Impact of Firm-specific Attributes on Shareholder Value Creation of Indian Companies: An Empirical Analysis

Economic Value Added

EVA has gained wide acceptance, in both the investment community and corporate boardrooms, as a measure that links managerial decisions to shareholder value creation (Ramezani et. al. 2002). Stewart (2000) defined EVA to be an estimate of true economic profitability and the performance measure that is most directly linked to the creation of shareholder value overtime value creation), or discount under (shareholder value dilution), the capital invested. In this study, EVA has been taken as a dependent variable representing the shareholder value created or eroded by a company.

Market Value Added

MVA is a significant overall summary assessment of corporate performance, one that shows how successful a company has been in allocating, managing and redeploying scarce resources to maximize the net present value of the enterprise and the wealth of its shareholder (Stewart, 1994). The financial advisory also argue that the real measure of a company’s long term ability to add shareholder value is MVA as it depicts the confidence of the capital market on the company’s performance (Dubey, 2000). MVA being the absolute measure of shareholder value creation is obtained as the difference between the company’s market value of invested capital and its economic capital. A positive MVA indicates that the company is building value for its shareholders whereas a negative MVA signals dilution of shareholder value. Therefore, the above discussion leads to the selection of MVA as the market-based surrogate of shareholder value creation.

Tobin’s Q Ratio

This ratio was developed by James Tobin of Yale University, Nobel Laureate in Economics, who hypothesized that the combined market value of all the companies on the stock market should be about equal to their replacement costs. The Q ratio is calculated as the market value of a firm’s assets divided by the replacement value of the firm’s assets (Tobin, 1969).

Boasson and Boasson (2005) explain that if the market value reflects solely the recorded assets of a company, Tobin’s Q would be one. If Tobin’s Q is greater than one, then the market value is greater than the value of the company’s recorded assets. This suggests that the market value reflects some unmeasured or unrecorded assets of the company. On the other hand, if Tobin’s Q is less than 1, the market value is less than the recorded value of the assets of the company. This suggests that the market may be undervaluing the company.

Due to the data limitations, a substitute measure of Tobin’s Q ratio is used for the present study. It is calculated by first adding the market value of equity, book value of preferred stock and book value of debt and then dividing the sum with book value of assets.

Various firm-specific attributes and the rationale of their inclusion as a possible determinant of firm’s value creation are discussed below:

Age

Sorensen et al. (1999) argued that organizational inertia operating in old firms tend to make them inflexible and unable to appreciate changes in the environment. Newer and smaller firms, as a result, take away market share in spite of disadvantages like lack of capital, brand names and corporate reputation with older firms. Kakani and Kaul (2002) found that older firms are unable to react quickly to the recessionary phase while the younger companies are a lot more agile and open to the opportunities that come with the opening up of the sector that helps them to adapt changing trends and customer preferences. Raman and Dangwal (2003) also identified that the continuous use of outdated management and marketing practices along with the obsolete technology used by older firms are the main causes of their lesser growth. On the contrary, Malhotra and Singh (2007) stated that the age of a company may be considered as a crude proxy for both, accumulation of experience as well as reduction in the perceived risks. An older firm may have significant market share due to the long-established clientele, customers’ loyalty and business linkages with various factors of production and distribution.

Size

Size is expected to be an important determinant of firm’s performance that positively contributes to its shareholder value. Capital market imperfections give a number of advantages to larger firms in securing finance and enjoying economies of scale in almost all the fields like management, production, marketing and distribution. These advantages help the larger firms to have stronger competitive capabilities, superior access to the organizational resources and increased market power than smaller ones to achieve their goals. Moreover, the economies of scale in product and financing market further assist the larger firms to reduce their cost of production thereby increasing return on capital and hence shareholder value. Boubakar et al. (2008) identified that the impact of size factor on value creation is negative for small sized firms (−36.9 per cent) and positive for large sized firms (16.6 per cent). The phenomenon can be explained by the resource constraints and financing problems of small firms. Kakani et al. (2001) empirically tested that an increase in the size of a firm, apart from increasing its profit margin and its profitability, also reduced its risk. All these factors led to an increase in the firm’s shareholder value. Hence the foregoing discussion justifies the acceptance of size as an independent variable in the study having a positive impact on its shareholder value. For the purpose of the study, size has been measured by three broad measures namely assets, sales and market capitalization, each representing a different view of a firm’s ability to expand.

