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Determinants of Research Productivity: An Individual-level Lens

Author

Listed:
  • Konstantin Fursov

    (Institute for Statistical Studies and Economics of Knowledge, National Research University Higher School of Economics (Russian Federation))

  • Yana Roschina

    (National Research University Higher School of Economics (Russian Federation))

  • Oksana Balmush

    (National Research University Higher School of Economics (Russian Federation))

Abstract

The continuous growth of investment in R&D in Russia and the world increases the demand for optimal allocation of public funds to support the most productive scientific performers. These are, however, hard to conceptualize and measure. First, we need to consider the nature of research activity itself and, second, we need to evaluate a number of factors that influence such activities at the national, institutional and individual levels. One of the key issues is motivation of academic personnel, who are considered to be the main producers of new knowledge. Therefore, it is necessary to analyse the employment characteristics of researchers, and develop adequate mechanisms to facilitate their scientific productivity. This paper aims to examine determinants of publication activity among doctorate holders employed in an academic sector in Russia. Data for the analysis was derived from a survey on the labour market for highly qualified R&D personnel conducted in 2010 by the HSE, within the framework of the OECD/UNESCO Institute for Statistics /Eurostat international project on Careers of Doctorate Holders (CDH). With the use of regression analysis, we assess the effects of scientific capital, international cooperation, employment, and socio-demographic characteristics of researchers on their productivity, which is measured through their total publication output as well as through the number of papers in peer-reviewed academic journals. The differences between factors were assessed for two generations of researchers – below 40 years old, and above. It was shown that the quality of scientific capital, measured through diversity of research experience, has a stronger impact on research productivity, rather than the age or other socio-demographic characteristics of doctorate holders. It was also demonstrated that direct economic stimuli and actual research productivity of researchers are weakly correlated. Consequently, we identified that a potentially winning strategy for universities and research institutions that want to improve their performance indicators would be to provide younger scholars with wider opportunities for professional growth, including intense global cooperation in the professional community.

Suggested Citation

  • Konstantin Fursov & Yana Roschina & Oksana Balmush, 2016. "Determinants of Research Productivity: An Individual-level Lens," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(2), pages 44-56.
    • Handle: RePEc:hig:fsight:v:10:y:2016:i:2:p:44-56
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    References listed on IDEAS

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    Cited by:

    1. Wu, Jiang & Ou, Guiyan & Liu, Xiaohui & Dong, Ke, 2022. "How does academic education background affect top researchers’ performance? Evidence from the field of artificial intelligence," Journal of Informetrics, Elsevier, vol. 16(2).
    2. I. N. Chernova & V. B. Mikhailets & K. V. Shurtakov, 2017. "Dynamics and structure of project performers of the «Federal target program for research and development in priority areas of development of the Russian scientific and technological complex for 2014â," Economics of Science, Delo Publishing house, vol. 3(3).
    3. Henning Kroll & Peter Neuhäusler, 2022. "“Formal and informal networkedness among German Academics”: exploring the role of conferences and co-publications in scientific performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6431-6452, November.
    4. Ionela Vlase & Tuuli Lähdesmäki, 2023. "A bibliometric analysis of cultural heritage research in the humanities: The Web of Science as a tool of knowledge management," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    5. Aybars Oruc, 2021. "Requirements for Productivity in the Academic Environment," Higher Education Studies, Canadian Center of Science and Education, vol. 11(4), pages 1-40, November.

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    More about this item

    Keywords

    performance-based payment; bibliometric indicators; Russian scholars; the productivity of science; human capital; scientific publications;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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