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Research: metrics, quality, and management implications

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  • Peter Andras

Abstract

Research evaluation is increasingly important in management decisions in universities. Research metrics provide an objective way to assess the research output of individuals, groups, departments and universities. Such metrics work well as quality assessment tools in the case of normal science research in mature sciences, and also in the case of early stage sciences containing a significant amount of research that is meant to be revolutionary. Revolutionary research in mature sciences and unfashionable revolutionary research in early stage sciences remain mostly invisible to research metrics in the short term. This kind of research may become measurable in the long term if it turns out to be successful and generates a large volume of follow-on research that becomes part of normal science. Pursuing revolutionary research is risky, and this risk is modulated by the availability of an appropriate research workforce and the funding environment. Hype and spin are part of the mechanisms of scientific public opinion, and dealing with these is important in the context of management decisions based on research metrics. Copyright , Beech Tree Publishing.

Suggested Citation

  • Peter Andras, 2011. "Research: metrics, quality, and management implications," Research Evaluation, Oxford University Press, vol. 20(2), pages 90-106, June.
    • Handle: RePEc:oup:rseval:v:20:y:2011:i:2:p:90-106
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    File URL: http://hdl.handle.net/10.3152/095820211X12941371876265
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    Cited by:

    1. Guillermo Armando Ronda-Pupo, 2020. "The performance of Latin American research on economics & business," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 573-590, January.
    2. Tijssen, Robert J.W., 2018. "Anatomy of use-inspired researchers: From Pasteur’s Quadrant to Pasteur’s Cube model," Research Policy, Elsevier, vol. 47(9), pages 1626-1638.
    3. Alonso Rodríguez-Navarro & Francis Narin, 2018. "European Paradox or Delusion—Are European Science and Economy Outdated?," Science and Public Policy, Oxford University Press, vol. 45(1), pages 14-23.
    4. Rodríguez-Navarro, Alonso & Brito, Ricardo, 2018. "Double rank analysis for research assessment," Journal of Informetrics, Elsevier, vol. 12(1), pages 31-41.
    5. Jesus Palomo & Cristina Figueroa-Domecq & Pilar Laguna, 2017. "Women, peace and security state-of-art: a bibliometric analysis in social sciences based on SCOPUS database," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 123-148, October.
    6. Manganote, Edmilson J.T. & Araujo, Mariana S. & Schulz, Peter A., 2014. "Visualization of ranking data: Geographical signatures in international collaboration, leadership and research impact," Journal of Informetrics, Elsevier, vol. 8(3), pages 642-649.
    7. Elizabeth Troncoso & Francisco Ganga-Contreras & Margarita Briceño, 2022. "Incentive Policies for Scientific Publications in the State Universities of Chile," Publications, MDPI, vol. 10(2), pages 1-19, June.
    8. Alis Oancea, 2019. "Research governance and the future(s) of research assessment," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-12, December.

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