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Methodologies for the analysis of research funding and expenditure: from input to positioning indicators

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  • Benedetto Lepori

Abstract

This paper discusses the status of indicators concerning research funding and expenditure and proposes some pathways for further developments. First, I discuss in depth the design of the R&D statistics based on the Frascati manual and its limitations concerning analytical categories, data availability and quality. Further I argue that, to answer to specific policy questions concerning the allocation of funds, the development of a new generation of indicators is needed — so-called positioning indicators — focusing on the analysis of financial fluxes between research funders, intermediaries and performers, and I present some recent results of comparative European work in this direction. Finally, I draw some general methodological lessons on the nature of these indicators and on the procedure for their production, discussing key aspects such as reproducibility, quality validation, simplicity, contingency and transparency. Copyright , Beech Tree Publishing.

Suggested Citation

  • Benedetto Lepori, 2006. "Methodologies for the analysis of research funding and expenditure: from input to positioning indicators," Research Evaluation, Oxford University Press, vol. 15(2), pages 133-143, August.
    • Handle: RePEc:oup:rseval:v:15:y:2006:i:2:p:133-143
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    File URL: http://hdl.handle.net/10.3152/147154406781775995
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    Cited by:

    1. Ulrich Schmoch, 2014. "The research output of universities: conceptual and methodological problems," Chapters, in: Andrea Bonaccorsi (ed.), Knowledge, Diversity and Performance in European Higher Education, chapter 4, pages iii-iii, Edward Elgar Publishing.
    2. Bozeman, Barry & Rimes, Heather & Youtie, Jan, 2015. "The evolving state-of-the-art in technology transfer research: Revisiting the contingent effectiveness model," Research Policy, Elsevier, vol. 44(1), pages 34-49.
    3. Auranen, Otto & Nieminen, Mika, 2010. "University research funding and publication performance--An international comparison," Research Policy, Elsevier, vol. 39(6), pages 822-834, July.
    4. Hung, Chia-Liang & Chou, Jerome Chih-Lung & Roan, Hung-Wei, 2010. "Evaluating a national science and technology program using the human capital and relational asset perspectives," Evaluation and Program Planning, Elsevier, vol. 33(4), pages 487-497, November.
    5. Lili Miao & Vincent Larivi`ere & Feifei Wang & Yong-Yeol Ahn & Cassidy R. Sugimoto, 2023. "Cooperation and interdependence in global science funding," Papers 2308.08630, arXiv.org, revised Feb 2024.
    6. Elisabetta Marinelli & Alexander Degelsegger & Katharina Buesel & Mariana Chioncel & Mathieu Doussineau & Karel Haegeman & Gérard Carat & Patrice dos Santos & Stephanie Daimer, 2014. "ERA Fabric Map Second Edition," JRC Research Reports JRC85302, Joint Research Centre.
    7. Irene Ramos-Vielba & Manuel Fernández-Esquinas & Elena Espinosa-de-los-Monteros, 2010. "Measuring university–industry collaboration in a regional innovation system," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 649-667, September.

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