Assessing the Effectiveness of Innovation Management: Evidence from Russia

The research aims to identify factors related to the innovation sector and influencing the dynamics of gross regional domestic product in Russia. The best practices of the European Union and the USA in implementing innovation policy show the high efficiency of economic clusters, industrial parks, and other innovation infrastructure facilities. More than 25 years ago, the Russian economy adopted the concept of the network (including cluster) structure. Years after, it is important to assess the performance of such objects. The theoretical framework of this research is based on the research of outstanding economists (Acemoglu, Aghion, Kerr, Lundvall, Nanda, Restrepo, and Zeira) who consider technological innovation, including artificial intelligence and robotics, as the main factor of economic growth in the digital age. The authors build regression models to understand innovation’s contribution to economic performance better. The first model is the classical linear regression model. However, the analysis of real statistical data for Russian regions under this model leads to an interesting issue. Indicators that should have a positive effect turn out to be statistically insignificant or interdependent. Therefore, these indicators cannot be included in the model. The second model described is the fuzzy multiple linear regression. It gives more reliable and adequate results than the previous one. The authors believe that the findings have important practical significance, which will make it possible to revise the foundations of innovation policy in Russian regions and develop a number of universal criteria for assessing the effectiveness of innovation management.