AN EMPIRICAL ANALYSIS ON THE IMPACT OF CAPITAL STRUCTURE DETRIMENTS ON PROFITABILITY OF FIRM: A CASE ON LISTED IT COMPANIES IN INDIA

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1 International Journal of Management (IJM) Volume 9, Issue 2, March April 2018, pp , Article ID: IJM_09_02_002 Available online at Journal Impact Factor (2016): (Calculated by GISI) ISSN Print: and ISSN Online: IAEME Publication AN EMPIRICAL ANALYSIS ON THE IMPACT OF CAPITAL STRUCTURE DETRIMENTS ON PROFITABILITY OF FIRM: A CASE ON LISTED IT COMPANIES IN INDIA Dr. Sudhendu Giri Deputy Dean and Professor of Finance, Maharshi Law School, Maharshi University of Information and Technology, Noida, India ABSTRACT To operate efficiently firms are free to raise equity or debt or any combination of two to optimally manage the financing of its assets. Because of tax advantage and as a cheaper source of finance Debt component is very often preferred and given a significant proportion in determining the capital structure of the firm. In present study we are mainly focusing on the analysis that whether or not capital structure has any impact over the profitability of Listed IT companies in Indian market. Through the present elaborated we are trying to establish the relationship between capstr(capital structure) and profitability and its effects on business revenue also. For a more purposeful analysis, selected firms are grouped under three categories on the basis of two attributes i.e revenue earned by business and firms assets size. At the very first stage, firms are grouped into low, medium and large on the basis of their respective assets size to test the hypothesis established that capstr has a significant impact on selected profitability measures of listed IT companies in India. For the purpose of our analytical study we choose a sample size of 96 IT companies through multi stage sampling technique for 10 years of data sets ranging from 2007 to 2017 for analysis purpose. Two dependent variables and four independent variables with one controlled variable are taken under consideration for analysis using regression. We used descriptive statistics such as Mean, S.D. and Ratio along with the techniques such as Pearson of Correlation, which is primarily used for testing the relationship between capstr variables and profitability measures under scope of our study along the side we also used Regression analysis(ols Model) to test the unidentified impact of capstr on profitability variables under scope. The use of correlation tools are mainly done for the purpose of finding out multicolinearity among independent variables to decide that what variables can further be tested in our regression models. The study proves the relationship of capstr variables and profitability variables with the help of analysis that capital structure has significantly influenced the profitability of the firms and a substantial increase in debt component in capital structure leads to a decrease in Net Profit of Listed IT companies in Indian market editor@iaeme.com

2 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India Key words: Capital Structure, Determinant, Profitability, Impact, Ratios. Cite this Article: Dr. Sudhendu Giri, An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India. International Journal of Management, 9 (2), 2018, pp INTRODUCTION The financing pattern of a firm and its associated component cost presents different dynamic dimensions of the competition between firms and an essential part of firms capital structure decision to maximize its market value and growth to shareholders investment. Capital structure strongly deals with the long term mode of finance to generate sound results pertinent for its value maximization. The debt to equity ratio reflects the two components of capital structure viz. debt and equity. For our clear understanding there is a difference between capital structure and finance structure, which besides long term debt also includes short term debts(nistor,2004). Investment opportunities have broadly expanded with liberalization and globalization of world economies and also the investment opportunities and financing options, and reason being the dependence of Capital Markets witnessed an unprecedented increase. Every firm requires capital to establish and more of it requires if it wants to grow. The sources of this capital can be different that suits to the need of the firm. They can use either equity of debt or any combination of the two in any proportion which yields the maximum value to shareholders. The issue regarding the best capital structure(debt-equity mix) is the most perplexing issue in the life of a finance manager. The debt is considered irrelevant in the firms capital structure if it is based on critical assumption of non existence of corporate taxes. But corporate taxes do exist and interest of debentures is treated as allowed expenditure