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Commercialising Public Research under the Open Innovation Model: New Trends

Author

Listed:
  • Mario Cervantes

    (OECD Directorate for Science, Technology and Industry)

  • Dirk Meissner

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

Abstract

Strengthening the motivation, quality and efficiency of researchers’ work is a pressing issue in all countries active in science, technology and innovation policy. One way to address this challenge is by introducing flexible remuneration mechanisms which are country-specific yet still share certain basic principles such as the relationship between compensation and research productivity. Improving researchers’ remuneration is particularly urgent issue now in Russia and it is addressed by recent policy measures adopted since 2012. This paper contributes new evidence from Russian researchers, R&D managers, and government representatives collected via a survey and focus group discussions on the desirability and efficiency of the current remuneration policy. Although most members of Russia’s scientific community do not question the necessity and relevance of the government’s ‘efficient contract’ initiative in the R&D sector, the implementation of this policy has had a more mixed response. Scientists’ generally low enthusiasm towards the planned reforms may be explained by a general low level of trust in executive authorities by all layers of Russian society (especially by intellectuals), a conservative inertia of the scientific community, and by the de facto failure of previous attempts at reform. Overall, Russian scientists see introducing efficient remuneration mechanisms and increasing research productivity as key challenges. The experts pointed out that research productivity should be interpreted more widely, to include researchers’ educational, administrative and other responsibilities. The package of indicators used to evaluate R&D productivity should take into account the particular features of different scientific disciplines and areas of work. Performance-related pay (PRP) mechanisms can only be efficient if a decent basic salary is provided. Negotiating such imbalances could make the R&D sphere attractive again to talented young people as well as to experienced professionals. Our analysis leads us to conclude that a rapid transition to a PRP system without simultaneously undertaking much-needed institutional reforms would be inadvisable. It is first necessary to address the systemic problems. Regular business processes should be restructured so that researchers do not have to carry out irrelevant responsibilities. It is certainly necessary to continue increasing R&D expenditures, including raising researchers’ salaries. However, that will have little effect if researchers do not see professional and personal opportunities for themselves in the future and if their profession’s prestige remains low. An incomplete list of due S&T policy reforms includes: restructuring the public R&D sector and identifying the best performing PROs; improving funding mechanisms; attracting non-budgetary funds; improving the work of public science foundations; upgrading facilities and equipment; implementing targeted measures to preserve disciplinary schools in science; and attracting young people into science.

Suggested Citation

  • Mario Cervantes & Dirk Meissner, 2014. "Commercialising Public Research under the Open Innovation Model: New Trends," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 8(3), pages 70-81.
  • Handle: RePEc:hig:fsight:v:8:y:2014:i:3:p:70-81
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    Citations

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    Cited by:

    1. Meissner, Dirk & Shmatko, Natalia, 2017. "“Keep open”: the potential of gatekeepers for the aligning universities to the new Knowledge Triangle," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 191-198.
    2. Dirk Meissner & Wolfgang Polt & Nicholas S. Vonortas, 2017. "Towards a broad understanding of innovation and its importance for innovation policy," The Journal of Technology Transfer, Springer, vol. 42(5), pages 1184-1211, October.
    3. Maryam Ghorbankhani & Federica Rossi, 2023. "Intrinsic and strategic complementarity of research and knowledge transfer activities as determinants of knowledge transfer management: evidence from public research organisations," The Journal of Technology Transfer, Springer, vol. 48(4), pages 1386-1412, August.
    4. Elias Carayannis & Evangelos Grigoroudis, 2016. "Quadruple Innovation Helix and Smart Specialization: Knowledge Production and National Competitiveness," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 10(1), pages 31-42.
    5. CHEAH, Sarah Lai-Yin & HO, Yuen-Ping & LI, Shiyu, 2020. "How the effect of opportunity discovery on innovation outcome differs between DIY laboratories and public research institutes: The role of industry turbulence and knowledge generation in the case of S," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    6. Alexey Kindras & Dirk Meissner & Konstantin Vishnevskiy, 2019. "Regional Foresight for Bridging National Science, Technology, and Innovation with Company Innovation: Experiences from Russia," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(4), pages 1319-1340, December.
    7. De Silva, Muthu & Gokhberg, Leonid & Meissner, Dirk & Russo, Margherita, 2021. "Addressing societal challenges through the simultaneous generation of social and business values: A conceptual framework for science-based co-creation," Technovation, Elsevier, vol. 104(C).
    8. Carayannis, Elias & Grebeniuk, Anna & Meissner, Dirk, 2016. "Smart roadmapping for STI policy," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 109-116.
    9. Dirk Meissner & Natalia Shmatko, 2019. "Integrating professional and academic knowledge: the link between researchers skills and innovation culture," The Journal of Technology Transfer, Springer, vol. 44(4), pages 1273-1289, August.
    10. Jutta Günther & Dirk Meissner, 2017. "Clusters as Innovative Melting Pots?—the Meaning of Cluster Management for Knowledge Diffusion in Clusters," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 8(2), pages 499-512, June.
    11. Audretsch, David Bruce & Belitski, Maksim & Guerrero, Maribel, 2022. "The dynamic contribution of innovation ecosystems to schumpeterian firms: A multi-level analysis," Journal of Business Research, Elsevier, vol. 144(C), pages 975-986.
    12. Christos Kalantaridis & Merle Küttim, 2021. "University ownership and information about the entrepreneurial opportunity in commercialisation: a systematic review and realist synthesis of the literature," The Journal of Technology Transfer, Springer, vol. 46(5), pages 1487-1513, October.
    13. Bukhari, Esraa & Dabic, Marina & Shifrer, Dara & Daim, Tugrul & Meissner, Dirk, 2021. "Entrepreneurial university: The relationship between smart specialization innovation strategies and university-region collaboration," Technology in Society, Elsevier, vol. 65(C).

    More about this item

    Keywords

    open innovation; technology transfer; commercialisation; public research institutes; universities; industry; co-operation;
    All these keywords.

    JEL classification:

    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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