Automobile industry is one of the most significant and the fastest growing industry all around the world. As per the recent report by (Motor Trade Association) the Australian auto industry is worth $37 billion which is more than 2 % of the Australian economy. With increase in the purchasing power of the people and the declining prices of the automobiles has make it more affordable, due to which there is significant increase in the demand(Jha & Kulkarni, 2015; Lee, 2012).
However from the company’s point of view, with increase in demand there has been increase in the number of companies entering into the industry, which has made the automobile industry more competitive as compared to earlier. Some of the companies are struggling to increase the sales with various models introduced almost every month by some companies(Bollen, Skully, Tripe, & Wei, 2014; Brown & Davis, 2011).
Recently the car manufacturer company Holden Auto stopped it manufacturing in Australia, which was manufacturing the cars for more than a century. This shows that the automobile industry have become more competitive and to sustain in the market and to increase the sales the automobile industry have to invest heavily on their research and development. So, the current research is aimed to examine the impact of the R&D investment by the firms on their sale(Ernst, Hoyer, & Rübsaamen, 2010; The World Bank, 2015).
Significance of the study
The researcher is mechanical engineering by profession, which makes the research more interesting for the researcher as he has the practical knowledge of the automobile industry and pursuing the course in Business administration allows the researcher to mix the R&D investment and the sales. The current research is expected to be useful not only for the managerial purpose but also from the academic perspective also. The findings from the current study can be used by the managers in the automobile industry to review their R&D investment and compare the findings from their actual scenario.
Even though the results may not be applicable for all types of firms, the managers will be able to get some idea about the relationship between the two factors. On the basis of the personal experience and the previous literature, it has been found that the linkage between the R&D and the sales has not been established. The R&D and the sales are taken as two different department with no linkage at all, in most of the firms. So, the current study will work as a bridge between the two. On the other hand, the current research can also be used by other academic researchers who want to explore the similar area in future. The data and the methodology used in the current research can be used for further study also(DIPP, 2012; Kangogo & Gakure, 2013; Krishnaven & Vidya, 2015).
Aims and Objective of the research
The current research is aimed to examine the impact of R&D on the sales taking into consideration the automobile industry. Apart from this following, the research has following objectives:
The current research is expected to answer the following research question:
What is the impact of R&D on the sales in the Auto mobile industry?
Hypothesis:
Following hypothesis will be tested on the basis of the secondary data:
Null hypothesis (H0): There is no significant impact of R&D on the sales in the automobile industry.
Alternative hypothesis(H1): There is significant impact of R&D on the sales in the automobile industry.
Literature Review
This section of the research has been dedicated to the review of the previous literature in the similar areas. Impact of the R&D on the financial performance of the firms have been one of the most researched topic especially in the manufacturing firms. This is because in the current competitive world, the only way to sustain in the market is to introduce products which are different from its competitors. The product differentiation can only be achieved by investing in the Research and Development.
According to the (Ernst et al., 2010) examined the impact of R&D and other cross functional operations on the sales. Scholars used the multiple-informant 424 sales data and also conducted the interview with the R&D managers. Findings from the study shows that there is no unique conclusion as the different process shows different impact. However authors concluded that the relationship between the sales and R&D is one of the most critical especially in the development stage. Furthermore a study by (VanderPal, 2015) analyzed the relationship between the R&D on the financial performance of the firms. The data of the 103 companies was used for the time period 1979 to 2013. For the financial performance the total revenue, ROA and ROE was used.
The time series regression analysis was used for the analysis purpose and the results shows that the R&D is significantly related to the financial performance of the firms. Another study by (Ba?goze & Sayin, 2013) investigated the relationship between the investment in the R&D and the value of the firm. Authors argued that most of the research in similar area have shown that two variables are positively related.
Using both the multiple and the simple regression models authors investigated the impact of R&D on the financial performance of the firms and the results from the study shows that there is strong and positive relationship between the R&D investment and the firm’s performance. Similarly another study by (Pandit, Wasley, & Zach, 2011) examine the impact of the innovative outputs and R&D on the performance of the firm. In this research authors have also taken into consideration the patents files by the firms as one of the proxy for the research and development.
Findings from the study show that firms which have productive R&D output have less volatile performance in the future. (Usman, Shaique, Khan, & Baig, 2017) examined the relationship between the R&D investment and the performance of the firms located in the developed countries. The previous research have shown that there the R&D investment in the developed countries is higher as compared to the developing countries. Authors used both the firm level and the country level data to examine the relationship. The regression analysis was used to analyze the collected data. Authors found that the R&D investment in the year t, have negative impact on the firm’s performance however it has positive effect on the value of the firm.
The reason behind such findings may be because the investment in the firm lead to higher cost in the initial year. The output of the R&D investments are not instant, so the returns are realized only after some time lag. Another study by (Jaisinghani, 2016) focused on the effect of the R&D investment in the profitability of the firms in the pharma sector. The data for the same was collected from the pharmaceuticals firms in India for the time period between 2005 and 2014.