which yields higher returns to a levered firm and the reason one can conclude on a general term that levered firms are valued more than an unlevered firm because of tax saving on interest paid on debt and the fact alone makes debt advantageous over equity. The firms market value increases with its debt proportion in capital structure that makes a levered firm more valuable over unlevered firms. The seminal work on the subject by Modigliani and Miller(1958,1963)dicussed the determinants of capital structure- whether interest on debt is tax deductible or not, was a pioneering work. If consider the non tax deductibility of Debt-Interest, the firm owners will be indifferent between the use of equity and debtors as they will yield the same thing to firm. But on the other hand where tax deductibility is considered, the market value of the firm can be maximized upto 100 percent by employing 100 percent debt financing. Despite the fact that Debt Interest is tax deductible, the use of debt component, in capital structure of firms varies in all firms, which gives rise to a new puzzle that what determines capital structure and what should be ideal debt ratio for firms. In last couple of years, the demarcation line has been created between small firms and large firms and recognition that former has different aspects regarding their capital structure than to later. One thing which is clearly observed in determining the capityal structure is level of risk attached with debt component, the higher the debt, the greater the risk and the interest rates but at the same time this increased tax rate also provides higher tax advantage to the firm in the form of tax saving. But contrarily, if firms do not have sufficient operating profit in any of coming year, the firm can go up in bankruptcy. The paper of Modigliani and Miller(1958) founded the approach for modern theory of capital structure presenting a view that Capital Structure can be irrelevant under what circumstances and since then many other economist also followed the same view which Modigliani and Miller followed. Some other recent studies include Taggard(1977), 17 editor@iaeme.com

3 Dr. Sudhendu Giri Masulis(1983), Ravid(1988) and Allen(1991), comment by Bhattacharya(1979) on Miller(1977), Modigliani(1982),Ross(1977) and Stiglitz(1974) and Masulis(1980) are all that includes general survey studies. Jensen and Meckling(1976) was the initiative in this area which was build on an earlier research work of Fama and Miller(1972). It has been proven empirically that profitability of firms in concentrated sector firms are totally different from the level of firms that are in competitive business. 2. STATEMENT OF PROBLEM, IT S SIGNIFICANCE AND SCOPE In the present paper the impact of capital structure on profitability of Indian firms is analyzed. While determining the profitability of Indian firms two important factors viz. assets size and business revenue are considered important determinant. In Indian context, only few studies so far, have analyzed the size and revenue and its analytical impact on profitability of the Indian firms. The present study is formulated after categorizing the selected Indian IT Firms into three different categories which are further based on two attributes. After very first, firms are classifieds on the basis of revenue i.e. total income as low, medium and high income groups and secondly they are classified on the basis of asset size into small, medium and large to formulate the hypothetical relationship that capstr has significant impact on the profitability of selected IT companies listed in Indian Stock Market. In spite of the fact that many research studies have been undertaken on the subject of capital structure, there are a few which focuses on relationship between capstr and profitability. Thus the present attempt is a maiden attempt to analyze the profitability of selected Indian IT companies and the relationship amongst grouped firms in terms of their capital structure and their profitability. The present paper is attempted to conduct an empirical study to the hypothesis that there is a relationship exist between capstr and profitability. 3. OBJECTIVES AND HYPOTHESIS The present empirical paper is aimed To analyze the factors determining capstr of Indian IT firms listed on BSE on the basis of their respective size and total income groups. To analyze the interrelationship of firms capital structure and their profitability based on the two attributes viz. assets size and revenue. 1 H 0 The selected capstr variables and Return on Assets variable of all three different Income group IT firms viz. Low Income IT firms, Medium Income IT firms and High Income IT firms do not have any significant relationship. 2 H 0 The selected capstr variables and Return on Assets variable of all three business size IT firms viz Small size IT firms, Medium size IT firms and Large size IT firms do not have any significant relationship. 3 H 0 The selected capstr variables and Return on Capital Employed variable of all three different Income group IT firms viz. Low Income IT firms, Medium Income IT firms and High Income It firms do not have any significant relationship. 4 H 0 The selected capstr variables and Return on Capital Employed variable of all three business size IT firms viz. Small size IT firms, Medium size IT firms and Large IT firms do not have any significant relationship. H 5 0 The selected capstr variables and Return on Assets variable for overall IT companies do not have any significant relationship editor@iaeme.com

