Performance Measurement and Shareholder Value Creation in Indian Computer Software Industry: An Empirical Analysis
Abstract
The paper empirically analyses business performance of Indian computer software industry over the years 2003-04 to 2012-13 with the help of Return of Investment (ROI) and Economic Value Added (EVA) of select 10 companies in this industry. A comparative analysis of ROI and EVA reflected in these companies is made using some statistical tools like average, Standard Deviation, Maximum and Minimum values and Coefficient of Variation. It is observed that Tata Consultancy Services (TCS), Infosys and Wipro are the top companies in this industry in terms of their ROI and EVA. One way ANOVA conducted to analyse the significant difference among select companies in terms of their ROI and EVA shows that select companies are significantly different. Pearson’s Correlation Coefficient (r) between ROI and EVA depicts a strong positive correlation between these two business performance indicators. Significance of this correlation is then tested using t test. The result suggests that the correlation between ROI and EVA is not significant in this industry. Impact of EVA and select economic variables on ROI is analysed with the help of Multiple Regression Analysis. Standardised regression coefficients for each predictor variables estimated based on Ordinary Least Square Method indicate the relationship between each predictor variable and ROI. Significance of regression coefficients are tested using t test. It is observed that variables like Net Operating Profit after Tax, Capital Employed, Net Sales, etc. significantly influence ROI in this industry. Adjusted Coefficient of Multiple Determinations (R²) shows a strong association between ROI and its predictor variables. Finally, the model perfectly fits the data according to one way ANOVA result.
Keywords: Return on Investment, Economic Value Added, Indian Computer Software Industry, Pearson’s Correlation Coefficient, t test, one way Analysis of Variance, Multiple Linear Regression Analysis
JEL Codes: M490, O160
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ISSN (Paper)2224-5758 ISSN (Online)2224-896X
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