Scientific activity evaluation in Cuban universities: Analysis based on Scival (2011-2021)

Objective. The study aims to analyze indicators of production, collaboration, visibility, impact, and innovation of Cuban universities through Scival during the period 2012-2021. Design/Methodology/Approach. The study design is non-experimental (cross-sectional) and quantitative (descriptive). Eleve...

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Veröffentlicht in:Iberoamerican Journal of Science Measurement and Communication (Online) 2022-03, Vol.2 (1)
Hauptverfasser: Peralta-González, María Josefa, Gregorio-Chaviano, Orlando
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container_title Iberoamerican Journal of Science Measurement and Communication (Online)
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creator Peralta-González, María Josefa
Gregorio-Chaviano, Orlando
description Objective. The study aims to analyze indicators of production, collaboration, visibility, impact, and innovation of Cuban universities through Scival during the period 2012-2021. Design/Methodology/Approach. The study design is non-experimental (cross-sectional) and quantitative (descriptive). Eleven Cuban universities were identified in Scival. The indicators were delimited in a time window of 10 years (2012-2021). We analized the results based on 21 indicators covering scientific output, thematic categories, collaboration, visibility, and scientific and patent impact. Results/Discussion. 59.7% of the scientific output is produced by the University of Havana (UH) and the Central University of Las Villas (UCLV). There is a high specialization in engineering and computational sciences. Basic sciences such as mathematics, chemistry and physics are highlighted. 62.1% of the scientific output has been cited. The works’ distribution by journals’ quartiles revealed that 47.3% of the production had been published in 50% of the top Scopus journals during the last ten years. Low performance in innovation and social impact through patents was evidenced. Only UH and UCLV are highlighted. Conclusions. Scival is highly useful for conducting more effective institutional scientific production studies and establishing comparisons of multiple indicators. The biases offered by the tool are minimized, thus offering reliable information for decision-making. The study revealed essential data on Cuban universities' scientific output in Scopus in the last ten years. This is useful for science managers, decision-makers, researchers, and publishers. Originality/Value. The study is novel given that there is a lack of antecedents of Cuban studies using Scival to analyze the universities’ performance. An update on the status of scientific output, visibility and impact is provided.
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The study aims to analyze indicators of production, collaboration, visibility, impact, and innovation of Cuban universities through Scival during the period 2012-2021. Design/Methodology/Approach. The study design is non-experimental (cross-sectional) and quantitative (descriptive). Eleven Cuban universities were identified in Scival. The indicators were delimited in a time window of 10 years (2012-2021). We analized the results based on 21 indicators covering scientific output, thematic categories, collaboration, visibility, and scientific and patent impact. Results/Discussion. 59.7% of the scientific output is produced by the University of Havana (UH) and the Central University of Las Villas (UCLV). There is a high specialization in engineering and computational sciences. Basic sciences such as mathematics, chemistry and physics are highlighted. 62.1% of the scientific output has been cited. The works’ distribution by journals’ quartiles revealed that 47.3% of the production had been published in 50% of the top Scopus journals during the last ten years. Low performance in innovation and social impact through patents was evidenced. Only UH and UCLV are highlighted. Conclusions. Scival is highly useful for conducting more effective institutional scientific production studies and establishing comparisons of multiple indicators. The biases offered by the tool are minimized, thus offering reliable information for decision-making. The study revealed essential data on Cuban universities' scientific output in Scopus in the last ten years. This is useful for science managers, decision-makers, researchers, and publishers. Originality/Value. The study is novel given that there is a lack of antecedents of Cuban studies using Scival to analyze the universities’ performance. 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The study aims to analyze indicators of production, collaboration, visibility, impact, and innovation of Cuban universities through Scival during the period 2012-2021. Design/Methodology/Approach. The study design is non-experimental (cross-sectional) and quantitative (descriptive). Eleven Cuban universities were identified in Scival. The indicators were delimited in a time window of 10 years (2012-2021). We analized the results based on 21 indicators covering scientific output, thematic categories, collaboration, visibility, and scientific and patent impact. Results/Discussion. 59.7% of the scientific output is produced by the University of Havana (UH) and the Central University of Las Villas (UCLV). There is a high specialization in engineering and computational sciences. Basic sciences such as mathematics, chemistry and physics are highlighted. 62.1% of the scientific output has been cited. The works’ distribution by journals’ quartiles revealed that 47.3% of the production had been published in 50% of the top Scopus journals during the last ten years. Low performance in innovation and social impact through patents was evidenced. Only UH and UCLV are highlighted. Conclusions. Scival is highly useful for conducting more effective institutional scientific production studies and establishing comparisons of multiple indicators. The biases offered by the tool are minimized, thus offering reliable information for decision-making. The study revealed essential data on Cuban universities' scientific output in Scopus in the last ten years. This is useful for science managers, decision-makers, researchers, and publishers. Originality/Value. The study is novel given that there is a lack of antecedents of Cuban studies using Scival to analyze the universities’ performance. 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