4 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India H 0 6 The selected capstr variables and Return on Capital Employed for overall IT companies do not have any significant relationship. 4. LITERATURE REVIEW A Capital structure exist whenever there is a debt component exist in a firm and therefore it can be concluded that capital structure(capstr) and debt are variables that are interlinked. The value of debt cannot be determined easily if we do not have clear idea about the capital structure(capstr), which in turn is useful to determine the default or bankruptcy levels, even in turn, the capital structure can not be optimized at all if we do not know the leverage s impact on final debt value. Modigliani and Miller(1958) presents clearly an overview that admissibility of Interest as an allowed expenditure for the purpose of corporate tax creates a good incentives to companies to increase the debt levels in their capital structure design. Titman(1988) changed the implications when he breaks down the total debt into short term, long term and convertible debt rather taking aggregate debt into considerations. Whereas, Barton and Godon(1988) presented the view of managerial perspective of determining capital structure at the determinant level of company analysis. Vogt(1994) used simultaneous equation set to analyze the debt component the test the pecking order theory(myers 1984). Rajon and Zingales(1995) come to conclusion that factors identified in other previous studies in the US are correlated similarly in other countries as well. Jenson and Meckling(1976) the optimal capital structure is obtained by trading off the agency cost of debt against the benefit of debt. In his research, Jenson and Mackling identified disputes between the concerns of shareholders and managers because of the fact that managements ownership being less than 100% of the equity. Jensen(1986) proposed that this problem could be sorted out by increasing the management s ownership or by reducing the debt component in capital structure. Gratom(2000) estimated tax advantage to debt component in capital structure. Stein(2001) concluded that tax advantages increases as firm chooses to increase debt level. Booth at al(2001) concluded that ratios pertaining to debt in developing countries have the same implications as they have in developed countries but there are differences in the way that these ratios are connected by country factors like, GDP growth rates, inflation rates and capital market developments. Um(2001) stated that the static trade off theory is obtained, where the net tax advantage of debt financing balances leverage related costs such as bankruptcy and suggests that a high profit level gives rise to a higher debt capacity and interest tax shield, therefor, a profitability and financial leverage is positively related. Guney and Paudyal(2002) concluded that capital structure of companies not only affected by its own characteristics but by other surrounding environment factors also, such as the state of the economy, stock market and bank sector. Harris and Raviv (1990) in their research state that the optimal structure is obtained through a trade-off between liquidation decisions and higher investigation costs. They concluded that high leverage can be an outcome with large firm value, lower probability of reorganization following default, and higher debt level. Stulz (1990) stated that the optimal capital structure can be designed by a trade-off between benefit of debt and cost of debt. His arguments were based on the fact that managers issue debt only if they fear a takeover.diamond (1989), and Hirschleifer and Thakor (1989) in their research argued that the asset substitution problem (such as using debt to finance high risk projects instead of equity) could be reduced because of the management s reputation being at stake. While shareholders preferred to maximize an expected return, managers maximized the possibility of being successful. Diamond (1989) argued that as a firm gets older, it chooses less risky projects, thereby reducing its defaults which would lead to a lower cost of debt. This theory suggests that younger firms will have less debt than older ones. The size of companies is another feature that may influence the companies capital structure. According to Titman and Wessels (1988), size of companies is positively related to debt. Since then, 19 editor@iaeme.com

