Review of literature

A number of literature studies have been conducted to serve our purpose out of which a few have been mentioned as under. Prior studies have shown the relationship between “Innovation” and “Business Sustainability”.

The study performed by Hayes and Abernathy (Reference Hayes and Abernathy1980) explains their point of view that in order to succeed, the firms have an organizational commitment to compete on technological grounds. The firms therefore should offer superior products to earn profits in the long run.

Erickson and Jacobson (Reference Erickson and Jacobson1992) in their study confirmed that innovation plays a significant role in gaining an edge over current and potential competitors of the firms. The specific nature of R&D expenses for brining innovation would determine its advantage. Innovation enables the firms to prevent imitation by the rivals and earn adequate or above average profits which ensures business sustainability.

Bhagwat et al. (Reference Bhagwat, DeBruine and Gondhalekar2001) in their study experienced that a 1% increase in R&D investment resulted in one-quarter percent increase in earnings per share (EPS) for publicly traded pharmaceutical companies for the period 1989–98 in USA.

Drucker (Reference Drucker2002) wrote in his seminal work that the basic function of a business is to bring innovation to earn profits. Thus, in order to gain a competitive edge, more resources should be spent on R&D activities for brining innovation which enables the organizations to enjoy business sustainability.

Shankaran (Reference Shankaran2016) made a comparative study between the Indian origin pharmaceutical companies and multi-national companies (MNCs). In his study he had considered return on assets (ROA) and return on equity (ROE) as explanatory variables. The study shows that Indian companies are becoming more aggressive to be at par with MNCs.

Cooper et al. (Reference Cooper, Gulen and Schill2008) in their study have shown a significant positive relationship between investment in R&D and future returns in the accounting literature. Most studies in accounting and finance explained a positive relationship between investment in R&D and future returns toward business sustainability.

Ray and Chittoor (Reference Ray and Chittoor2007) in their study propose a conceptual model of internationalization for emerging economy firms through a combination of exploitation and exploration strategies through new products and new markets in the context of liberalized economies.

Cooper in his study experienced a positive relationship between R&D investments and firm earnings.

The research work conducted by Ehie and Olibe (Reference Ehie and Olibe2010) showed that after controlling for firm size, industry concentration, and leverage, R&D investment positively affects firm performance.

Wang (Reference Wang2011) in his study confirmed that the level of performance of a firm will be a function of its resources of R&D activities. The firms which allocate higher R&D expenditures are expected to earn more than those that do not.

A study conducted by Kiran and Mistra (Reference Kiran and Mistra2011) focuses on the changed scenario due to Amended Patent act 2005. Researchers have clearly mentioned that Indian pharmaceutical companies have understood the need of research activity to survive in market and nowadays most of them are changing from imitation to innovation by increasing R&D activity to sustain in the market place.

In a study conducted by Christina Sheela and Karthikeyan (Reference Christina Sheela and Karthikeyan2012) found that Cipla pharmaceutical Company's financial performance is high, followed by Dr Reddy's Laboratories and then Ranbaxy Pharmaceutical. The three companies are significant at their level. In conclusion, researchers have expressed that ROE and return on investment are the most comprehensive measure of profitability of a firm.

Kafouros and Forsans (Reference Kafouros and Forsans2012) in their study explain that the knowledge acquisition from foreign countries results in superior performance and assists firms in unlocking their innovation potential.

In a study, Donelson and Resutek (Reference Donelson and Resutek2012) have expressed that the level of R&D and the changes in it are not related to the profits. From the perspective of an investor, R&D costs are thought of as an expense whereas in reality, these are the investments which will generate future revenues in the form of profits.

Atalay et al. (Reference Atalay, Sarvan and Anafarta2013) in their study have found that technological innovation has significant and positive impact on firm performance in Turkish automotive supplier industry.

Rao et al. (Reference Rao, Yu and Cao2013) in their study discuss that nowadays, technique innovation is the precondition that companies, especially technology intensive companies, can survive and progress further followed by an investment effect analysis with empirical method and comparative method on the technique innovation in the context of China and Japan.

