annual reports. But Guthrie, Petty & Ricceri (2006) found that voluntary disclosure of intellectual capital is very low in and was in qualitative form rather than quantitative. Abeysekera & Guthrie (2003) conducted the study to examine the reporting of intellectual capital in the developing nation and found that Sri Lankan firms have reported a large range of intellectual capital though not using the term directly. And most of the reported items were external capital and human capital.

Ricceri & Guthrie (2008) conducted a survey to assess the information about the use of intellectual capital in decision making. Results concluded that financial professional did not found the information in the annual reports useful in taking decision and they were of the view that greater disclosure of intellectual capital would increase company’s share price. Garcia-Meca (2005) examined intellectual capital disclosure and its uses in decision making process by Spanish companies. Results found that intellectual capital was widely reported to financial analyst and also used in their decision making process.

Intellectual capital is considered as the difference between market value and book value of the firm. Further, to minimize the difference James Tobin (1969) modified it and book value was substituted by the replacement value of the companies in Tobin’s q model. Differences can also be seen among the financial reporting system of developed and developing countries. To have consistency in reporting system, International Accounting Standards (now IFRS) was adopted by many countries. India also decided to adopt IFRS from April 1, 2011 and the decision was taken by the Prime Minister Dr. Manmohan Singh at G20, a global forum of the world’s largest economies.

The present paper proposes to study the total value added efficiency of intellectual capital and its components’ association with profitability and market valuation of the two major indices i.e. CNX S&P Nifty and Junior fifty for a time period of ten years.

The paper is divided into four different sections: Section I includes the review of existing literature, Section II proposes the research methodology, Section III is for results and analysis. Section IV concludes the paper with policy implication.

I. Review of literature

Intellectual capital and intangible assets have been used interchangeably by different authors. Choong (2008) has drawn attention towards the different definitions of intellectual capital given by different authors. The crux of the most definitions was that intellectual capital is non-monetary assets without physical in nature and can generate future benefits for the organization. Sanchez, Chaminade, & Olea, (2000) divided intellectual capital into three different components namely human capital, structural capital and relational capital.

Chen, Cheng & Hwang (2005) examined the association between intellectual capital efficiency and company’s financial performance and market valuation. Results were found in support of the hypothesis that intellectual capital and financial and market performance were positively related. Investors give different value to the components of intellectual capital i.e. physical capital, human capital and structural capital. Further research and development expenditure used in the study provided additional information of the structural capital.

Firer & Stainbank (2003) investigated a sample of 65 companies in South Africa and found that intellectual capital of the South African companies have explanatory power of productivity and profitability and market valuation. Productivity was negatively and profitability was positively associated with intellectual capital. The reason for this could be less information disclosure available in the annual reports of the companies so the investors were not able to put information in the calculation and hence value of the intellectual capital was not reflected in the market valuation of the companies.

Tan, Plowman & Hancock (2007) examined the relationship between intellectual capital and financial performance of the companies. The study was carried out using the VAIC method and partial least squares (PLS). Results found that companies’ intellectual capital was positively related with its current and future performances. The three financial ratios selected as the indicator of companies’ performance were return on equity (ROE), earning per share (EPS) and annual stock return (ASR). It was also analyzed that intellectual capital efficiency was differed by industry to industry.

Villalonga (2004) empirically investigated that intangibility and sustainability of competitive advantage have inter-relationship among them. Two methods were calculated, they were Tobin’s q and hedonic regression of q. It was concluded that intangible assets play significant role in sustaining a firm’s competitive advantage.

Bruggen, Vergauwen & Dao (2009) investigated the determinants of intellectual capital disclosure in decision making. Content analysis method was used in the study of 125 publicly listed Australian companies. Contrary to previous studies, the paper found industry type and firm size as the major determinants of intellectual capital disclosure. Finally there was no evidence to support the hypothesis that there was relationship between information asymmetry and intellectual capital disclosure.

Firer & Williams (2003) examined the association between intellectual capital and traditional measures of performance i.e. return on assets, assets turnover ratio and market to book value used as proxies for profitability, productivity and market valuation. Intellectual capital was measured by VAIC model. Results of the study found no association between the intellectual capital and traditional measures of corporate performance. Physical capital remained an important factor associated with the performance of the companies.