Profitability

Profitability of a company has been recognized as a driver of corporate growth and value creation by many researchers. Varaiya et al. (1987) found that both profitability and growth influence shareholder value, but profitability has a greater impact. Kakani et al. (2001) also found that a higher profit margin implies that the firm enjoys significant market power and hence can reap what economists call ‘producers surplus’ or ‘rents’. Moreover, Glenning and Goth (2007) revealed that the most striking differentiating factor of top-quartile companies’ performance in terms of total shareholder return (TSR) has been their ability to grow revenues strongly. Hence, to gauge the firms’ efficiency of converting its assets, investments, capital, sales and equity into value for shareholders, the present study uses five measures of profitability, that is, return on total assets (ROTA), return on investments (ROI), return on capital employed (ROCE), profit margin and return on equity (ROE). A higher ratio of these measures reflects a firm’s capability to generate more earnings resulting in a higher spread and improved shareholder value.

Risk

Pandey (2006) empirically found that economic profitability has a positive correlation with growth, size and capital intensity; it has a negative correlation with beta and leverage (two determinants of a firm’s risk). On the other hand, since the market value of a firm is a function of its return, given the level of risk (cited from Fruhan, 1979 and quoted in Kakani et al., 2001), risk of a firm becomes an important determinant of its valuation and hence of its shareholder value.

Efficient Resource Management (ERM)

The efficiency, with which a firm manages and utilizes its resources, is another factor affecting the value generation ability of a firm. The impact of ERM on shareholder value of a firm can be judged on the basis of four broad measures namely assets turnover ratio (ATR), working capital turnover ratio (WTR), inventory turnover ratio (ITR) and capital turnover ratio (CTR). ATR measures the company’s ability to generate sales revenue in relation to the size of the asset investment. If the assets do not create a sufficient amount of sales, these are not used effectively and this fact can have an unfavourable impact on the amount of operating profitability and on the shareholder value. At the same time, unutilized or underutilized assets increase the requirement of costly financing for additional expenditure on their maintenance and upkeep that again effects the shareholder value adversely. Thus, higher ATR implies more sales with same level of assets resulting in higher profitability and improved shareholder value. Kakani et al. (2001) stated that WTR, a measure of the solvency position of a business group is basically an expression of how much, in liquid assets, the firm currently has to build its business, fund its growth and produce value. Kishore (2002, p. 172) explains that by optimizing the investment in current assets and by reducing the level of current liabilities, the company can reduce the locking up of funds in working capital thereby, it can improve the return on capital employed in the business and hence its shareholder value.

The goal of shareholder’s wealth maximization is related to ITR that shows the efficiency with which inventory is managed and how rapidly the inventory is turning into receivables through sales. A low inventory turnover signals the excessive inventory levels than warranted by production and sales activities resulting in unnecessary tie up of funds, reduced profits and increased costs (Pandey, 1997). On the contrary, a high inventory turnover may be due to the replenishments of inventory in too small lots that further results in higher ordering costs and it may also signal that firm carries low levels of inventory that may result in frequent stock outs. But if the higher inventory turnover indicates that stocks are sold more frequently it means lesser amount of money is required to finance the inventory. Hence, ITR influences the liquidity position and operating efficiency of a firm and hence its shareholder value. Further, CTR conveys the firm’s efficiency in utilization of capital employed to generate revenues for its shareholders.

Liquidity

Pandey (1997) explains that

a liquid firm has less risk of insolvency i.e. it hardly experience a cash shortage or stock-outs. However, there is a cost associated with maintaining a sound liquidity position as a considerable amount of firm’s funds will be tied up in current assets, and to the extent this investment is idle, the firm’s profitability will suffer.

