Assessing the innovation policy implementation effectiveness through clustering: The Russian Federation regions case study

Abstract

Subject. This article discusses the role of cluster analysis in assessing the effectiveness of regional innovation policy implementation. Objectives. The article aims to develop a conceptual approach to assessment of the effectiveness of regional innovation policy implementation through clustering and test it considering the Russian Federation subjects. Methods. For the study, we used the methods of complex rate setting, integral estimation, and cluster analysis (tree-type clustering, k-means). Results. The article proposes a stepwise algorithm for assessing the effectiveness of regional innovation policy implementation, taking into account the relevant methodological and mathematical apparatus. Conclusions and Relevance. The developed algorithm helps create a consolidated model that characterizes the level of effectiveness of innovation policy implementation by the Russian Federation subjects in the context of cluster groups. Subject to improvement and adjustment depending on strategic priorities, the proposed tools can serve as a basis for decision-making on the development of mechanisms for implementing innovation policy at the regional level.