Wang & Chang (2005) analyzed the effects of intellectual capital elements on the performance of business in Taiwanese IT companies. Results found that all elements of intellectual capital (innovation capital, process capital and customer capital) except human capital directly affected the business performance. Bozzolan, Favotto & Ricceri (2003) investigated the disclosure of intellectual capital was related to external capital and factors affecting disclosure were industry and size of the organization.

Bontis (2001) reviewed the existing intellectual capital models with their strengths and weaknesses. They are Skandia Navigator, IC-Index, Technology Broker, Intangible Assets Monitor, MVA and EVA. The author highlighted the need for more empirical research on the intellectual capital reporting to broaden the area.

Sriram (2008) investigated the importance of composition of tangible and intangible assets of the firms in evaluation of financial health. For that purpose, sample is divided into two sub-samples, one having traditional physical assets and other having primarily intangible assets. A sample of 457 bankrupt firms was analyzed with two models namely Altman’s model and hybrid models. Results have shown that although financial variables played an important role in financial health but intangible assets information has also revealed improvement in the financial health.

Kamath (2007) evaluated 98 Indian banks to analyze the value added efficiency of the banks. Results found that the best performers of the intellectual capital efficiency were the foreign banks. Human capital efficient banks were foreign banks and Indian public sector banks were efficient in utilizing the physical capital. It was because of the investments of funds in the large amount of human capital which may not be contributing to the efficiency of the banks.

Ghosh & Mondal (2009) examined the association between intellectual capital and financial performance of the pharmaceuticals and software companies in India. Results found that intellectual capital companies are an indicator of profitability but not of productivity and market valuation of the companies.

Kamath (2008) conducted the study to find the association between intellectual capital and its components with traditional performance measures and market valuation. The analysis was carried out on top 25 Indian pharmaceutical companies with a time period of 1996 to 2006. Finding suggests that Indian domestic companies were better in utilizing and performing in case of intellectual capital by VAIC ranking. Among the different components of intellectual capital, human capital was found to have a major impact on profitability and productivity of the companies.

Gan & Saleh (2008) carried out the research to assess the association between value added efficiency and corporate performance of technology-intensive companies (MESDAQ) listed on Bursa Malaysia. Findings of the study suggested that there was dependency on the physical capital efficiency of the companies. Physical capital efficiency has been significantly related with profitability and human capital efficiency with the productivity of the companies. Overall VAIC fails to explain the market valuation of the companies.

After that a number of studies were carried out to know the importance of intellectual capital in decision making by managers and analyst. In addition, studies have been carried out to know the value added efficiencies of the companies with the help of the model Value Added Intellectual Co-efficiency.

Studies have been carried out to check the association between intellectual capital efficiency and traditional performance and market valuation of the companies (Muhammad & Ismail, 2009), (Makki, Lodhi & Rahman, 2008) and (Zhang, Zhu, & Kong, 2006). India is still in the nascent stage of reporting and measuring intellectual capital.

Few studies have been conducted in India and most of them are sector specific. Few of them are (Kamath, 2007) on Indian banks, (Bower & Sulej, 2006) and (Kamath, 2008) on Indian pharmaceutical sector and (Ghose & Mondal, 2009) on Indian software and pharmaceutical industry.

Research Gaps Indentified:

The above mentioned are carried out on specific sectors of Indian corporate but there is a research gap regarding the overall corporate performance of the companies. This research gap has necessitated the researcher to check the intellectual capital efficiency in overall Indian corporate sector.

II. Research Objectives and Methodology: S&P CNX Nifty and CNX Junior are taken as sample and data is obtained from Prowess database maintained by Centre for Monitoring Indian Economy (CMIE). A time period of ten years is taken i.e. from 2000-01 to 2009-10.

As all the hundred companies are not listed from the last ten years, so the data is minimized in the previous years. Those companies whose key variables for the calculation of VAIC are not found excluded from the study. To have consistency in the results outliers are also removed. So the final sample consists of the ninety-four companies in the year 2009-10. The above hypothesis is explained through a diagram as follows

Figure 1.1 Diagrammatic represents of the proposed hypothesis

Figure 1.1 Proposed hypotheses

Objectives of the Study

The main objective of the present study is to investigate the relationship with the total value added efficiency with market valuation and profitability of the companies. Further relationship of components of VAIC i.e. physical capital employed, human capital employed and structural capital efficiency with market valuation and profitability for a time period of ten years (from 2000-01 to 2009-10).