Hence the firm’s liquidity position involves risk–return implications where a firm either accepts higher risk (of low liquidity) and higher return or accepts lower risk and lower profitability. Pitman et al. (2006) identified that liquidity in the market makes the regulatory authorities able to perform their function of monitoring the firms and can improve its value. Based upon the above discussion the study considers liquidity as an important determinant of firm’s shareholder value.

Marketing Expenditure

Higher expenditure on marketing and advertising helps firms in building their reputation and also acts as an entry deterrent for new entrants in the industry (Pant and Pattanayak, 2007). Such expenditure helps to create awareness regarding products and services offered by the company and help to build the customer loyalty. Marketing expenses in building brands can also help firms to get over difficult years and protect their market share and sales volume, and defy industry trends (Mathur et al., 1998 and quoted in Kakani et al., 2001). Thus, marketing expenditure can be hypothesized to have a positive influence on the shareholder value.

Research and Development Expenditure

Research and development expenditure is expected to be a substantial determinant of corporate growth and shareholder value generation. Higher spending in R&D leads to a higher shareholder value which suggests that high R&D firms are innovative and profitable (Pant and Pattanayak, 2007). Glenning and Goth (2007) suggested that companies need to meld innovations and creativity to drive growth and value creation in the long run. A successful R&D initiative allows a firm to go for new product development, improved methods and technological upgradation which leads to a secure market share as well as high economic profitability that ultimately generates more shareholder value. Hence the study perceives the positive impact of Research and Development expenditure on shareholder value creation.

Data Source and Sample Frame

For the underlying objectives of the research work, initially a sample of the top 200 companies has been selected from BT-500, India’s most valuable companies. The rationale behind selecting BT-500 (year 2006 rankings) as that sample base is that, these companies are ranked on the basis of market capitalization in the Indian securities market and hence can be projected as India’s largest and best-performing companies (Business Today, 2006). At first, out of 200 companies, banks, financial institutions and NBFCs are excluded to prevent distortions in the comparisons. Second, companies for which complete financial information is not available have been excluded. Further, companies which are identified as outliers have also been excluded from the list resulting in a final sample of 100 companies. To avoid factors like temporal stability and business cycles influencing the study, a longer time frame of 12 years has been used. Thus, the data for this study consists of panel data of 100 companies in India covering the financial years from 1997–1998 to 2008–2009 (the list of sample companies is provided in the Appendix). The study applies multiple regression analysis for which the relevant financial data has been sourced primarily from the CMIE’s corporate database Prowess. The capital market data regarding share prices has been obtained from the Capitacharts of Capital Market Publishers of India, Ltd.

Statistical Diagnostic

Before proceeding to the regression analysis, various assumptions underlying multivariate analysis were tested. To assess the ‘normality’ of the variables employed in the regression analysis, the study applied visual analysis (that is, derivation of the probability plots), descriptive statistics (skewness and kurtosis) as well as the statistical test for normality, that is, the Kolmogorov–Smirnov test. The variables that exhibit a statistically significant departure from normality were diagnosed through data transformations by taking either log or square root of the respective variables. Testing for normality and possible remedies adopted in the study are given in Table 1.

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Table 1.

