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КЛАСТЕРНЫЙ АНАЛИЗ ФАКТОРОВ, ВЛИЯЮЩИХ НА ИННОВАЦИОННОЕ РАЗВИТИЕ ЭКОНОМИКИ В РЕГИОНАХ РОССИЙСКОЙ ФЕДЕРАЦИИ

КЛАСТЕРНЫЙ АНАЛИЗ ФАКТОРОВ, ВЛИЯЮЩИХ НА ИННОВАЦИОННОЕ РАЗВИТИЕ ЭКОНОМИКИ В РЕГИОНАХ РОССИЙСКОЙ ФЕДЕРАЦИИ

Abstract

В статье описывается статистическое исследование, направленное на выявление факторов, которые влияют на инновационное развитие экономики Российской Федерации. Данная статья основывается на результатах, полученных на предыдущих этапах изучения эффективности внедрения инноваций [1, с. 212–218]. На первом этапе было дано определение понятия инноваций, инновационного прогресса, а также отмечена их роль в современной экономике. На следующем этапе выбраны факторы, которые могут иметь влияние на объем инновационных товаров, работ и услуг в стране. В ходе работы собраны данные с официального сайта Федеральной службы статистики, сделан выбор предполагаемых факторов влияния, произведен анализ их значимости с аналитическими выводами. Выводы и рекомендации, представленные в данной работе, отражают результаты кластерного анализа регионов по интенсивности внедрения инноваций. Для изучения показателей выборки, а также для разбиения регионов на кластеры использовано программное обеспечение ППП Statistica [2]. В результате выполнения статистического анализа и работы с данными регионы разделены на кластеры согласно трем методам: иерархической классификации, методу К-средних и двухвходовому распределению. Для получения более детальных выводов и рекомендаций для всех регионов РФ были построены регрессионные модели: линейная, степенная и экспоненциальная. В результате исследования составлены две таблицы регионов: таблица, состоящая из евклидовых расстояний между регионами, и таблица, состоящая из регрессионных моделей и значимых факторов. Таким образом, регионы сгруппированы согласно схожим характеристикам и расстояниям. Для каждой группы регионов сделаны отдельные выводы и даны рекомендации. Результаты исследования будут полезны для анализа и планирования инвестиций различными государственными органами федерального и регионального уровней, а также частными инвесторами.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.

Keywords

INNOVATION,ECONOMY OF RUSSIAN FEDERATION,REGIONS OF RUSSIAN FEDERATION,INNOVATION DEVELOPMENT,STATISTICAL ANALYSIS,CLUSTERS ANALYSIS,ИННОВАЦИИ,ЭКОНОМИКА РОССИЙСКОЙ ФЕДЕРАЦИИ,РЕГИОНЫ РОССИЙСКОЙ ФЕДЕРАЦИИ,ИННОВАЦИОННОЕ РАЗВИТИЕ,СТАТИСТИЧЕСКИЙ АНАЛИЗ,КЛАСТЕРНЫЙ АНАЛИЗ

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average