Cluster analysis of the factors influencing innovative development of economy in regions of Russian Federation

• Main Authors: V. N. Yur’ev, D. M. Dybok
• Format: Article
• Language: Russian
• Published: Plekhanov Russian University of Economics 2017-03-01
• Series: Statistika i Èkonomika
• Subjects: innovation; economy of russian federation; regions of russian federation; innovation development; statistical analysis; clusters analysis
• Online Access: https://statecon.rea.ru/jour/article/view/1057

This article provides a statistical description aimed at identifying the factors, which influence on the innovative development in regions of the Russian Federation. Presented article refers to the results of previous research [1, p. 212–218]. On the first stage, there was given a terminology on the concepts of innovations and innovative development, as well as their role in the modern economy was stated. On the next stage, the factors, which may have an influence on the volume of innovative products, activities and services, were chosen. The results received from this article show the cluster analysis of the regions conducted according to three chosen methods. In the course of the research, data was collected from an official web page of Federal State Statistics Service in accordance to previously chosen factors, its’ analysis and conclusions were made, on the current step the cluster analysis was additionally conducted. To analyze the sample rates and to divide regions to the clusters we’ve used a fully integrated line of analytic solutions Statistica [2], for analyzing, visualizing and forecasting. As a result of a statistical analysis and Statistica use regions were divided into clusters according to the three methods: hierarchical classification, Kaverage method and two-input distribution. To make more detailed analysis, linear, power and exponential equations were built for each region. As a result there were drawn two tables: 1) with the Euclidian distances; 2) with the regression models and the meaningful factors. Thereby, regions were grouped. For each group conclusions and recommendations were given. The results of current research will be applicable for analysis and planning of different commercial and governmental market participants.