Description of Variables Affecting the Firm’s Shareholder Value

Labels	Variable Name	Notation	Description Expected Sign
Y	Dependent Variables
	Economic Value Added	EVA	Net Operating Profit after Taxes − (WACC*Economic Capital)
	Market Value Added	MVA	Market Capitalization + Book Value of Debt − Economic Capital
	Tobin’s Q	TOBIN	(Market Value of Equity + Book Value of Preferred Stock + Book Value of Debt)/ (Book Value of Assets)
	Independent Variables
X1	Age	AGE	2009 − (Year of Incorporation)	+
X2	Size			+
	Sales	LTS	Log of Total Sales
	Assets	LTA	Log of Total Assets
	Market Capitalization	LMC	Log of 365 Days Average Market Capitalization
X3	Profitability			+
	Return on Total Assets	ROTA	(Profit before Interest and Taxes − Provision for Tax/Assets)*100
	Return on Capital Employed	ROCE	(PAT nnrt/Average Capital Employed)*100
	Return on Investment	ROI	(PAT/ Net Worth)*100
	Return on Equity	ROE	(PAT − Preference Dividend/Net Worth − Preference Capital)*100
	Profit Margin on Sales	Profit Margin	(Profit before Interest and Taxes/Sales)*100
X4	Risk			–
	Systematic Risk	BETA	Covariance (Ri, Rm)/ Variance (Rm)Where, Ri is the Return on Security i and Rm is the market return
	Unsystematic Risk (Leverage)	DERATIO	Total Borrowings/Net Worth
X5	Resource Management			+
	Asset Turnover Ratio	ATR	Total Sales/Fixed Assets
	Working Capital Turnover Ratio	WTR	Total Sales/(Current Assets − Current Liabilities)
	Capital Turnover Ratio	CTR	Total Sales/Capital Employed
	Inventory Turnover Ratio	ITR	Net Sales/Average Inventory
X6	Liquidity i.e. Quick Ratio	QR	Quick Assets/Current Liabilities and Provisions	+
X7	Marketing Expenditure	MARKET EXP	(Marketing Expenditure + Advertising Expenditure)*100/Sales	+
X8	Research and Development	R & D	(Capital R&D Expenditure + Revenue R&D Expenditure)*100/Sales	+

Pearson’s correlation coefficient matrix and the average variance inflating factor (VIF) were calculated to detect and solve the existence of ‘multicollinearity’ among the independent variables (Field, 2000).

The White procedure was applied to ensure that coefficients are not ‘heteroscedastic’. Further, the study also calculates Durbin–Watson statistics to check the assumption of independent errors (‘auto-correlation’). For the purpose of the study, the backward elimination method of the stepwise regression technique was employed (Gujrati, 2004).

Empirical Model

To assess the predictive power of a set of corporate attributes on the shareholder value of a company, the study uses the tool multivariate regression analysis. The explanatory variables used in the study are firm-specific characteristics as described in Table 2. For the statistical analysis, all the variables have been taken as an average of 12 years, that is, from 1998 to 2009. A firm’s shareholder value creation has been thus taken as a function of various firm-specific characteristics like age, size, profitability, risk, etc., as shown below:

Shareholder Value Creation = f {Age, Size, Profitability, Risk, Resource Management, Liquidity, Marketing Expenditure and Research & Development Expenditure}, that is, _{1122334455667788}

where, Y is the shareholder value i.e. (EVA/MVA/Tobin’s Q)

X₁, X₂, X₃..............X₈are the various firm-specific attributes (as defined in Table 2)

β₁, β₂, β₃................β₈are coefficients of independent variables that are to be estimated

a is the constant i.e. Value of Y when b of all independent variables is zero

n is the error term which is used as a surrogate for all those variables that are omitted from the model but affect the dependent variable collectively.

Notations and formulas used for the variables and the expected relationships of explanatory variables with dependent variable (shareholder value) are presented in Table 2.

EVA Dimension

Table 3 reports the result of regression analysis between various firm-specific attributes and EVA (the accounting-based surrogate of shareholder value creation) of selected Indian companies. Applying the backward elimination method, the model starts by including all the independent variables in the regression equation and deletes market cap, QR, and R&D expenditure in the elimination process. Evaluated on the basis of ‘best model fit’ criteria with improved adjusted R² and fulfilling the model validity diagnostic, a fourth model has been chosen as the best among all. This model provides adjusted R² of 30.1 per cent with statistically significant F-value at 8.095. The average VIF at 1.503 confirms that the problem of multicollinearity does not exist in the model. The Durbin—Watson test statistic at 1.824 also evidences the non-existence of auto-correlation.