Hypothesis of the Study

H01: There is no association between VAICTM and market to book value of the Indian companies.

H02: There is no association between VAICTM and return on equity of the Indian companies.

H03: There is no association between components of VAICTM (i.e. CEE, HCE & SCE) and market to book value of the Indian companies.

H04: There is no association between components of VAICTM (i.e. CEE, HCE & SCE) and return on equity of the Indian companies.

Data and sample selection: Two indices of National Stock Exchange (NSE) i.e. S&P CNX Nifty and CNX Junior are taken as sample and data is obtained from Centre for Monitoring Indian Economy (CMIE) database called Prowess. A time period of ten years is taken from 2000-01 to 2009-10.

Variables used in the study:

Value Added Intellectual Co-efficient (VAICTM): Prof. Ante Pulic (1998, 2000) developed the VAICTM model for measuring intellectual capital efficiency of the companies. It is the value added efficiency of the intangible assets. Value added is the difference of output and input of the companies.

Value Added = Output – Input

Output consists of all the revenue and input includes all the expenses incurred in earning the revenues except the expenditure on manpower. It is argued that an expense on manpower is considered as investment rather than expense.

Pulic has divided VAIC into three major efficiency divisions. They are capital employed efficiency (CEE), human capital efficiency (HCE) and structural capital efficiency (SCE). This model measure how much efficiency is created by the rupee spends on three components of intellectual capital.

VAIC is the sum of the above three co-efficient.

VAIC = CEE + HCE + SCE

Value Added of the companies is measured by the summation of the following items.

VA= I + DP + D + T +M + R + WS

Where

I = Interest expenses

DP = Depreciation expenses

D = Dividend paid

T = Taxes paid

M = Equity of minority shareholders in net income of the subsidiaries

R = Profits retained of the company and

WS = Wages and salaries.

It can also be calculated as

VA = W + I + T + NI

Where,

W = wages of the employees

I = Interest

T = Taxes

NI = Profits after taxes

Further,

CEE = VA / CE

HCE = VA / HC

SC = VA - HC

SCE = SC / VA

Where,

CEE = Capital Employed Efficiency

VA = Value added

CE = Capital employed taken as net worth of the company.

HCE = Human Capital Efficiency

HC = Total of wages and salaries of the employees

SCE = Structural capital efficiency and

SC = Structural capital

This method is considered relatively good since it is based on the audited annual reports which are audited and easily available. This is even useful in comparison with other similar companies in the industry.

Return on Equity (ROE)

Return on equity measures a company's profitability by revealing how much profit a company generates from the shareholders’ investment. It is calculated as

Return on Equity = Net Income/Shareholder's Equity

Market to book value (MB)

Market valuation is measured by market to book value of the companies. It is calculated as total market capitalization divided by the book value of the companies.

Total Market Capitalization = Market share prices * No. of outstanding shares / book value of the shares

Research models

Here model 1 and model 3 check the association between intellectual capital efficiency with return on equity and market valuation of the companies. Model 2 and model 4 will depict the relationship with components of intellectual capital i.e. capital employed efficiency, human capital efficiency and structural capital efficiency.

MBit = α0 + β1 VAICit + εit (1)

MBit = α0 + β1 CEEit + β2 HCEit + β3 SCEit + εit (2)

ROEit = α0 + β1 VAICit + εit (3)

ROEit = α0 + β1 CEEit + β2 HCEit + β3 SCEit + εit (4)

III. Results and Analysis

Descriptive statistics Table 1.1 presents the descriptive statistics for both dependent and independent variables.

