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How to use indicators to measure scientific performance: a balanced approach

Author

Listed:
  • Ulrich Schmoch
  • Torben Schubert
  • Dorothea Jansen
  • Richard Heidler
  • Regina von Görtz

Abstract

Scientific performance should not be measured by a one-dimensional metric such as publication, since it is a multi-dimensional phenomenon. A quantitative analysis of the activities of research groups in three scientific fields demonstrates in particular the importance of sufficient numbers of PhD graduates and of contributions to the infrastructure of the scientific community, in terms of editorships or memberships of boards, etc. The results of a quantitative analysis are largely confirmed by a parallel qualitative investigation; however, both approaches complement each other by highlighting different aspects. For example, the qualitative approach conveys explicitly the demand structure for intermediary and final outputs in the qualitative approach that interlinks the activities of different research units. The results show that it is important for science policy to set appropriate incentives for all dimensions of scientific activities, i.e. not publication output exclusively, as this entails considerable hazard of distortion, endangering the sustainability of scientific research. Copyright , Beech Tree Publishing.

Suggested Citation

  • Ulrich Schmoch & Torben Schubert & Dorothea Jansen & Richard Heidler & Regina von Görtz, 2010. "How to use indicators to measure scientific performance: a balanced approach," Research Evaluation, Oxford University Press, vol. 19(1), pages 2-18, March.
    • Handle: RePEc:oup:rseval:v:19:y:2010:i:1:p:2-18
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    Cited by:

    1. Liao, Hongjing & Hitchcock, John, 2018. "Reported credibility techniques in higher education evaluation studies that use qualitative methods: A research synthesis," Evaluation and Program Planning, Elsevier, vol. 68(C), pages 157-165.
    2. Torben Schubert, 2014. "Are there scale economies in scientific production? On the topic of locally increasing returns to scale," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 393-408, May.
    3. Corey J A Bradshaw & Justin M Chalker & Stefani A Crabtree & Bart A Eijkelkamp & John A Long & Justine R Smith & Kate Trinajstic & Vera Weisbecker, 2021. "A fairer way to compare researchers at any career stage and in any discipline using open-access citation data," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-15, September.
    4. Katarina Rojko & Brankica Bratić & Borut Lužar, 2020. "The Bologna reform’s impacts on the scientific publication performance of Ph.D. graduates—the case of Slovenia," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 329-356, July.
    5. Nabil Amara & Réjean Landry, 2012. "Counting citations in the field of business and management: why use Google Scholar rather than the Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 553-581, December.
    6. Fiorenzo Franceschini & Elisa Turina, 2013. "Quality improvement and redesign of performance measurement systems: an application to the academic field," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 465-483, January.
    7. Akshaya Kumar Biswal, 2013. "An Absolute Index (Ab-index) to Measure a Researcher’s Useful Contributions and Productivity," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-10, December.
    8. Irwin Feller, 2013. "Performance measures as forms of evidence for science and technology policy decisions," The Journal of Technology Transfer, Springer, vol. 38(5), pages 565-576, October.
    9. Tasso Brandt & Torben Schubert, 2014. "Is the university model an organizational necessity? Scale and agglomeration effects in science," Chapters, in: Andrea Bonaccorsi (ed.), Knowledge, Diversity and Performance in European Higher Education, chapter 8, pages iii-iii, Edward Elgar Publishing.
    10. Sandro Mendonça & João Pereira & Manuel Ennes Ferreira, 2018. "Gatekeeping African studies: what does “editormetrics” indicate about journal governance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1513-1534, December.
    11. Antonio Fernández-Cano & Manuel Torralbo & Mónica Vallejo, 2012. "Time series of scientific growth in Spanish doctoral theses (1848–2009)," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 15-36, April.
    12. Tasso Brandt & Torben Schubert, 2013. "Is the university model an organizational necessity? Scale and agglomeration effects in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(2), pages 541-565, February.
    13. Yagi, Michiyuki & Managi, Shunsuke, 2018. "Shadow price of patent stock as knowledge stock: Time and country heterogeneity," Economic Analysis and Policy, Elsevier, vol. 60(C), pages 43-61.
    14. Gibson, Elizabeth & Daim, Tugrul U. & Dabic, Marina, 2019. "Evaluating university industry collaborative research centers," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 181-202.
    15. Laura Graf & Wiebke S. Wendler & Jutta Stumpf-Wollersheim & Isabell M. Welpe, 2019. "Wanting More, Getting Less: Gaming Performance Measurement as a Form of Deviant Workplace Behavior," Journal of Business Ethics, Springer, vol. 157(3), pages 753-773, July.
    16. Kroll, Henning & Schubert, Torben, 2014. "On universities' long-term effects on regional value creation and unemployment: The case of Germany," Working Papers "Firms and Region" R1/2014, Fraunhofer Institute for Systems and Innovation Research (ISI).
    17. Franc Mali, 2013. "Why an Unbiased External R&D Evaluation System is Important for the Progress of Social Sciences—the Case of a Small Social Science Community," Social Sciences, MDPI, vol. 2(4), pages 1-14, December.
    18. Torben Schubert & Henning Kroll, 2016. "Universities’ effects on regional GDP and unemployment: The case of Germany," Papers in Regional Science, Wiley Blackwell, vol. 95(3), pages 467-489, August.
    19. Schubert , Torben, 2013. "Are there Scale Economies in Scientific Production? On the Topic of Locally Increasing Returns to Scale," Papers in Innovation Studies 2013/43, Lund University, CIRCLE - Centre for Innovation Research.
    20. Torben Schubert & Andrea Bonaccorsi & Tasso Brandt & Daniela De Filippo & Benedetto Lepori & Andreas Niederl, 2014. "Is there a European university model? New evidence on national path dependence and structural convergence," Chapters, in: Andrea Bonaccorsi (ed.), Knowledge, Diversity and Performance in European Higher Education, chapter 2, pages iii-iii, Edward Elgar Publishing.

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