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The aim of this study is to assess the impact of R&D spending on innovation and productivity growth of Russian high-tech firms. Our research is based on BEEPS data for 2012-2014 for Russian firms, extended by the regional integral index of innovative development. We employ a modified CDM model, which consists of three stages linking R&D spending, innovation, and productivity growth. At each stage, we consider both internal and external factors important for R&D, innovation, and productivity. Our research expands the existing literature, first, by analyzing the R&D spending-productivity link in Russian high-tech firms based on BEEPS data. Second, at the last stage of the model, we study the firm-level productivity change over three years, which allows us to consider the dynamics of the key indicator of firms’ performance and to capture the impact of innovation on this dynamics, in contrast to the original model with static productivity level. The results show the positive impact of import and share of the firm owned by private foreign individuals on R&D spending of high-tech firms. R&D expenditures are found to have a significant positive effect on innovative sales. Additionally, the indicator of favorable regional innovative conditions and cooperation have a significant positive effect on firms’ innovation activity. Employee training was found to be especially important for innovative sales of high-tech firms. Besides, our model confirms that barriers to business operation affect R&D investment. Finally, the effect of innovative sales on productivity growth is not significant for high-tech firms. This may indicate weak competitiveness and high cost of innovation faced by the Russian high-tech firms. The results provide a background for policy recommendations. In particular, we suggest that attention should be paid to development of a business environment favorable for innovations, cooperation and international economic activity. [ABSTRACT FROM AUTHOR]

The efficient and effective inventory management goes a long way in the successful running and survival of an industry. In the present paper, the authors studied the existing inventory control system of an industry manufacturing gear wheels. The various types of gear wheels are made from the S45C material round bar. These gear wheels are manufacturing by various cutting inserts. The ABC analysis was performed to identify the A class inserts. Subsequently, the linear programming technique was used to establish the relationship between the consumption of A-class inserts and the production quantity of gear wheels. This relationship was used to determine the requirement of inserts for the future production quantity. The EOQ, re-order level, safety stock and total insert's inventory cost were determined for future production. The linear programming based inventory model reduced the 24-27% inventory cost as compared to the existing inventory model. [ABSTRACT FROM AUTHOR]