Business & Management Studies: An International Journal
Yazarlar: Musa GÜN, Ceyda YERDELEN KAYGIN
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Özet: 1. LITERATURE 1.1. RESEARCH SUBJECT Research and Development (R&D) activities can contribute to reveal the creativity and innovation. The changes occur in this way. These activities help businesses gain competitive advantage, achieve sustainable growth, and play an essential role in the success of their financial performance. Many studies in the literature analyse the effects of R&D expenditures on the financial performance of businesses. Bae and Kim (2003), Ehie and Olibe (2010), Pandit, Wasley and Zach (2011), Çiçek and Onat (2013), Ayaydın and Karaaslan (2014), VanderPal (2015), Freihat and Kanakriyah (2017), Çıtak and İltaş (2017), Huang et al. (2018), Zang, Zhu and Guerrero (2019) found out that R&D investments have positive effects on the financial performance of the companies. Lantz and Sahut (2005) concluded in their study that R&D expenses significantly reduce the financial performance of the companies. On the other hand, Arslantürk (2010), Kiracı and Arsoy (2014) argued that there is no relationship between R&D expenditures and financial performance of the companies. 1.2. RESEARCH PURPOSE AND IMPORTANCE This study aimed to analyse the effects of R&D investments. In this direction, 18 firms with the highest R&D intensity traded in 9 different sectors in the BIST ALL index between 2010 and 2019 were analysed through Data Envelopment Analysis. The study provides the opportunity to evaluate R&D and financial performance for the company executives, investors and all other stakeholders in the market. 1.3. CONTRIBUTION of the ARTICLE to the LITERATURE When the literature is reviewed, it has been observed that generally a single sector or index is analysed in the researches on the R&D and financial performance. However, the market is a whole, and many sectors are included in this market. Therefore, this research, which allows the comparison of different sectors, differ from other studies. 2. DESIGN AND METHOD 2.1. RESEARCH TYPE This study is a research article, and quantitative research design was adopted in the study. 2.2. RESEARCH PROBLEMS In this study, the authors tried to find out the effects of R&D investment on the financial performance of the companies. 2.3. DATA COLLECTION METHOD The data within the scope of the study were obtained from the Finnet database and the Public Disclosure Platform (KAP). 2.4. QUANTITATIVE / QUALITATIVE ANALYSIS In the study, a quantitative analysis was performed. Data Envelopment Analysis (DEA) method was used in the research. The BCC model assuming a variable return to scale developed by Banker, Charnes and Cooper (1984) was preferred. 3. FINDINGS AND DISCUSSION 3.1. FINDINGS as a RESULT of ANALYSIS In this study, efficiency scores, proportional reduction or augmentation amounts of inefficient firms, the benchmark firms, and the reference weights to which the inefficient firms need to catch up to become efficient were examined within the scope of DEA findings based on input-oriented BCC model. As a result of the analysis, it is found out that GENTS and KOZAA are the firms that use their resources efficiently, in other words, these firms can deploy the input composition to produce a particular output composition most efficiently. The efficiency scores for these firms were calculated as 1 in all review period. The average efficiency score calculated by considering all the firms within the scope of the sample was at the level of 0.80. The efficiency score closer to 1 is an indication of an increase in the firms’ productivity. The OTKAR is the firm with the lowest efficiency score of an average 0.32 level by years. The firm LOGO takes second place with an average efficiency score of 0.37. On the other hand, the ULKER, KUTPO, CEMTS, and IPEKE firms are also among the firms that have full efficiency scores in all years except for one or two years. Proportional reduction or augmentation amounts according to the efficiency scores obtained by data envelopment analysis show the amount of change in percentage that the inefficient firms need to make in the input and output variables to become efficient. These amounts were not calculated for the GENTS and KOZAA firms since they were efficient in all years. There is an inverse relationship between efficiency scores and proportional amounts. As the efficiency level of the firm increases, the proportional amounts that should be made in the variables decrease naturally. For instance; the amount of reduction that OTKAR firm which has the lowest efficiency score of 0.32 should make in R&D intensity is 69% to become an efficient firm, whereas the amount of reduction that IPEKE firm which has a higher efficiency score of 0.92 should make in R&D intensity is just 8%. The average proportional reduction percentage to be made in R&D intensity was calculated as 43%. When all firms are evaluated together, it is understood that the firms that need to make the highest reduction amount in the R&D intensity are in the I.T. sector with an average of 74%. It is followed by the EMKEL and OTKAR firms, which are in the index of metal goods, machinery, electrical devices, and vehicles. The average reduction amount that these firms should make in the R&D intensity was calculated as 64%. Subsequently, DYOBY and MRSHL firms operating in the chemical, pharmaceutical, petroleum, rubber, and the plastic sector take the third rank with an average of 55% reduction rate. 4. CONCLUSION, RECOMMENDATION AND LIMITATIONS 4.1. RESULTS of the ARTICLE The result of the study shows that there is a positive correlation between the R&D intensity and the net sales, asset profitability and equity profitability of the firms. In the study, the R&D intensity was calculated as 4.1% on average for all sectors and periods. On the other hand, it is seen that the I.T. sector, with an average R&D intensity of 26.1% differs significantly from other sectors. The fact that the efficiency score approaches 1 is an indication of the increase in firms’ efficiency. In this regard, the firms that used their resources efficiently for the analysis period and showed full efficiency in all years are the GENTS firm, which is operating in the forest products and furniture industry, and the KOZAA firms, which is operating in the mining industry. The average efficiency score was calculated at the level of 0.80 in the analysis period by considering all firms. The percentage of reduction that the inefficient firms need to make in R&D intensity to become efficient firms has been calculated as 43% on average. Due to the high level of R&D expenditures in the I.T. sector, the firms in this sector should make an average of 74% reduction in the R&D intensity to achieve efficiency. The firms that need to make the lowest reduction in the R&D intensity were identified as the IPEKE and ULKER firms with 8% and 10% rates respectively. According to the findings of the benchmark firms and their reference weights, which present the efficient firms be set as a model for inefficient firms, the inefficient firms should generally imitate the GENTS firm, which operates in the forest products and furniture sector, and the CEMTS firm, which operates in the metal industry. 4.2. SUGGESTIONS BASED on RESULTS The percentage of reduction that the inefficient firms need to make in R&D intensity to become efficient firms has been calculated as 43% on average. Due to the high level of R&D expenditures in the I.T. sector, the firms in this sector should make an average of 74% reduction in the R&D intensity to achieve efficiency. For future studies, analysing the relationship between R&D expenditures and the performance indicators mainly covering different sectors and multiple periods rather than a single sector or period through various methods except data envelopment analysis may be the subject of research. 4.3. LIMITATIONS of the ARTICLE Financial institutions were excluded from the sample selection. The companies included in the analysis are those that are traded in Borsa Istanbul without interruption during the review period, have full access to their data and R&D expenditure. Also, these companies selected from different sectors are those with the highest R&D intensity.