Table 1.1 Descriptive statistics for selected variables

Year

CEE

HCE

SCE

VAIC

MB

ROE

2010

Mean

0.544

9.133

0.801

10.478

4.383

0.308

Std Deviation

0.408

9.035

0.149

9.119

6.850

0.374

2009

Mean

0.592

14.209

0.805

15.606

3.234

0.285

Std Deviation

0.452

27.052

0.166

27.132

3.778

0.303

2008

Mean

0.611

13.325

0.814

14.750

5.110

0.338

Std Deviation

0.424

18.129

0.166

18.218

4.986

0.326

2007

Mean

0.624

13.171

0.793

14.587

4.626

0.331

Std Deviation

0.344

26.267

0.176

26.342

3.814

0.346

2006

Mean

0.584

10.460

0.774

11.818

4.136

0.298

Std Deviation

0.343

15.375

0.162

15.468

3.246

0.256

2005

Mean

0.617

7.140

0.759

8.516

3.449

0.331

Std Deviation

0.374

6.484

0.158

6.582

2.960

0.328

2004

Mean

0.705

6.134

0.740

7.578

2.926

0.343

Std Deviation

0.461

5.185

0.156

5.397

2.722

0.476

2003

Mean

0.710

6.604

0.743

8.057

2.076

0.295

Std Deviation

0.565

6.033

0.157

6.250

2.347

0.372

2002

Mean

0.678

6.960

0.735

8.373

2.303

0.231

Std Deviation

0.619

7.272

0.172

7.538

3.207

0.270

2001

Mean

0.705

8.166

0.748

9.619

3.660

0.266

Std Deviation

0.660

8.960

0.182

9.254

6.600

0.333

Table 1.1 shows the mean value of VAIC is highest 15.606 in the year 2009 and lowest 7.578 in the year 2004 which depicts that VAIC is considered good and that the sample companies are generating intellectual capital efficiency in the time period of ten years. Trend of the last ten years for VAIC shows an increasing trend in the last five years but declined in the year 2010.

The mean value of MB used as the proxy for the market valuation of the companies ranges from 5.110 (2008) to 2.076 (2003) which indicates that investors of these companies placing high value to the shares of the selected companies in comparison to the book value of the shares.

Mean value of ROE is used as the proxy for profitability from investors’ perspective. It ranges from 0.338 to 0.231 which depicts that selected companies are generating desirable profits from the shareholders’ investments.

Correlation analysis

Table 1.2 Pearson Correlation analyses of selected variables

Year

MB

ROE

2010

VAIC

-0.200**

VAIC

-0.112

2009

VAIC

-0.182**

VAIC

0.030

2008

VAIC

-0.159***

VAIC

0.046

2007

VAIC

-0.342*

VAIC

0.022

2006

VAIC

-0.274*

VAIC

-0.011

2005

VAIC

-0.346*

VAIC

0.111

2004

VAIC

-0.312*

VAIC

0.208**

2003

VAIC

-0.120

VAIC

0.352*

2002

VAIC

-0.105

VAIC

0.325*

2001

VAIC

-0.033

VAIC

0.263**

Note: *,** & *** represent level of significance at 1, 5 and 10 percent.

Table 1.2 shows the results of Pearson Correlation analyses and found market to book value of the selected companies are negatively related with the intellectual capital efficiency and found significant in the given time period. Return on equity was positively related with the intellectual capital efficiency.

Results of linear multiple regressions

Table 1.3 shows the Regression results of Market to book value with VAIC

Model 1: MBit = α0 + β1 VAICit + εit

Year

Independent variable

Co-efficient

t-statistics

 

2010

Constant

1.564

5.718*

Adjusted R2

0.029

VAIC

-0.243

-1.956***

F-value

3.825**

2009

Constant

1.202

5.510*

Adjusted R2

0.023

VAIC

-0.163

-1.780***

F-value

3.169***

2008

Constant

1.685

7.029*

Adjusted R2

0.015

VAIC

-0.157

-1.558

F-value

2.428

2007

Constant

2.061

7.981*

Adjusted R2

0.107

VAIC

-0.401

-3.412*

F-value

0.117*

2006

Constant

1.718

7.465*

Adjusted R2

0.064

VAIC

-0.290

-2.598**

F-value

6.747**

2005

Constant

1.796

6.641*

Adjusted R2

0.108

VAIC

-0.442

-3.218*

F-value

10.353*

2004

Constant

1.621

4.955*

Adjusted R2

0.084

VAIC

-0.463

-2.671**

F-value

7.132**

2003

Constant

0.633

1.607

Adjusted R2

-0.001

VAIC

-0.185

-0.965

F-value

0.932

2002

Constant

0.287

0.915

Adjusted R2

-0.005

VAIC

-0.135

-0.842

F-value

0.709

2001

Constant

0.371

0.990

Adjusted R2

-0.016

VAIC

-0.046

-0.255

F-value

0.065

Note: *,** & *** represent level of significance at 1, 5 and 10 percent.