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Table 3.

Results of Multivariate Regression Analysis (Backward Elimination Method) with Economic Value Added (EVA) as Dependent Variable

Model	Age	Market Cap	ROCE	BETA	DERATIO	WTR	QR	Market Exp	R&D	F-Ratio	R2	Ad R2
1	0.127(1.263)	0.024(0.237)	0.626 (4.856)*	−0.296(−3.017)*	0.254(2.077)**	0.192(2.043)**	0.022(0.242)	−0.097(−0.969)	−0.042(−0.437)	5.270(0.000)	0.345	0.280
2	0.133(1.392)		0.635 (5.147)*	−0.299(−3.1)*	0.254(2.084)**	0.196(2.138)**	0.025(0.289)	−0.1(−1.012)	−0.037(−0.397)	5.984(0.000)	0.345	0.287
3	0.131(1.378)		0.638 (5.231)*	−0.295(−3.108)*	0.256(2.114)**	0.195(2.142)**		−0.101(−1.025)	−0.035(−0.378)	6.895(0.000)	0.344	0.294
4	0.135(1.436)		0.638 (5.251)*	−0.298(−3.161)*	0.261(2.191)**	0.197(2.174)**		−0.111(−1.777)		8.095(0.000)	0.343	0.301
5	0.134(1.427)		0.614 (5.116)*	−0.276(−2.984)*	0.280(2.361)**	0.179(2.003)**				9.399(0.000)	0.333	0.298
6			0.563 (4.888)*	−0.313(−3.502)*	0.248(2.119)**	0.214(2.461)**				11.119(0.000)	0.319	0.290

Notes: The figures in parentheses represent the t-value.

*, ** and *** indicate that coefficients are statistically significant at 1%, 5% and 10% levels respectively.

As per the fourth model, it can be observed that profitability in terms of ROCE has a significant (at the 1 per cent level) and positive impact on shareholder’s value creation. On the contrary, BETA shows a significantly (at the 1 per cent level) negative association with EVA that signals the inverse relationship between systematic risk of a company and its shareholder value which is in line with the hypothesized relationship. These results confirm that companies can enhance their shareholder’s value by improving their profitability (in terms of ROCE) and reducing their market risk. DERATIO too reveals a positive influence on shareholder value that is found to be significant at the 5 per cent level of confidence. It shows that rate of return earned on the additional funds raised by highly geared Indian firms exceed the cost paid to the loan providers. Finally, the efficient management of a company’s working capital (WTR) also seems to assist management in making additions to the shareholder value. AGE and MARKET EXP are not found to be the significant determinants of shareholder value. Hence, as far as the EVA dimension is concerned, only four predictors, that is, profitability in terms of ROCE, risk (both BETA and DERATIO) and ERM of a firm in terms of WTR, turn out to be statistically significant explanatory variables that collectively explain about 34.3 per cent of the variation in shareholder value creation in selected Indian companies.

MVA Dimension

Table 4 presents the results of regression analysis considering MVA as a surrogate of shareholder value creation, the dependent variable of the study. The results suggest that size (in terms of LMC) has a significant positive coefficient indicating that large-size Indian firms are better placed in shareholder value. DERATIO again shows a significant and positive relationship with shareholder value creation. It can be implied as higher the debt component in capital structure, lower is the total cost of capital (due to tax shield on interest charges) that further improves the shareholder value.

The sixth model given in Table 3 was selected as the best model as it reported highest adjusted R² of 54.1 per cent with a significant F value (p < 0.001).The model ensures the non-existence of multicollinearity with Average VIF at 1.667. The Durbin–Watson test statistic was also found to be satisfactory at 1.572. In this model, just two corporate attributes, that is, size (as LMC at 1 per cent), and leverage (at 5 per cent) were found to be the significant predictors that collectively explain as much as 56 per cent of the variation in shareholder value of a company. There is a lack of significant relationship between other corporate attributes and shareholder value when the latter is proxied by MVA.

