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Innovation and business sustainability (IBS): empirical evidence from Indian pharmaceutical industry (IPI)
Published online by Cambridge University Press: 23 April 2019
Abstract
The aim of our study is to investigate how innovation is taking place through different research and development (R&D) activities and to establish a link between innovation and business sustainability in the context of Indian pharmaceutical companies. Our study is based on the secondary data. Sample data of 37 Indian pharmaceutical companies listed on the National Stock Exchange have been used based on the stratified sampling technique. For empirical analysis we have performed descriptive statistics, correlation matrix, and panel regression analysis as statistical techniques with the help of STATA 12.0 statistical package. R2 value can predict 100 and 98.20% variability in return on assets (ROA) and return on equity (ROE) in model 1 and model 2, respectively. In model 1, the value of c2 is 1.48 and its corresponding p value is 0.00 (<0.05) which means that the model is a good fit for interpretation. R&D intensity is having a positive effect on ROA and the effect is statistically significant at 1% level. Advertising and marketing intensity, capital intensity, leverage ratio and operating expenditure to the total assets ratio are having positive effect on ROA but the effect is not statistically significant. In model 2, the value of F statistics is 8025.62 and its corresponding p value is 0.00 which is <0.05. It means that the model is a good fit for study. R&D intensity is having a positive effect on ROE and the effect is statistically significant at 1% level. Advertising and marketing intensity, capital intensity and operating expenditure to the total assets ratio have positive effect on ROE and the effect is statistically significant at 1% level. Leverage ratio is having a negative effect on ROE but the effect is statically significant at 10% level.
Keywords
- Type
- Research Article
- Information
- AI EDAM , Volume 33 , Special Issue 2: Knowledge Engineering and Management Applied to Innovation , May 2019 , pp. 117 - 128
- Copyright
- Copyright © Cambridge University Press 2019
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