Table 1.4 shows the Regression results of Market to book value with components of VAIC

Model 2: MBit = α0 + β1 CEEit + β2 HCEit + β3 SCEit + εit

Year

Independent variable

Co-efficient

t-statistics

 

2010

Constant

1.558

5.713*

Adjusted R2

0.023

CEE

0.066

0.642

F-value

1.735

HCE

-0.234

-2.065**

 

SCE

0.017

0.029

2009

Constant

1.301

4.262*

Adjusted R2

0.016

CEE

0.000

-0.002

F-value

1.492

HCE

-0.203

-1.895***

 

SCE

0.240

0.536

2008

Constant

1.692

6.622*

Adjusted R2

0.012

CEE

0.021

0.171

F-value

1.374

HCE

-0.165

-1.812***

 

SCE

0.026

0.046

2007

Constant

1.573

4.701*

Adjusted R2

0.069

CEE

0.082

0.619

F-value

0.101**

HCE

-0.205

-1.589

 

SCE

-0.374

-0.849

2006

Constant

1.778

5.171*

Adjusted R2

0.061

CEE

0.097

0.771

F-value

2.819***

HCE

-0.298

-2.138**

 

SCE

0.181

0.351

2005

Constant

0.839

2.030**

Adjusted R2

0.122

CEE

-0.065

-0.530

F-value

4.562*

HCE

-0.111

-0.707

SCE

-0.941

-1.883***

2004

Constant

0.487

0.682

Adjusted R2

0.058

CEE

-0.008

-0.074

F-value

2.367***

HCE

-0.016

-0.056

SCE

-0.952

-1.122

2003

Constant

0.872

1.393

Adjusted R2

0.006

CEE

-0.064

-0.510

F-value

1.129

HCE

-0.335

-1.354

SCE

0.300

0.406

2002

Constant

1.256

1.452

Adjusted R2

-0.011

CEE

-0.030

-0.239

F-value

0.768

HCE

-0.503

-1.491

SCE

1.294

1.244

2001

Constant

1.490

1.805***

Adjusted R2

-0.011

CEE

0.084

0.371

F-value

0.785

HCE

-0.497

-1.359

SCE

0.982

1.484

Note: *,** & *** represent level of significance at 1, 5 and 10 percent.

Table 1.3 represents the results of the model 1 where MB is dependent variable and VAIC is independent variable. Results show that VAIC is found to be significantly associated with intellectual capital in 6 out of 10 cases. So it can be concluded that investors are placing higher values for the companies with greater intellectual capital.

But Table 1.4 shows that in the components of intellectual capital, only human capital is significantly associated with intellectual capital only in 4 out of 10 cases. Structural capital is found to be associated only in a single year.

In Model 1 the adjusted R ranges from -0.016 to 0.107 and in model 2, it ranges from -0.011 to 0.122 highlighting that model 2 is a better representation of the market valuation of the companies. Zeghal & Maaloul (2010) found that VAIC and companies’ stock market performance is significantly associated only in high-tech industry sectors among a sample of 300 UK companies.

Similar study conducted by Firer & Stainbank (2008) did not found association between VAIC and market valuation of South African companies. Chen, Cheng & Hwang (2005) found that VAIC is significantly positively related with MB and three components were also positively significant with market valuation of the companies. In addition to the three components advertising and R&D expenditure were also added and found to have increased the explanatory power of the equation.

Table 1.5 shows the Regression results of Return on Equity with VAIC

Model 3: ROEit = α0 + β1 VAICit + εit

Year

Independent variable

Co-efficient

t-statistics

 