In the study conducted by Tyagi et al. (Reference Tyagi, Mahajan and Nauriyal2014) recommends encouragement to public-private R&D partnership in the realm of basic and applied research, which could be commercially harnessed by the interested private sector partner(s).

Zambad and Londhe (Reference Zambad and Londhe2014) in their study discuss the amended patent act and its effect on Indian pharmaceutical companies with respect to innovation.

Ayaydin and Karaaslan (Reference Ayaydin and Karaaslan2014) in their study focused their investigation on the study of the effect of R&D investment on firm's financial performance. The authors have used ROA as a measure of financial performance. Their study have revealed the positive effect of R&D intensity on the firm performance by using Generalized Method of Moments (GMM) system estimators for a sample of 145 manufacturing firms registered BIST for the period of 2008–2013 with respect to manufacturing firms in Turkey.

Xin (Reference Xin2015) in his study has found that technologically innovative products have a statistically significant positive effect on operating performance.

A study by Geoffrey and Pal (Reference Geoffrey and Pal2015) investigates the R&D impact on the financial value of the company. Their study focuses on the relationships between R&D and earnings, operational performance, revenue growth, and market value. Their study also includes the empirical analysis using a sample of 103 companies which registered high values of R&D, between 1979 and 2013. Overall, researchers have assumed a positive impact of R&D on the corporate value, using a new variable that includes both decision and outcome features.

Nandy and Pal (Reference Nandy and Pal2017) in their study established that R&D activities create significant impact on the financial performance of MNCs pharmaceutical companies operating in India. In their study they had measured financial performance through ROA and had used research and development intensity (RDI) and advertising and marketing intensity (AMI) as independent variables (IV). With the help of panel regression analysis the authors found the significant positive impact of RDI and AMI on ROA and the effect was statistically significant at 5% level and 1% level, respectively.

Jui et al. (Reference Jui, Yen, Cheng and Chieh2017) in their study entitled have explored that the firms with a high level of innovative energy have better stock returns and net sales, but such firms do not have an advantage in terms of operating income. The empirical results of their study indicate that higher R&D expenses increase operating costs which, in turn, decreases operating income despite increased net sales.

Freihat and Kanakriyah (Reference Freihat and Kanakriyah2017) in their study empirical study have incorporated simple linear regression analyses to discover the effect of R&D on company performance. The authors have used ROA, ROE, and EPS as a proxy to measure company performance, and to measure R&D expenditure we considered the following items: research, experiments, studies, and courses. They have found that there is a significant impact of R&D expenditure on company performance as measured by ROA, ROE, and EPS, which is consistent with the results for developed countries.

Research gap

All prior studies indicate that there is an impact of R&D activities on the financial performance of the pharmaceutical companies. But, none of the studies so far conducted has established the link between “Innovation” and “Business Sustainability” and hence we are taking an endeavor for further study to bridge the gap between “innovation” and “business sustainability” by establishing a link between the two in the context of IPI.

Theoretical foundation of study

Innovation can be a catalyst for the growth and success of business organization, and helps the organizations to adapt and grow in the marketplace. Being innovative does not only mean inventing. Innovation can mean changing the business model and adapting to changes in the environment to deliver better products or services. The successful exploitation of new ideas is crucial to a business being able to improve its processes, bring new and improved products and services to market, increase its efficiency and, most importantly, improve its profitability. The profitability can also be in the form of ROA or ROE. Emerging markets like India are facing rapid growth of chronic “Western” diseases such as diabetes, hypertension, chronic respiratory problems, cancer, heart disease, and neurological disorders. In some cases, conditions such as diabetes are turning into near-epidemic situations. In India, for example, the prevalence of diabetes and cancer is projected to rise in many fold in the years to come. In the current scenario, innovation is the need of the hour in the IPI, having the large and diverse patient pool, rising cost of treatments, and increasing risk factors of chronic diseases due to changing lifestyles in emerging countries like India. The GOI and the IPI have both shown growing focus to boost innovation. Multiple initiatives by the GOI to boost innovation and protect IPR and the increasing R&D spend by the corporate segment highlight this.

The framework pertains to theoretical foundation of the study is shown in Figure 1.

Fig. 1.