Tobin’s Q Dimension

The results of regression analysis, taking Tobin’s Q as the dependent variable have been presented in Table 5. Consistent with the previously established relationship, profitability (in terms of ROCE) once again establishes a significant positive effect on shareholder value creation. Size as measured with LMC and MARKET EXP of a company depict a positive association with its shareholder value. Kakani et al. (2001) state that an increase in the size probably enhances a firm’s financial clout and its market power, while an increase in the marketing spend by a firm probably improves its market share apart from increasing the size of the product market itself, helping the firm to increase its sales, margins and shareholder value. Among efficiency ratios, CTR depicts a positive influence on shareholder value. It implies that sample companies report effective utilization of capital resources in generating revenues and creating value for their shareholders. A positive association between liquidity (QR) and Tobin’s Q indicates the competency of the sample companies to meet all present and potential demands on cash that minimizes cost and maximizes value of the firms. Moreover, the positive and significant slope coefficient of QR also signifies that companies with better liquidity position are excellently monitored by regulatory bodies, financial institutions and stock markets resulting in building the investor’s confidence that further leads to pick up the company’s market value and shareholder wealth.

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Table 4.

Results of Multivariate Regression Analysis (Backward Elimination Method) with Market Value Added (MVA) as Dependent Variable

Model	Age	Market Cap	ROCE	BETA	DERATIO	ATR	QR	Market Exp	R&D	F-Ratio	R2	Ad R2
1	−0.03(−0.364)	0.769(9.059)*	0.121(1.1)	0.04(0.536)	0.159(1.572)	0.135(1.575)	0.052(0.712)	−0.041(−.513)	−0.067(−0.871)	13.389(0.000)	0.572	0.530
2		0.758(9.71)*	0.138(1.379)	0.045(0.604)	0.163(1.63)	0.126(1.542)	0.055(0.77)	−0.043(−0.552)	−0.062(−0.824)	15.191(0.000)	0.572	0.534
3		0.76(9.784)*	0.131(1.322)	0.052(0.721)	0.169(1.698)***	0.124(1.521)	0.056(0.789)		−0.073(−1.01)	17.449(0.000)	0.570	0.538
4		0.752(9.798)*	0.128(1.304)		0.179(1.83)***	0.126(1.548)	0.067(0.958)		−0.07(−0.98)	20.376(0.000)	0.568	0.540
5		0.758(9.912)*	0.14(1.434)		0.189(1.94)***	0.12(1.48)			−0.065(−0.913)	24.288(0.000)	0.564	0.540
6		0.749(9.888)*	0.134(1.375)		0.200(2.068)**	0.122(1.509)				30.205(.000)	0.560	0.541
7		0.775(10.519)*			0.13(1.575)	0.15(1.907)***				39.279(0.000)	0.551	0.537
8		0.732(10.616)*				0.089(1.29)				56.809(0.000)	0.539	0.530
9		0.729(10.545)*								111.201(0.000)	0.532	0.527

Notes: The figures in parentheses represent the t-value.

*, ** and *** indicate that coefficients are statistically significant at 1%, 5% and 10% levels respectively.

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Table 5.

Results of Multivariate Regression Analysis (Backward Elimination Method) with Tobin’s Q as Dependent Variable

Model	Age	Market Cap	ROCE	BETA	DERATIO	CTR	QR	Market Exp	R&D	F-Ratio	R2	Ad R2
1	0.022(0.283)	0.238 (3.135)*	0.513(4.627)*	−0.085(−1.252)	0.041(0.459)	0.182(2.252)**	0.165(2.489)**	0.145(2.026)**	0.009(0.128)	18.957(0.000)	0.655	0.620
2	0.021(0.271)	0.240 (3.214)*	0.513(4.655)*	−0.084(−1.253)	0.04(.450)	0.181(2.264)**	0.165(2.506)**	0.148(2.167)**		21.557(0.000)	0.655	0.624
3		0.247 (3.621)*	0.499(5.195)*	−0.087(−1.325)	0.035(0.405)	0.190(2.593)**	0.163(2.506)**	0.148(2.184)**		24.877(0.000)	0.654	0.628
4		0.245 (3.615)*	0.477(6.043)*	−0.084(−1.293)		0.192(2.641)*	0.166(2.569)**	0.144(2.157)**		29.259(0.000)	0.654	0.631
5		0.258 (3.829)*	0.484(6.129)*			0.191(2.622)*	0.149(2.343)**	0.160(2.427)**		34.529(.000)	0.647	0.629

