{"title":"Growth zones of the national innovation system of Russia","authors":"Dmitry Serpuhovitin","doi":"10.56199/dpcsebm.tdao4707","DOIUrl":null,"url":null,"abstract":"The article presents the original algorithmic model for identification of growth zones of the national innovation system that maximize the effect of government support. The model is based on numerical comparison of values of indicators of gross domestic product, the human development index and the integral value of the global innovation index, and also its subindicators characterizing government support of national innovation system in each of the countries under consideration. The model compares these indicators for about 180 countries aggregated from 2013 to 2019 and identifies sectors of the national innovation system, stimulation of which gives the highest contribution to growth of the integral indicator of the global innovation index. For the Russian Federation with the use of the model the spheres of potential economic growth in the national innovation system were determined and ranked according to the dynamics. The growth zones of the national innovation system of Russia identified by the model are generally consistent, on the one hand, with the internal policy pursued by the government, and on the other hand, with the peculiarities of the country’s historical path.","PeriodicalId":281515,"journal":{"name":"Human resource management within the framework of realisation of national development goals and strategic objectives","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human resource management within the framework of realisation of national development goals and strategic objectives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56199/dpcsebm.tdao4707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article presents the original algorithmic model for identification of growth zones of the national innovation system that maximize the effect of government support. The model is based on numerical comparison of values of indicators of gross domestic product, the human development index and the integral value of the global innovation index, and also its subindicators characterizing government support of national innovation system in each of the countries under consideration. The model compares these indicators for about 180 countries aggregated from 2013 to 2019 and identifies sectors of the national innovation system, stimulation of which gives the highest contribution to growth of the integral indicator of the global innovation index. For the Russian Federation with the use of the model the spheres of potential economic growth in the national innovation system were determined and ranked according to the dynamics. The growth zones of the national innovation system of Russia identified by the model are generally consistent, on the one hand, with the internal policy pursued by the government, and on the other hand, with the peculiarities of the country’s historical path.