5 Dr. Sudhendu Giri extensive research work has been developed over this topic and the consensus is that SMEs are expected to show a positive relationship between size and LTD, but a negative one with STD (e.g. Michaelas et al., 1999; Hall et al., 2000; Esperança et al., 2003; Vieira and Novo, 2010). Warner (1977) said that a large company has lower transactions costs of financing externally than a small company, making it harder for the small companies to access debt and keeping them away from outside financing. In general, large companies follow a strategy of diversified business, enabling them to have stable earnings reducing the risk of bankruptcy and contributing to meet their debt obligations (Warner, 1977; Marsh, 1982). Moreover, SMEs are averse to risk because they are less leveraged and prefer to use more self-financing (Gallo and Vilaseca, 1996). According to GABA, D., & GARG, R. (2012), the effect of different company specific variables includes asset composition, business risk, size, debt service capacity, growth rate and earning rate on the capital structure of selected variables. Regression results revealed that asset composition, business risk and debt service capacity are significant factors in context of automobile industry. According to Ashraf, T., & Rasool, S. (2013), Out of 7 variables only 3 are significant (Size, tangibility and growth). It means that the firms in automobile sector should keep in mind these factors because these factors determine the leverage decision in this sector. The remaining three factors (profitability, tax, risk and NDTS) are insignificant and do not play any role in the determination of leverage in non-financial firms of automobile sector of Pakistan. According to Ani, M. A., & Amri, M. A. (2015), higher fixed assets, higher risk and size encourage firms to use the debts in the capital structure. According to Boateng, A. (2004), Firm characteristics such as size of the JV, type of the industry have effect on the capital structure. Also the level of ownership of partners of the JV influences the capital structure of the firm. According to Vicente-Lorente, J. (2001). Reputational assets technological capabilities & specific human capital affect the firm s debt ratio in spite of the fact that they are expected to have similar implications as intangible assets and non debt tax shields. Gorden (1962) observed that with the increase of size, return on investment was negatively related to debt ratio. He also confirmed the negative association between operating risk and debt ratio. Baxter (1967) articulated that the degree of degree of financial leverage would depend on the variance of net operating earnings, since; business with relatively stable income streams is comparatively least prone to bankruptcy. Hence, a negative association exists between variance of net operating earnings and degree of financial leverage. A cross sectional study Gupta (1969), on the financial structure of American Manufacturing Enterprises during confirmed^ that total debt ratios were positively related to growth and negatively related.,to size. Toy et al (1974} found higher level of operating risk is associated with higher debt ratio and growth, typically measured in terms of sales, is negatively related to debt ratio while financial leverage is indirectly tied with return on investment (ROI). Ferri and Jones (1979) investigated the relationship between firm's financial structure and its industrial class, size, variability of income and operating leverage. They found that the industry class was linked to the firm's leverage, but not in a direct manner as was suggested in other researches. Secondly, a firm's use of debt is related to its size. Finally, operating leverage does influence the percentage of debt in a firm's financial structure. In the same manner,.venkatesan (1983) analyzed the relationship between seven variables; industry categorization, size, operating leverage, debt coverage, cash flow coverage, business risk, growth ratio and financial structure of firms. It was observed that, only debt coverage ratio was found to be important variable significantly affecting the financial structure of the firm. Careltori and Siberman (1997) concluded that higher the variability in ROI lower will be the degree of financial leverage in firms. Bradley, Jarroll and Kim (2002} found that debt to asset ratio is negatively related to both volatility of annual 20 editor@iaeme.com