Innovation and business sustainability framework (IBSF)

Source: Conceptualized by the Authors.The IBSF has been conceptualized based on the relationship between “Innovation (I)” and “Business Sustainability (BS)”.

From Figure 1 we come to know that, in IPI, R&D activities are undertaken for the purpose of the innovation. An innovative healthcare solution is extremely helpful for taking care of the unmet healthcare needs where the speedy recovery of different diseases and disorders of needy patient fraternities are being ensured. It is possible to market innovative healthcare solution for the benefit of society at large. As a result Indian pharmaceutical companies adapting R&D activities for bringing “innovation” is for catering the contemporary healthcare needs as well as enjoying the satisfactory financial returns which has been measured in the form of ROA and ROE in our study. Satisfactory financial returns always acts as a catalyst to help the organization to continue its business operation in the long run which basically ensures “business sustainability”.

Objective of the study

The objective of our study is mentioned as follows:

1. (1) To investigate how innovation is taking place through R&D activities of listed Indian pharmaceutical companies to provide innovative healthcare solution.

2. (2) To establish the relationship between innovation and business sustainability with financial performance of listed Indian pharmaceutical companies.

Hypotheses

We are interested in observing whether innovation is having any relation with business sustainability or not. “Innovation” is measured by R&D expenses and “business sustainability” is measured by financial performance.

With respect to the research presented above, we propose the following hypotheses.

Research methodology

A research methodology is the specification of methods and procedures for acquiring the information needed. It is the over-all operational framework of a study that stipulates what information is to be collected from which sources and by what procedures. Complete stepwise procedures what we have followed during the study have been discussed in the following as per the systematic order.

Data collection

The study is based on the secondary data only. The data relating to sales turnover, market capitalization, R&D expenses, advertisement and marketing expenses, capital intensity, leverage ratio, and operating expenditure to total assets ratio pertain to Indian pharmaceutical companies listed in India's National Stock Exchange (NSE) have been collected from different sources as mentioned in Table 4.

Table 4.

Secondary data sources

Source: Different Secondary Data Collection Sources.

The name of Indian pharmaceutical companies considered for the study is shown in Table 5.

Table 5.

List of Indian pharmaceutical companies

Source: Capital Market Publishers India Ltd. Database.

Variables specification and empirical model

Variable specification

To establish the relationship between “innovation” and “business sustainability” we have used the following variable names under the purview of dependent variable (Y), independent variable (X), and control variable (X). Nomenclature of the variables with detailed explanation is provided in Table 6.

Table 6.

Description of different variables used in the study

Variable Description Source: Evidence from Existing Literatures.

From Table 6 we come to know the details of the variables which we have used in our study.

Empirical model

We are proposing herewith two different empirical models by incorporating all dependent, independent, and control variables which have been considered for our study and already discussed in detail in the previous section.

The two different empirical models of our study are as follows:

(1)$${\rm RO}{\rm A}_{{\rm it}} = \alpha + \beta _1{\rm RD}{\rm I}_{{\rm it}} + \beta _2{\rm AM}{\rm I}_{{\rm it}} + \beta _3{\rm C}{\rm I}_{{\rm it}} + \beta _4{\rm L}{\rm R}_{{\rm it}} + \beta _5{\rm OE}{\rm R}_{{\rm it}} + E_{{\rm it}}\comma \,$$

(2)$${\rm RO}{\rm E}_{{\rm it}} = \alpha + \beta _1{\rm RD}{\rm I}_{{\rm it}} + \beta _2{\rm AM}{\rm I}_{{\rm it}} + \beta _3{\rm C}{\rm I}_{{\rm it}} + \beta _4{\rm L}{\rm R}_{{\rm it}} + \beta _5{\rm OE}{\rm R}_{{\rm it}} + E_{{\rm it}}\comma \,$$

where ROA_it, Return on Assets; ROE_it, Return on Equity; RDI_it, Research and Development Intensity; AMI_it, Advertisement and Marketing Intensity; CI_it, Capital Intensity; LR_it, Leverage Ratio; OER_it, Operating Expenditure to Total Assets Ratio; and E _it, error term.