Notes: The figures in parentheses represent the t-value.

*, ** and *** indicate that coefficients are statistically significant at 1%, 5% and 10% levels respectively.

Further, to identify the best regression model for the sample companies, a suitable diagnostic and valid relationship between corporate attributes and Tobin’s Q ratio was adjusted for multicollinearity and auto-correlation. The diagnostic shows that fourth model given in Table 4 is better as it reports highest value of adjusted R² at 63.1 per cent. The F statistics of the model is also significant as p < 0.001. The value of R² confirms that independent variables (namely ROCE, LMC, CTR, QR and MARKET EXP) cause 65.4 per cent of the variation in shareholder value of the sample companies. The values of Durbin–Watson statistics at 1.288 and average VIF at 1.2975 also verifies that the model is statistically fit and proves the relationship between corporate attributes and shareholder value.

Thus, evaluating shareholder value on the basis of accounting as well as market based dimensions, the study reveals divergence between the results. It shows that the set of independent variables explain about 34 per cent of the variation in the accounting-based surrogate EVA whereas they account for more than 55 per cent variation in the firm’s shareholder value when it is measured on the basis of market-based surrogates, MVA and Tobin’s Q. Kakani et al. (2001) state ‘…to the extent that the effect of the predictor variables on market-based performance measures and accounting-based performance measures differs, it can be attributed to speculative forces that influence asset pricing in capital markets’. The present study reveals that although the firm characteristics like size, profitability, risk, efficient resource management, liquidity and market expenditure depict a significant influence on the shareholder value yet their composition differs. For instance, four variables, that is, ROCE, BETA, DERATIO and WTR are significant with respect to accounting-based dimension EVA, whereas just SIZE (LMC) and DERATIO depict significant association in case of market-based dimension MVA. Similarly, SIZE (LMC), ROCE, CTR, QR and MARKET EXP are found to be the significant predictors of shareholder value as far as Tobin’s Q is concerned.

The results clearly show that the all the hypotheses except H₁, H₄ and H₈, evidence the pre-established relationships and thus accepted. On the contrary, an attempt has been made to identify the probable reasons that have led to divergence between the hypothesized and actual relationships with respect to other explanatory variables. AGE (H₁), the first chosen firm attribute, is not found to be a significant predictor of shareholder value. It implies that being the oldest or the youngest company around does not lead a business to maximize shareholders’ interests. Rather, there is a need to maximize tradeoffs between margins and capital efficiency in various strategic and operational decisions. Further, leverage (H₄) depicts a positive association with firm’s shareholder value as opposed to the expected negative relationship. The results of the study are in line with the net income approach of capital structure theory given by David Durand. It states that with increased use of debt, the weighted average cost of capital declines and the total value of the firm rises. Moreover, such positive association also witness that in Indian companies, institutional investors and debt holders perform an adequate and effective monitoring role. Pandey (2006) too, identified a similar relationship between leverage and shareholder value implying that higher financial risk increases shareholder value.

At last, R&D (H₈) intensity has also been identified as an insignificant explanatory variable in both the accounting as well as market based dimensions of shareholder value. From accounting perspective, it implies that in Indian companies the amount spent on R&D activities captures such a small share of sales revenue that does not contribute to the shareholder wealth substantially. Moreover from market perspective, it seems as if Indian markets and investors do not perceive corporate R&D initiatives as an influential factor determining wealth generating capabilities of a business.