6 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India operating earnings and advertising and Research and Development expenses. Mohanty found that financial leverage is negatively related to profitability and value of the firm within an industry in Indian context 5. METHODOLOGY 5.1. Data Sources For the purpose of present study secondary data sources are used. The secondary data is extracted from CMIE s proprietory data base package PROWESS. The listed IT firms on BSE are divided in three different categories as Los, Medium and High based on Buisness Income of the firms. The categorization is based on the following premise: Low Income Group < Rs. 25 Crore Medium Income Group >= Rs. 25 Crore & < Rs. 100 Crore High Income Group >= Rs. 100 Crore Firms are further categorized on the basis of their respective size which is based on their total assets size. This categorization is done on the following premise: Small Size Firms < Rs. 25 Crore Medium Size Firms >= Rs. 25 Crore but < Rs. 100 Crore Large Size Firms >= Rs. 100 Crore 5.2. Sample Design for Analysis Total number of IT firms listed in BSE as on 31 st March, 2017 were 5315, out of these total firms 915 firms were listed as IT Sector firms, 836 were listed as software firms and firms doing business other than software were 107,only 797 firms out of total 836 software firms were continuously listed in BSE and the reason being only 797 firms were considered for the study. After considering the data availability and firms listing criteria for the 10 years period( to ), 113 firms were selected as sample for further analysis. Out of these 113 firms further adjustment is made in regard to 15 firms which shows extreme values(outliers) and finally 98 firms were selected by using Multi stage sampling technique Data Analysis In present study Pearson of Correlation is used to analyze whether there is any significant relationship is there between capstr and Profitability variables along with this Regression analysis using Ordinary Least Squares Model is carried out to find out the unique impact of capstr on Profitability measures. Descriptive statistics is also used for setting relationship with the help of Mean, Standard Deviation and Ratios Analysis. For the purpose of analysis two dependent variables are taken in consideration i.e. Return on Assets and Return on Capital Employed as Profitability variables. To study capstr(capital structure) paper considers Total Debt to Total Assets and Debt Equity Ratio as proxy to capital structure(capstr). Expense Ratio and Current Ratio are used as controlled variables in present study. Below is the Dependent and Independent Variables used through out the paper for analysis purpose: 1. Dependent (Profitability) Variables Return on Assets Return on Capital Employed 2. Independent (Capstr) Variables Total Debt to Total Assets Ratio 21 editor@iaeme.com

7 Dr. Sudhendu Giri Expense to Income Ratio Debt Equity Ratio Current Ratio 3. Controlled Variables Expense Ratio Current Ratio In furtherance to the above analytical process, correlation analysis is used to check out the multi collinearity amongst variables to decide what variables should we include in our regression model or how all independent variables could be used in the regression model. (Multiple) Regression Model γ e = α + β 1exp_inc + β 2TD_TA + β 3CR + β 4DER + ε Where, γ e = Dependent (Profitability) variables(return on Assets and Return on Capital Employed) exp_inc = Expense to Income Ratio TD_TA = Total Debt to Total Asset Ratio CR = Current Ratio α β 1, β 2, β 3, β 4 = and, ε = Residual error = Intercept of the Model The study includes the time period of 10 years ranges from to Since all the IT firms are not listed continuously, multi stage sampling technique is used for sample identification. 6. LIMITATION OF THE STUDY The data is collected from CMIE s PROWESS database, which is subject to accuracy and reliability of secondary data. Trend identification analysis could not be done due to lack of resources. From the point of view of sample identification data is restricted to 103 firms. Firms could not be exclusively identified as Hardware IT firms Software IT firms as Hardware firms easily get entry in Software domain and outsourcing also loses their domain as Hardware firms. Variable Table 1 Regression Results for RoA based on Business Income (Low Income Group) (Medium Income Group) (High Income Group) Intercept *** *** *** Exp_inc *** *** *** TD_TA CR *** D_E Ratio *** *** 22 editor@iaeme.com