Statistical tools and techniques

For the accomplishment of the research objective we have used the following statistical tools and techniques for data analysis and interpretation:

1. (A) Descriptive Statistics

2. (B) Correlation Matrix and

3. (C) Regression Analysis

We have used Application Software STATA 12 for data analysis. The complete data analysis and results are discussed in the following section.

Data analysis and results

After collecting cross-sectional and time series data from the sample, a strongly balanced panel dataset has been arranged for the analysis of our study. After that, descriptive statistics has been presented as per the following for all DV, IV, and CV to know the nature of sample properly.

Now, with the help of correlation matrix we will be able find out the presence of partial correlation if any and through variation inflation factor (VIF) result we can ensure the presence of multicollinearity in our strongly balanced dataset. These two diagnostic tests result would enable us to include the variables which are having less VIF values (<0.10) and have less (<0.80) partial correlation and finally with these tests result we will take forward the study.

In the next stage multivariate regression analyses have been performed by incorporating the dependent variables (Ln_ST and Ln_MC) one by one. In our study, we have applied two models associated with panel data analysis and the models are:

1. (a) fixed effect model (FEM) and

2. (b) random effect model (REM)

In last stage we have applied the Hausman specification test (popularly known as Hausman test) for selecting the appropriate model of panel regression analysis between FEM and REM and the detailed interpretation of the appropriate model as per the Hausman test has been discussed in our study.

Descriptive statistics

In this section we have dealt with the basic statistical values of the variables which are calculated. In our study we have applied descriptive statistics to describe the basic features of the data. With the help of descriptive statistics we also come to know the simple summaries about the sample and the measures.

Table 7 reveals the complete description of 777 observations which is the product of 37 Indian pharmaceutical companies for the period of 21 years (from 1995 to 2015). The average amount of R&D expenditure for brining innovation toward providing innovative healthcare solution, deployed by the sample Indian pharmaceutical companies is 0.76 crore. There is a wide variation in case of R&D expenditure where the minimum amount is 0.22 crore and maximum amount is 1.39 crore. This dispersion is also supported by standard deviation of 0.29 crore. We can observe that the sample Indian pharmaceutical companies are incurring 2.37 times less in the areas of advertising and marketing expenditure in comparison with R&D expenditure since the average advertising and marketing expenditure is 0.32 crore. In case of AMI the values are highly spread with minimum of 0.22 crore and maximum of 0.55 crore where the standard deviation is 0.07 crore. The average amount of capital intensity employed by the sample companies is 0.31 crore. The values of CI is also dispersed where the minimum is 0.06 crore and maximum is 5.22 crore and this dispersion is well supported by standard deviation 0.72 crore. The sample Indian pharmaceutical companies also utilized leverage ratio 56.94% where minimum is 0.26 and maximum is 1.07. In case of LR the dispersion is supported by standard deviation 0.22. The sample Indian pharmaceutical companies have employed operating expenditure with an average spending amount of 0.35 crore and this spending is highly dispersed where the minimum spending is 0.01 crore and maximum spending is 5.79 crore. This OER spending dispersion is also supported by standard deviation 0.62 crore. By deploying R&D expenditure and different other expenditures, the sample companies can find the path of business sustainability by obtaining favorable financial performance with respect to ROA as 88.38% and ROE as 100.89% for the study period. This type of exceptional financial performance can well be anticipated when different listed Indian pharmaceutical companies takes risks and spends substantial amount of R&D expenditure for brining innovation toward enjoying business sustainability with high margins.

Table 7.

Descriptive statistics of different variables (DV, IV, and CV)

Source: Authors processing in Stata Software (Version-12).

Bivariate correlation matrix

Bivariate correlation is the analysis of the relationship between the two variables and the bivariate correlation matrix will help us know the existence of partial correlation in our dataset if any. Before conducting our panel regression analysis we are using bivariate correlation matrix as an econometric test to ensure that there is no serial correlation (>0.80) in our strongly balanced panel dataset.

The bivariate correlation matrix is shown in Table 8.

Table 8.

Bivariate correlation matrix for pair-wise correlation

Source: Authors processing in Stata Software (Version-12).

