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dc.contributor.authorNiembro, Andrés Alberto-
dc.contributor.authorStarobinsky, Gabriela-
dc.date.accessioned2023-11-02T14:25:57Z-
dc.date.available2023-11-02T14:25:57Z-
dc.date.issued2023-
dc.identifier.citationNiembro, A. y Starobinsky, G. (2023). “Looking at regional innovation systems and industrial knowledge bases from the South: An analysis of Argentine provinces”. International Journal of Technological Learning, Innovation and Development, Vol. 15, No. 1. DOI: 10.1504/IJTLID.2023.10053951es_ES
dc.identifier.issn1753-1950es_ES
dc.identifier.urihttp://rid.unrn.edu.ar/handle/20.500.12049/10955-
dc.description.abstractStudies on regional innovation systems and, particularly, on differentiated knowledge bases are still highly concentrated in Europe. This article presents some original methodologies for adapting these approaches to peripheral countries and regions. Principal component analysis is used to construct two indexes that distinguish the degree of socio-economic development of Argentine provinces and their innovation systems development. The latest innovation survey and cluster analysis techniques are used to identify the predominant knowledge base among industries and then the regional productive specialisation. The results show a relationship between all these dimensions, especially in two large groups of provinces: one of peripheral innovation systems, specialized in symbolic sectors, with low socio-economic development; and the other of core-intermediate systems, with an analytical-synthetic combination and medium-high development. In Argentina, as in many developing countries, narrow and spatially blind innovation policies, dissociated from regional capabilities and production structures, usually reproduce regional inequalities and reinforce peripheral conditions.es_ES
dc.format.extentp. 1-27es_ES
dc.language.isoenes_ES
dc.publisherInderScience Onlinees_ES
dc.relation.urihttps://www.inderscienceonline.com/es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/-
dc.titleLooking at regional innovation systems and industrial knowledge bases from the South: An analysis of Argentine provinceses_ES
dc.typeArticuloes_ES
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)-
dc.description.filiationNiembro, Andrés Alberto. Universidad Nacional de Río Negro. Instituto de Estudios en Ciencia, Tecnología, Cultura y Desarrollo (CITECDE). Río Negro; Argentina.es_ES
dc.description.filiationStarobinsky, Gabriela. Universidad Nacional de Chilecito. La Rioja; Argentina.es_ES
dc.subject.keywordregional innovation systemses_ES
dc.subject.keywordknowledge baseses_ES
dc.subject.keywordregional inequalitieses_ES
dc.subject.keywordperipheral regionses_ES
dc.type.versioninfo:eu-repo/semantics/acceptedVersiones_ES
dc.subject.materiaEconomía y Contabilidades_ES
dc.origin.lugarDesarrolloUniversidad Nacional de Río Negroes_ES
dc.relation.journalissue15 (1)es_ES
dc.description.reviewtruees_ES
dc.description.resumenStudies on regional innovation systems and, particularly, on differentiated knowledge bases are still highly concentrated in Europe. This article presents some original methodologies for adapting these approaches to peripheral countries and regions. Principal component analysis is used to construct two indexes that distinguish the degree of socio-economic development of Argentine provinces and their innovation systems development. The latest innovation survey and cluster analysis techniques are used to identify the predominant knowledge base among industries and then the regional productive specialisation. The results show a relationship between all these dimensions, especially in two large groups of provinces: one of peripheral innovation systems, specialized in symbolic sectors, with low socio-economic development; and the other of core-intermediate systems, with an analytical-synthetic combination and medium-high development. In Argentina, as in many developing countries, narrow and spatially blind innovation policies, dissociated from regional capabilities and production structures, usually reproduce regional inequalities and reinforce peripheral conditions.es_ES
dc.identifier.doihttps://doi.org/10.1504/IJTLID.2023.132867-
dc.relation.journalTitleInternational Journal of Technological Learning, Innovation and Developmentes_ES
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