8 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India R Adjusted R F Statistic 27.19*** *** 98.39*** P-Value(F Statistic) *** Significant at 1% level Present empirical study is focused on IT firms listed on BSE. The inferences and results conclude thereon can be useful for further studies carried on other sector firms for drawing conclusions and inferences regarding capital structure variables and profitability measures. Further inferences can be drawn on other firms from different sectors and different conclusions can be drawn for firms other than IT firms. Conclusion can be drawn on the basis of firm s size whether it has significant relationship or not for firms other than IT firms. Studies could also be carried out about to find out whether there is any significant relationship exist between fixed assets, assets structure, investment and volatility, the probability of bankruptcy and uniqueness of the product etc. in respect to capital structure and profitability. 7. MAJOR FINDINGS AND ANALYSIS The major findings from data analysis pertaining to capital structure and profitability are presented in Table1. The use of debt component in capital structure and Return on Assets of Low Income group IT firms(β=0.2937, t = -10, p < 0.01); (R 2 = , F = 27.19, p < 0.01); 31 percent of variation is reported in RoA. Therefor, H 1 0 The capital structure(capstr) variables and Return on Assets for low income group IT firms has no significant relationship is accepted. But, in case of medium income group IT firms a significant relationship is found between capstr variables and profitability. A significant but negative relationship is there with profitability and capstr (R 2 =.8923, F = , p < 0.01). Therefore H 1 0 in regard to medium income group IT firm is rejected. In case of High income class IT firms debt component in capital structure shows a significant negative impact on profitability by using assets(roa).(r 2 = , t = , p < 0.01), D_E Ratio( β = , t = -4.09, p = <0.01) is found significant statistically. So, Null Hypothesis H 1 0 in the case of High Income class IT firms is rejected. In order to find out the relationship between capital structure and profitability in respect to small size firm(on the basis of asset size) the relationship expressed by correlation analysis shows that exp_inc with RoA and TD_TA with RoA is negatively significant. Only the individual β coefficient amongst others, the β coefficient of exp_inc(β = , t = 11.53, p= < 0.01); β coefficient of TD_TA(β = , t = -5.03, p = <0.01) (R 2 = , F= 31.64, p <0.01) is significantly negative(see Table 2). Hence H 2 0 The selected capstr variables and RoA of small size group IT firms do not have any significant relationship is subject to be rejected. However, in case of Medium size IT firms, Profitability has inverse relationship by the use of debt component in capital structure, the β coefficient for exp_inc ratio is with negative sign(β = , t = -6.93, p = <0.01); for TD_TA(β = , t = -3.19, p< = 0.01); for CR the β coefficient is found to be(β = , t = -4.03, p = <0.01); and for D_E Ratio(β = , t = -3.03, p = <0.01) are found to be significant. Hence, H 2 0 is rejected in respect to Medium size IT firms. In respect to large size IT firms capital structure tends to reduce the 23 editor@iaeme.com

9 Dr. Sudhendu Giri level of Net Profit with an increase in debt component. The RoA has inverse relationship with exp_inc, TD_TA and D_E Ratio; exp_inc(β = , t = , p = <0.01); TD_TA(β = , t = , p = <0.01); D_E Ratio(β = , t = -3.87, p = <0.01) and,therefore, H 2 0 is also rejected in case of large size IT firms. In case of all selected firms the profitability variable RoA is significant negatively with capstr variables [ exp_inc, TD_TA, CR]. Net Profit(Profitability) relative to Total Asset Size tends to show an increase in Total Debt where there was an increase in CR. The β coefficient for exp_inc (β = , t = -5.93, p < 0.01) and for CR (β = , t = -2.95, p <0.01) are significant negatively(see table 2). Hence H 0 5 that The selected capstr variables and Return on Assets for overall IT firms do not have any significant relationship is rejected. Table 2 Regression Analysis for Return on Assets Based on Firms Size Variable (Small Size Firms) (Medium Size Firms) (Large Size Firms) (Overall Firms) Intercept *** *** *** *** Exp_Inc *** *** *** TD_TA *** *** *** CR ** *** D_E Ratio ** ** R Adjusted R F Statistic 31.64*** 18.19*** *** 61.97*** P Value (F Statistic) **Significant at 5% level, ***Significant at 1%level. If we look at Table 3 than it can be found that selected capstr variables and RoCE of low Income IT firms do not have any significant raltionship. Exp_inc(β = , t = 11.93, p <0.01); TD_TA (β = , t = 17.93, p <0.01); CR(β = , t = , p<0.01); D_E Ratio(β = , t = 2, p<0.01). Profitability in respect to Return on Capital Employed has negatively and significantly impacted by expenditure, TD_TA, and D_E Ratio(see table 3); therefore H 3 0 The selected capstr variables and Return on Capital Employed for Low Income IT firms do not have any significant relationship is accepted. The fit of regression is found to be good as (F=25.17 at 1% level of significance) where as the value of R 2 is very 3 low(0.2317) supporting the acceptance of H 0. But, in case of Medium Income IT girms, the paper witnessed a significant relationship between capstr variables and Return on Capital Employed(R 2 =0.5851, F= 52.37,p<0.01). The negative sign used in case of exp_inc, TD_TA, CR and D_E Ratio indicates that debt component in capital structure is subject to reduce the Net Profit component of the firms in this group. Therefore, H 0 3 with respect to Medium Income Firm is subject to be rejected. Table 3 Regression Analysis for RoCE Based on Income Group Variable (Low Income Group) (Medium Income Group) (High Income Group) Intercept *** *** *** Exp_inc *** *** *** TD_TA *** *** CR *** *** D_E Ratio *** R Adjusted R editor@iaeme.com