*Denotes at the 5% level of significance.

From the bivariate correlation matrix presented in Table 8, we can find the bivariate correlation between DV versus IV and CVs. In this bivariate correlation matrix financial performance related DV are ROA and ROE which basically ensures business sustainability. RDI is an IV which has been used to measure innovation in our study and the CV which we have used for our study are AMI, CI, LR, and OER for the robustness of the test. In our strongly balanced dataset there is no serial correlation found since all the correlation coefficients in the abovementioned bivariate correlation matrix falls <0.80. We can find that ROA is having significant positive correlation with RDI, AMI, CI, LR, and OER. We have also observed that RDI, AMI, CI, LR, and OER are having statistically significant positive correlation with ROE. All coefficient estimates are statistically significant at the 5% level. Overall this bivariate correlation matrix is favorable for the study.

Variation inflation factor (VIF)

The VIF and tolerance are both widely used measures of the degree of multicollinearity of the ith IV with the other IVs in a regression model. VIF measures how much variance of the regression coefficient is inflated by multicollinearity.

In our study, we would like to perform VIF as an econometric test before running the panel regression model. In this econometric test we want to ensure that our strongly balance panel data set is totally free from multicollinearity and the test has applied for all explanatory variables (IV and CV) taken for our study.

From Table 9 we have observe the VIF values of RDI, AMI, CI, LR, and OER are 1.66, 2.25, 1.67, 1.12, and 2.28 respectively. All VIF values are <4 and are nowhere near to the rule of thumb (the maximum acceptable cut-off value for the VIF is 10 and minimum cut-off value for tolerance that is, 1/VIF is 0.10 as per the different econometric literature studies available). For our study all the variables RDI, AMI, CI, LR, and OER will be considered since all these variables are free from multicollinearity as per VIF Result.

Table 9.

VIF test results for multicollinearity

Source: Authors processing in Stata Software (Version-12).

Empirical model and panel data multivariate regression analysis for empirical model-1

After testing the multicollinearity problem in our independent (IV) and CV we have applied FEM and REM taking all two DV ROA and ROE of our study one after another. At first we will run the following empirical model-1 by incorporating ROA as DV:

(1)$${\rm RO}{\rm A}_{{\rm it}} = \alpha + \beta _1{\rm RD}{\rm I}_{{\rm it}} + \beta _2{\rm AM}{\rm I}_{{\rm it}} + \beta _3{\rm C}{\rm I}_{{\rm it}} + \beta _4{\rm L}{\rm R}_{{\rm it}} + \beta _5{\rm OE}{\rm R}_{{\rm it}} + E_{{\rm it}}.$$

Table 10 shows the result of panel regression analysis taking ROA as a DV.

Table 10.

Panel regression results under FEM and REM (Y = ROA)

Source: Authors processing in Stata Software (Version-12).

***Denotes significant at 1%, **at 5% and *at the 10% level of significance.

From Table 10 we can find panel data regression results for both FEM and REM under empirical model-1. We have carried out the Hausman test in order to have a robust selection between FEM and REM. The result of Hausman test is shown in Table 11.

Table 11.

Hausman test results for appropriate model selection

Source: Authors processing in Stata Software (Version-12).

From Table 11 we can visualize the p value of χ² is 0.09 which is >0.05 or 5%. Since p value of χ² is >0.05 or 5%, the result is statistically insignificant and the null hypothesis (H₀) is accepted and the alternate hypothesis (H₁) is rejected. Finally REM is found to be most appropriate for the panel dataset used in our study.

The results of REM are as follows.

The value of χ² is 1.48 and its corresponding p value is 0.00 (<0.05) which means that the model is good fit for interpretation. The value of R ² is 1.00. It signifies that the model can predict 100% variability. Explanatory variable: RDI is having positive effect on ROA and the effect is statistically significant at the 1% level. We have also observed that all CVs: AMI, CI, LR, and OER are having a positive effect on ROA but the effect is not statistically significant.

