{"title":"REGIONAL COMPETITIVENESS RESPONSE TO INNOVATION CHANGES: ISSUES OF EVALUATION","authors":"A. Polyakova, V. Kolmakov, O. Yamova","doi":"10.37043/jura.2019.11.2.3","DOIUrl":null,"url":null,"abstract":"Our research addresses regional competitiveness as the function of innovation activity. We use 15 indicators to cluster the Russian regions in five different groups, and to propose and to estimate the composite competitiveness quotient of a region in order to further regress it by innovation activity indicators. We prove that different groups of regions – “potential competitiveness leaders”, “traditional competitiveness factor employers”, “competitiveness outsiders”, “moderate competitiveness regions”, “competitiveness leaders” – are prone to respond to innovation parameters change in a different manner, thus uniform regulation and strategies are irrelevant. We contribute to the methodology of regional competitiveness estimation by presenting a ready-to-deploy set of data structures and model propositions. Our measure of competitiveness is economy related and easily adjustable regarding the specific innovation phenomena that influence the corporate and aggregate performance, value or efficiency of regions.","PeriodicalId":54010,"journal":{"name":"Journal of Urban and Regional Analysis","volume":"1 1","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2019-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Urban and Regional Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37043/jura.2019.11.2.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 7
Abstract
Our research addresses regional competitiveness as the function of innovation activity. We use 15 indicators to cluster the Russian regions in five different groups, and to propose and to estimate the composite competitiveness quotient of a region in order to further regress it by innovation activity indicators. We prove that different groups of regions – “potential competitiveness leaders”, “traditional competitiveness factor employers”, “competitiveness outsiders”, “moderate competitiveness regions”, “competitiveness leaders” – are prone to respond to innovation parameters change in a different manner, thus uniform regulation and strategies are irrelevant. We contribute to the methodology of regional competitiveness estimation by presenting a ready-to-deploy set of data structures and model propositions. Our measure of competitiveness is economy related and easily adjustable regarding the specific innovation phenomena that influence the corporate and aggregate performance, value or efficiency of regions.