{"title":"The relationship of public investments in science and scientometric indicators from the perspective of Croatian universities","authors":"Miroslav Rajter","doi":"10.48188/so.3.4","DOIUrl":null,"url":null,"abstract":"Aim: This study addresses the hypothesis that the invest-ments in science are positively correlated with the indica-tors of productivity and performance of the universities. Methods: A cross-sectional design was used with the datafrom 27 EU countries. The percentage of GDP invested in science in higher education in 2019 and investments ex-pressed as €/inhabitant were used. The criterion variables were total number of publications in Web of Science for 2020; number of publications categorized as article, review or note (ARN); change in the number of publications com-pared to 2016 in total and for Organisation for Economic Co-operation and Development (OECD) research areas; productivity per inhabitant; productivity per researcher; productivity per researcher in higher education system; and number of Academic Ranking of World Universities (ARWU) TOP1000 universities per inhabitant. Descriptive data and Pearson and Spearman correlations were calculat-ed. Additionally, partial Spearman correlations for detailed examinations were used.Results: Most of the productivity indicators were positivelycorrelated to the investment in science. The absolute invest-ment in science in €/inhabitant is more important than in-vestment expressed as the percentage of GDP. Unexpectedly, the correlations between investments and the growth rate in productivity were negative indicating that the less devel-oped countries have achieved a larger growth in productiv-ity in the examined 5-year period. Conclusion: The results indicate that the investments inscience as the percentage of GDP is important, but the ab-solute amount of money also has an important role in the prediction of scientific productivity. However, since the absolute amount of investments is limited in the less developed countries, they should be more focused on buildingthe strategies that capitalize on specific strengths and potentials. This further accentuates the need for science policychange in Croatia with the strategic focus on aligning the re-sources to the expected results.","PeriodicalId":422483,"journal":{"name":"St open","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"St open","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48188/so.3.4","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
Aim: This study addresses the hypothesis that the invest-ments in science are positively correlated with the indica-tors of productivity and performance of the universities. Methods: A cross-sectional design was used with the datafrom 27 EU countries. The percentage of GDP invested in science in higher education in 2019 and investments ex-pressed as €/inhabitant were used. The criterion variables were total number of publications in Web of Science for 2020; number of publications categorized as article, review or note (ARN); change in the number of publications com-pared to 2016 in total and for Organisation for Economic Co-operation and Development (OECD) research areas; productivity per inhabitant; productivity per researcher; productivity per researcher in higher education system; and number of Academic Ranking of World Universities (ARWU) TOP1000 universities per inhabitant. Descriptive data and Pearson and Spearman correlations were calculat-ed. Additionally, partial Spearman correlations for detailed examinations were used.Results: Most of the productivity indicators were positivelycorrelated to the investment in science. The absolute invest-ment in science in €/inhabitant is more important than in-vestment expressed as the percentage of GDP. Unexpectedly, the correlations between investments and the growth rate in productivity were negative indicating that the less devel-oped countries have achieved a larger growth in productiv-ity in the examined 5-year period. Conclusion: The results indicate that the investments inscience as the percentage of GDP is important, but the ab-solute amount of money also has an important role in the prediction of scientific productivity. However, since the absolute amount of investments is limited in the less developed countries, they should be more focused on buildingthe strategies that capitalize on specific strengths and potentials. This further accentuates the need for science policychange in Croatia with the strategic focus on aligning the re-sources to the expected results.
目的:本研究提出了科学投入与高校生产力和绩效指标正相关的假设。方法:采用横断面设计,数据来自27个欧盟国家。使用了2019年高等教育科学投资占GDP的百分比和以欧元/居民表示的投资。标准变量为2020年Web of Science的总发表数;被分类为文章、评论或注释(ARN)的出版物数量;与2016年相比,经济合作与发展组织(OECD)研究领域的出版物数量变化;人均生产力;人均生产力;高等教育系统研究人员人均生产力;世界大学学术排名(ARWU)前1000所大学的人均数量。计算描述性数据以及Pearson和Spearman相关性。此外,对详细检查使用了部分Spearman相关。结果:大部分生产率指标与科技投入呈正相关。以欧元/居民为单位的绝对科学投资比以GDP百分比表示的投资更重要。出乎意料的是,投资和生产率增长率之间的相互关系是负相关的,这表明较不发达国家在审查的五年期间实现了较大的生产率增长。结论:研究结果表明,科技投入占GDP的比重很重要,但绝对投入对科技生产力的预测也有重要作用。然而,由于投资的绝对数量在欠发达国家是有限的,他们应该更专注于建立利用特定优势和潜力的战略。这进一步强调了克罗地亚改变科学政策的必要性,其战略重点是使资源与预期结果保持一致。