Empirical model and panel data multivariate regression analysis

Empirical model-2

In this section we would like to estimate the following panel data regression analysis by incorporating ROE as a DV:

(2)$${\rm RO}{\rm E}_{{\rm it}} = \alpha + \beta _{1{\rm it}}{\rm RD}{\rm I}_{{\rm it}} + \beta _{{\rm 2it}}{\rm AM}{\rm I}_{{\rm it}} + \beta _{{\rm 3it}}{\rm C}{\rm I}_{{\rm it}} + \beta _{{\rm 4it}}{\rm L}{\rm R}_{{\rm it}} + \beta _{5{\rm it}}{\rm OE}{\rm R}_{{\rm it}} + E_{{\rm it}}.$$

From Table 12 we can find panel data regression results for both FEM and REM under empirical model-2. We have carried out the Hausman test in order to have a robust selection between FEM and REM.

Table 12.

Panel regression results under FEM and REM (Y = ROE)

Source: Authors processing in Stata Software (Version-12).

***Denotes significant at 1%, **at 5% and *at the 10% level of significance.

Table 13 shows the result of Hausman test. From the table we can visualize the p value of χ² is 0.00 which is < 0.05 or 5%. Since p value of χ² is <0.05 or 5%, the result is statistically significant and the null hypothesis (H₀) is rejected and the alternate hypothesis (H₁) is accepted. Finally FEM is found to be most appropriate for the panel dataset used in our study.

Table 13.

Hausman test results for appropriate model selection

Source: Authors processing in Stata Software (Version-12).

The results of FEM are as follows.

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 good fit for study. The value of R ² is 0.9820 which signifies that the model can explain 98.20% variability. IV: RDI is having positive effect on ROE and the effect is effect is statistically significant at the 1% level. CV: AMI, CI, and OER have a positive effect on ROE and the effect is statistically significant at the 1% level. We have also found that CV: LR is having negative effect on ROE but the effect is statically significant at the 10% level.

Conclusion and implications

After analyzing and interpreting the data we can come to conclusion that by holding the hands of innovation through R&D activities satisfactory financial performance is achieved which in turn ensures business sustainability for the listed Indian pharmaceutical companies. Our study has revealed that innovation through R&D activities in IPI are yielding satisfactory ROA and ROE which is highly beneficial to strengthen the financial capabilities for business sustainability. Apart from RDI, Indian pharmaceutical companies should take AMI, Capital Intensity (CI), LR, and operating expenditure to the total assets ratio (OER) into their business model for ensuring IBS since we have found that all these factors are having positive impact on the financial performance. Innovation will not only impact the business sustainability but also these innovative healthcare solution will certainly improve the quality of living of the needy patient fraternities and will bring smile in their faces by taking away the pain of sufferings from the different diseases and disorders toward ensuring saving of human lives which is need of the hour for the emerging economy like India.

Limitations

Our study employs sample size of 37 Indian pharmaceutical companies listed with NSE and it is considered not to be the sufficient for detailed analysis. Further, the study has considered the tools and techniques for analysis which may have its own limitations. The study does not consider the impact of lagging effect of the R&D activities on financial performance.

Social implications

The continuous efforts rendered by Indian pharmaceutical companies in the areas of R&D activities, innovation, and research breakthrough are constantly taking place and these breakthrough with the help of innovation will not only impact the financial performance for ensuring business sustainability but also these innovative healthcare solution will certainly improve the quality of living of the needy patient fraternities and will bring smile in their faces by taking away the pain of sufferings from the different diseases and disorders toward saving human lives. Innovation also ensures quality healthcare solutions by taking care of different unmet healthcare needs of the human being.

Scope of further research

Since we have conducted the study pertaining to the pharmaceutical industry, researcher fraternities can look forward further research work in any of the following areas to bring the innovation through R&D activities for ensuring business sustainability.

As far as the “innovation” is concerned with the help of R&D activities in IPI, there may be the possibilities of certain risks and uncertainties associated with R&D activities and “innovation” which may affect the financial performance of the different Indian pharmaceutical companies which in turn may act as an obstacle for “business sustainability.” Therefore, studies can further be performed for measuring and minimizing the risks and uncertainties associated with R&D activities and “innovation” pertain to IPI toward improving the financial performance of the Indian pharmaceutical companies for ensuring “business sustainability”.