The generalized methods of moments have been used to analyze the collected data and the results from the analysis show that there exists positive relationship between the R&D investment and the financial performance of the firms. Since pharmaceutical industry is the R&D intensive sector, so the results are as per the expectations. Some of the other authors have also conducted studies on similar areas (Imran, Nisar, & Ashraf, 2014; Kula & Guler2, 2014; Shihab, Soufan, & Abdul-Khaliq, 2014; Stock & McFadden, 2007).
Research methodology
In this section the methodology used in the current research has been discussed. The research methodology is considered to be one of most important section of any research. All the results and the conclusion are based on the analysis techniques used by the researcher to analyze the data. If the appropriate techniques are not used for the analysis, then the findings from the research are not robust and such results cannot be generalized to other areas. The research methodology followed in the current section are based on the similar research conducted before in the similar area, so the techniques used in this research are considered to be suitable for this type of research.
Research method and research strategy
There are different types of the research methodologies which can be used by the researcher to analyze the data and answer the research question. However, all the existing research methods can be categorized in three different types. The first research method is the qualitative research method which are mostly used in those researches where the author want to explore the research area more deeply. The qualitative research method helps to have in-depth analysis about some particular area or topic. The data for the qualitative research is mostly is in the forms of text, image, video, audio etc. For most of the qualitative research the primary data is collected and to collect the data open ended questionnaire is used.
In such type of the questions there is no pre-defined answers to the questions. The questions are same, however the answers for the question can be different from each individuals. The popular method for such data collection is conducting the personal interview or conducting the focused group discussions. Recently the theme based qualitative analysis has become more popular where the entire research is analyzed on the basis of the some themes. The themes for the analysis either be defined prior to the data collection or it can be defined after the data collection based on the responses from the respondents. One of the drawback of the qualitative study is that it does not have any number backed findings so the results can be interpreted in different way. Also it is very difficult to generalize the results(Creswell, 2003; R. Kumar, 2014; Mukaka, 2012).
Another research method is the quantitative method which is another popular method. Unlike the qualitative research, where the data is in non-numerical form, in quantitative research all the data are in numerical form and the researchers the main aim is to use the data and statistical techniques so that the data can be interpreted in meaningful way. There are various statistical techniques which can be used to analyze the quantitative data with the help of different statistical tools. The data for the quantitative analysis can collected through the close ended questionnaire(V. Kumar, Kumar, & Singh, 2013; Teddlie & Yu, 2007; Urrutia, 1995).
Since the current research is aimed to investigate the impact of the R&D investment in the sales of the automobile industry, the quantitative research method has been used. This is because the data collected are in the numerical form and the quantitative research method more appropriate when the impact has to be evaluated.
Data Source
There are mainly two types of data sources. The first is the primary data source where the researcher collect the data themselves on the basis of the requirement of the research. Conducting primary survey or personal interview are the major techniques used to collect the primary data. The second type of data is the secondary data, which is already collected by someone else. Therefore it is sometimes called the second hand data. The major source of secondary data included the books and journals, government data base, annual reports of the company etc.
For the current research the secondary data has been used for the analysis. The data has been collected among the five automobile companies for the time period 2013- 2017. All the data has been collected from the annual report of the respective companies.
Data analysis techniques
To analyze the data various statistical techniques have been used. The first technique is the descriptive statistics which is the basic representation of the collected data. Apart from that the graphical representation of the collected data has also been shown. For the inferential analysis, the correlation and the regression analysis have been performed(Armstrong, 2012; Cerrito, 2010; George, Seals, & Aban, 2014; Monem A Mohammed, 2014; Skrivanek, 2009).
Results and Discussion
In the first section the findings from the descriptive statistics has been presented and the results are shown in the table below.
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R&D |
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Percentiles Smallest |
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1% 67.5 67.5 |
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5% 74.6 74.6 |
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10% 78.7 78.7 Obs 25 |
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25% 495.8 89 Sum of Wgt. 25 |
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50% 754.19 Mean 837.8308 |
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Largest Std. Dev. 604.5917 |
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75% 1037.5 1796.96 |
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90% 1849.06 1849.06 Variance 365531.2 |
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95% 1932.94 1932.94 Skewness .5980173 |
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99% 2011.96 2011.96 Kurtosis 2.403464 |
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Table 1 Descriptive statistics of R&&D investment of the automobile industry
As the table shows the mean investment in the R&D by the automobile firms is 837.83 billion Yen per year. Since the data for each companies was different and most of them have shown the figures on Yen, so the results have been shown in the Yen to keep the unit constant. The standard deviation in this case is 604.59 which indicates higher variation among the automobile companies in terms of R&D investment. The minimum investment is 67.5 billion whereas the largest investment is 2011.96 billion(Pinto & Slevin, 1989; Wang & Ahmed, 2004).
