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ИД «Финансы и кредит»






Finance and Credit

Of an approach to setting up funding priorities of research

Vol. 28, Iss. 7, JULY 2022

Received: 25 December 2018

Received in revised form: 15 January 2019

Accepted: 31 January 2019

Available online: 28 July 2022


JEL Classification: O03

Pages: 1619—1653


Sergei V. PRONICHKIN Federal Research Center Computer Science and Control of Russian Academy of Sciences, Moscow, Russian Federation

ORCID id: not available

Subject. Nowadays research has totally changed its nature. Science and scientific achievements influence people’s lives and S&T progress so that management experts and politicians need to determine scientific priorities. Processes in science, factors influencing the efficiency of research, social value of scientific findings became the subject of this research.
Objectives. The research articulates aspects of setting up funding priorities of research, illustrating the case of healthcare.
Methods. The research is based on classification and structural analysis, logic and functional methods of research, principles of systems approach to identify the cause-and-effect relationship, and methods of multilevel modeling.
Results. I review practices of setting up funding priorities of research and identify contemporary distinctions of this practice. I emphasize the need to adhere to the uniform formal methodology for data collection and analysis and propose key principles for making a respective priority-setting technique. The article sets out priority-setting criteria. I developed the software to build and analyze multivariate logic structures for research priority setting.
Conclusions and Relevance. Scientifically proven approaches and modern methods for decision making should be used to evaluate relevant resources and develop the research and technical policy. The proposed tools help perform the systems analysis of research priorities in line with various fundamental and applied factors. Furthermore, they allow to give the fullest view of presumable scientific consequences and necessary resources for various tasks, and conduct their retrospective analysis. The findings may prove useful in the national innovation system of Russia for planning and managing S&T in healthcare.

Keywords: funding priorities, software, decision making, scientific priorities, multi-level modeling


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