10 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India F- Statistic 25.17*** 52.37*** 14.81*** P Value (F-Statistic) ****Significant at 1% level Table 4 Correlation Matrix Results Variables RoA RoCE Exp_inc TD_TA CR D_E Ratio RoA RoCE *** Exp_inc *** ** TD_TA *** *** CR *** *** ** ** D_E Ratio ** **Significant at 5%level, ***Significant at 1% level Through examining the table 3 we found a significant relationship between debt component in capital structure and Return on Capital Employed in the group of High Income IT firms(r 2 = , F= 14.81,p<0.01) and the reason being H 0 3 is subject to be rejected in High Income group IT firm. Variables Table 5 Regression Analysis for RoCE Based on Firms Size (Small Size Firms) (Medium Size Firm) (Large Size Firm) (Overall Firm) Intercept *** *** **** *** Exp_inc *** *** *** *** TD_TA *** *** *** *** CR *** *** *** *** D_E Ratio *** * R Adjusted R F Statistic 35.71*** 14.73*** 32.07*** 47.93*** P Value (F-Statistic) *Significant at 10%level, **Significant at 5%level, ***Significant at 1%level. Considering the small size IT firms we found that profitability has affected inversely with the use of debt component in capital structure. Return of Capital Employed(RoCE) is found significant(r 2 = ) with F Value of 35.71(p<0.01); exp_inc(β = , t = -7.39, p<0.01); analysis found an increase in Total Debt proportionate to Total Assets Size(β = , t = -8.97, p<0.01). The use of debt component in overall capital structure negatively affected the profitability of small size IT firms(see table 5). Therefore, H 0 4, The selected capstr variables and Return on Capital Employed for small size IT firms do not have any significant relationship is subject to be rejected. In case of Medium size IT firms net earnings reduced significantly with an increase in debt component in capital structure. Exp_inc(β = , t = -5.79, p<0.01); TD_TA(β = , t = -3.43, p<0.01); CR(β = , t = -4.78, p<0.01); D_E Ratio(β = , t = , p<0.01 is significant negatively at 1% significant level. Therefore H 0 4 in respect to medium size IT firms is subject to be rejected editor@iaeme.com

11 Dr. Sudhendu Giri If we consider Large Size IT firms then the use of debt component in capital structure is less profitable. The Regression result for Return on Capital Employed for Large Size IT firms(r 2 = , F = 32.07, p<0.01) are significant negatively. It is found during study period that the use of debt component in capital structure is less profitable. Hence, H 0 4 with respect to large size IT firms is subject to be rejected. The profitability measure checked in terms of RoCE is subject to decline with an increase in TE,TD, CAS and CLS and β coefficient is found significantly negative except for D_E Ratio. Return on Capital Employed(RoCE) with exp_inc(β = , t = , p<0.01); for TD_TA(β = , t = -6.79, p<0.01); for CR(β = , t = 4.75, p<0.01) are found significantly negative(see table 5). Thus it is concluded that capital structure has a significant impact on IT firms in India. Therefore, H o 6 The selected capstr variables and Return on Capital Employed for overall IT companies do not have significant relationship is subject to be rejected. 8. CONCLUSIONS In present empirical study we considered two variables as profitability control variables i.e. RoA and RoCE and as a proxy to capstr Total Assets to Total Debt ratio and Debt Equity Ratio(D_E Ratio) are considered. For the purpose of empirical study, Pearson s coefficient of correlation and Regression (OLS Model) analysis is used along with descriptive statistics i.e. mean, standard deviation through out the paper. For analytical purposes sample data is further categorized on the basis of business income into three categories viz. High income, medium income and low income IT firms and another classification is made on the basis of assets size of the firms viz. Large size, medium size and Low size IT firms. Then statistical tools are applied to the data set for analysis and inferences are drawn from them. The profitability and the use of debt in the capital structure over different variables under scope for profitability are studied and analyzed for all two different attributes and conclusions are drawn thereon. The present study proves, considering the data on the basis on business income, Low income IT firms shows highly profitable outcome with low expenses but profitability of these groups of firms is totally independent of the debt component in capital structure. Hence, profitability in terms of RoCE is inversely impacted by exp_inc and is free from any affect of capital structure of low income IT firms. Medium income