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Sales |
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Percentiles Smallest |
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1% 936 936 |
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5% 1029 1029 |
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10% 1047 1047 Obs 25 |
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25% 5318 1048 Sum of Wgt. 25 |
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50% 6607 Mean 9462 |
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Largest Std. Dev. 16188.08 |
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75% 8972 10217 |
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90% 10297 10297 Variance 2.62e+08 |
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95% 10741 10741 Skewness 4.399437 |
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99% 85654 85654 Kurtosis 21.31674 |
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Table 2 Descriptive statistics of the sales data of the automobile companies
Furthermore the descriptive results for the sales is shown in the table above and the data for the sales have been presented in units per thousand. As per the findings average sales of the automobile for the firms included in the data set is 9462 thousand units. The standard deviation in this case is also high. The positive value of skewness indicates that the data is skewed toward left(Greene, 2003; Koupaie, Ibrahim, & Hosseinkhani, 2013; Urrutia, 1995).
Graphical presentation
In this section the graphical presentation of the variables has been shown and for that purpose the histogram has been used.
The histogram of R&D shows that the variables follows the normal distribution as the most of the variables lies around the mean value and the less data in the tail. The normal distribution line has also been plotted along with the histogram so that the comparison can be made.
Furthermore the histogram of the sales have been shown in the figure above. As it represents, the sales data do not follow normal distribution as most of the sales data either lies to the left of the mean value and some value on the extreme right of the mean value. So, it can be concluded that the sales data do not follow the normal distribution.
Correlation analysis
Another important analysis in the current research is the correlation analysis between the two variables. To graphically show the relation between the investment in R&D and the scatter plot has been plotted.
As the figure shows, there is upward trend in the scatter plot, which indicates that there is positive and strong relationship between the two variables. The correlation coefficient is also shown in the table below.
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| rd sales |
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rd | 1.0000 |
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sales | 0.4509* 1.0000 |
The correlation coefficient value is 0.4509 which is statistically significant at 5 % significance level. Based on the above findings it can be concluded that there is positive and significant relationship between the two variables. Similar results have also been proposed by the previous studies. The impact of R&D on the sales will be clearer from the regression analysis.
Regression analysis
The major findings from the regression model is shown in the table below. The impact of the R&D on the sales have been evaluated by taking the sales as the dependent variable and the R&D investment by the automobile firm as the independent variable. Since the data is the panel data the regression analysis has been performed accordingly. The panel data consist of both the time series and the cross sectional data.
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Random-effects GLS regression Number of obs = 25 |
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Group variable: comp Number of groups = 5 |
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R-sq: Obs per group: |
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within = 0.3016 min = 5 |
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between = 0.9482 avg = 5.0 |
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overall = 0.2033 max = 5 |
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Wald chi2(1) = 5.87 |
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corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0154 |
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sales | Coef. Std. Err. z P>|z| [95% Conf. Interval] |
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rd | 12.07206 4.983356 2.42 0.015 2.304867 21.83926 |
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_cons | -652.3469 5113.395 -0.13 0.898 -10674.42 9369.723 |
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————-+—————————————————————- |
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sigma_u | 0 |
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sigma_e | 12920.408 |
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rho | 0 (fraction of variance due to u_i) |
Table 4 Results from the regression analysis
The regression analysis shows that the overall value of the R squared is 0.2 which implies that only 20 % variation in the sales is being explained by the R&D investment by the automobile companies. One of the reasons for the low value of R squared is may be because there in only one independent variable in the regression model. The F statistics is also significant as the wald Chi square value is significant. Furthermore the regression coefficient of rd is 12.07 which is statistically significant at 5 %. This is because the p value for the coefficient is 0.015 which is less than the 5 %. So, on the basis of the regression results, one can be say that the R&D investment has positive and significant on the sales in the automobile industry.
Hypothesis testing
Null hypothesis: There is no significant impact of R&D on the sales in the automobile industry.
Alternative hypothesis: There is significant impact of R&D on the sales in the automobile industry
As the regression coefficient of R&D is significant and also positive, we can reject the proposed null hypothesis. This implies that we can accept the alternative hypothesis.
Conclusion
The current research was aimed to examine the impact of the R&D investment on the sales in the automobile industry. To analyze the impact the secondary data was collected from the annual report of 5 automobile firms. The time period taken into consideration is from 2013 to 2017. Results from the analysis show that there is positive and strong relationship between the R&D investment and the sales. So, to increase the sales of the automobile products the firms have to invest in the research and development. However it should be noted that the return from the R&D are not immediate in most of the cases.
On the basis of the results following recommendations can be made:
Every research papers have some limitations and the current research is no exception. One of the major limitation of this research is that there is no qualitative analysis conducted which would have provide more detail analysis about the relationship between R&D and the sales. Furthermore the data is only collected among 5 firms which can be increased. In terms of analysis only the regression and correlation analysis has been conducted whereas other analysis such as co-integration could have been tested. Apart from this the monetary and time limitation were there while conducting the research.
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