2010

Constant

-1.296

-5.293*

Adjusted R2

0.002

VAIC

-0.120

-1.079

F-value

1.164

2009

Constant

-1.602

-7.335*

Adjusted R2

-0.010

VAIC

0.027

0.291

F-value

0.085

2008

Constant

-1.448

-6.584*

Adjusted R2

-0.009

VAIC

0.041

0.446

F-value

0.199

2007

Constant

-1.432

-5.924*

Adjusted R2

-0.011

VAIC

0.023

0.207

F-value

0.043

2006

Constant

-1.454

-6.584*

Adjusted R2

-0.012

VAIC

-0.011

-0.100

F-value

0.010

2005

Constant

-1.745

-6.710*

Adjusted R2

-0.001

VAIC

0.128

0.972

F-value

0.945

2004

Constant

-1.899

-6.811*

Adjusted R2

0.029

VAIC

0.255

1.728***

F-value

2.987***

2003

Constant

-2.440

-8.294*

Adjusted R2

0.110

VAIC

0.421

2.961*

F-value

8.768*

2002

Constant

-2.696

-8.098*

Adjusted R2

0.090

VAIC

0.439

2.617**

F-value

6.848**

2001

Constant

-2.205

-8.060*

Adjusted R2

0.052

VAIC

0.265

2.021***

F-value

4.086**

Note: *,** & *** represent level of significance at 1, 5 and 10 percent.

Table 1.6 shows the Regression results of Return on Equity with components of VAIC

Model 4: ROE it = α0 + β1 CEEit + β2 HCEit + β3 SCEit + εit

Year

Independent variable

Co-efficient

t-statistics

 

2010

Constant

-1.000

-4.340*

Adjusted R2

0.105

CEE

0.277

3.195*

F-value

4.643*

HCE

-0.140

-1.466

 

SCE

0.221

0.442

2009

Constant

-1.251

-4.123*

Adjusted R2

-0.003

CEE

0.136

1.412

F-value

0.909

HCE

-0.053

-0.498

 

SCE

0.356

0.800

2008

Constant

-1.201

-5.433*

Adjusted R2

0.099

CEE

0.390

3.656*

F-value

4.498*

HCE

0.039

0.495

 

SCE

-0.168

-0.345

2007

Constant

-1.248

-4.279*

Adjusted R2

0.067

CEE

0.360

3.034*

F-value

3.096**

HCE

0.048

0.421

 

SCE

-0.011

-0.030

2006

Constant

-0.854

-2.768*

Adjusted R2

0.129

CEE

0.350

3.096*

F-value

5.155*

HCE

-0.093

-0.742

 

SCE

0.769

1.664

2005

Constant

-1.348

-3.627*

Adjusted R2

0.139

CEE

0.406

3.693*

F-value

5.148*

HCE

0.087

0.612

SCE

0.084

0.187

2004

Constant

-0.440

-0.813

Adjusted R2

0.212

CEE

0.311

3.730*

F-value

6.999*

HCE

-0.273

-1.252

SCE

1.172

1.823***

2003

Constant

-0.260

-0.586

Adjusted R2

0.211

CEE

0.134

1.474

F-value

6.605*

HCE

-0.373

-2.150**

SCE

1.988

3.582**

2002

Constant

0.712

1.042

Adjusted R2

0.432

CEE

0.386

3.757*

F-value

15.985*

HCE

-0.739

-2.786*

SCE

3.324

3.993*

2001

Constant

-1.462

-2.634*

Adjusted R2

0.134

CEE

0.393

2.341**

F-value

3.887**

HCE

0.121

0.499

SCE

0.353

0.678

Note: *,** & *** represent level of significance at 1, 5 and 10 percent.

Table 1.5 shows the association of return on equity i.e. the return on the invested money of the shareholders. Results accept the hypothesis that returns on equity not found to be associated with intellectual capital.

Table 1.6 presents the association with components of intellectual capital with return of equity and found that capital employed efficiency i.e. physical capital of the firms were more significant factors in the financial performance of the companies physical capital 9 cases. But contrary to our results Maditious et al. (2011) found relationship between HCE and ROE in Greek companies. No association was found between ROE and other financial performance with VAIC.

Tin & Lean (2009) found that VAIC and ROA were positively related among the Malaysian finance sector.

IV. Findings and Conclusion

The empirical finding from the study shows that market valuation of the company reflecting the intellectual capital invested by them. The relationship between MB and VAIC was found significantly negative. The results of the return of equity are not encouraging for the investors. As still physical capital is dominating in Indian companies, results of the association of physical capital found to be majorly associated with return on equity.

In India very few studies were conducted covering sector specific companies. This study covers almost all types of industries and therefore results would be more generalized in nature. Further more studies can be carried out covering a large number of companies.

Policy Implications: Indian corporate sector can make use of the results in recognizing the importance of the intellectual capital measurements. Effective utilization of the intellectual capital can enhance the market valuation the companies.

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