IT firms shows good results by generating good profit with low level of debt. The capital structure of medium income IT firms shows a significant impact on profitability and the use of debt component in capital structure shows a substantial decrease in net income of these firms. Better management of capital structure is seen in case of high income IT firms that most of revenue is increased with the use of debt portion in capital structure. If size of business is taken into account, it can be concluded that the small size IT firms did not show any favorable performance in generating revenue. The concerned profitability variables are inversely affected by the increase in expenses and increase in Total Debt proportionate to Total Asset Size and capital structure shows a significant impact over profitability variables taken into account for analysis for small size IT firms and a remarkable negative influence of expenses on profitability is found. In a gist it can be inferred through overall regression analysis results that profitability measured by Return on Capital Employed(RoCE) is negatively(significantly) affected by use of debt component in capstr for small size IT firms. In case of Medium size IT firms the present empirical study proves that the net income stood at 10 percent to their Total Asset Size and capital employed and debt component is lesser in capstr in Medium size IT firms. Hence, in case of Medium size IT firms profitability measured through RoA and RoCE is inversely affected by the use debt component in capstr and net income is subject to decrease with an increase in debt component in capstr significantly. As far as Large size IT firms are subject to analysis, the results reveals 26 editor@iaeme.com

12 An Empirical Analysis on the Impact of Capital Structure Detriments on Profitability of Firm: A Case on Listed IT Companies in India that the large size IT firms never relied on debt component in their capstr and yielded better results even without employing debt in capstr. Further to analysis, the increase in the use of debt component in their capstr reduced the profitability scaled by Total Asset Size for large size IT firms and less profitability is recorded with the use of debt component during the study period. Therefore, it can be concluded that there has been a strong one to one relationship between capstr variables and profitability and capstr variables has a significant impact on profitability variables and an increase in debt component in capstr significantly reduced the profitability of IT firms listed in Bombay Stock Exchange(BSE). REFERENCES [1] Allen,D. E The Determinants of the Capital Structure of Listed Australian Companies: The Financial Manager s Perspective. Australian Journal of Management 16 (2): [2] Ang, J. S Small Business Uniqueness and the Theory of Financial Management. Journal of Small Business Finance 1 (1): On the Theory of Finance for Privately Held Firms. The Journal of Small Business Finance 1 (3): [3] Antoniou, A., Y. Guney, and K. Paudyal Determinants of Corporate Capital Structure: Evidence fromeuropean Countries. Working Paper 1-17, University of Durham, Durham. [4] Azhagaiah, R., and J. Premgeetha A Study on Capital Structure in Select Companies. Management Insight 7 (1): [5] Barnea, A., R. A. Haugen, and L. W. Senbet Agency Problems and Financial Contracting. Englewood Cliffs, nj: Prentice Hall.Managing Global Transitions The Impact of Capital Structure on Profitability 389 [6] Barton, S. L., and P. J. Gordon Corporate Strategy and Capital Structure. Strategic Management Journal 9 (6): [7] Berger, A. N Capital Structure and Firm Performance: A New Approach to Testing Agency Theory and an Application to the Banking Industry. Working Paper, Board of Governors of the Federal Reserve System,Washington. [8] Bhaduri, S. N Determinants of Capital Structure Choice: A Study of the Indian Corporate Sector. Applied Financial Economics 12 (9): [9] Bhattacharya, S Imperfect Information, Dividend Policy, and the Bird in the Hand Fallacy. Bell Journal of Economics 10 (1): [10] Booth, L., V. Aivazian, A.Demirgue-Kunt, and V.Maksimovic Capital Structure in Developing Countries. The Journal of Finance 56 (1): [11] Brander, J. A., and M. Poitevin Managérial Compensation and the Agency Costs of Debt Finance. Cahiers de recherche 8827, Centre interuniversitaire de recherche en économie quantitative,montreal. [12] Chen, J. J Determinants of Capital Structure of Chinese-Listed Companies. Journal of Business Research 57 (12): [13] Chen, L., and X. S. Zhao ProfitabilityMeans Reversion of Leverage Ratios and Capital Structure Choice. Working Paper Series, Michigan State University, East Lansing, mi. [14] Deesomsak, R The Determinants of Capital Structure: Evidence from the Asia- Pacific Region. Journal ofmultinational Financial Management 14 (4 5): editor@iaeme.com

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