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Economics of Science

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Vol 5, No 2 (2019)
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Author's column

Focus of the problem

84-100 8208
Abstract

An assessment is made of the prospects for Russia’s perception of advanced technological knowledge borrowed in industrialized countries for technological modernization of enterprises in the real sector of the economy. A review of the episodes of 2017–2019, which suggest that the policy of technological mercantelism is becoming more and more distinct and rigid forms, is presented. Especially frankly, it manifests itself in the example of relations between the USA and China, the USA and Russia.

The history of the formation and evolution of technological protectionism, starting from the seventeenth century, is considered to the present day. It has been suggested that technological colonization, which is carried out by the technology-leading countries with respect to the countries of the technological periphery, is the highest evolutionary form of technological protectionism.

National project «Science»

101-113 1315
Abstract

One of the seven target indicators of the National Science Project (NSP) is “The place of the Russian Federation by share in the total number of articles in the areas defined by the priorities of scientific and technological development in publications indexed in international databases”. The purpose of this study was to assess the basic value of this indicator for disciplines related to priority areas, according to the Strategy of scientific and technological development of the Russian Federation. The volumes of publication flows of the Russian Federation in 112 disciplines are compared with a similar indicator of countries ranked fifth in the number of publications in the subject area under consideration, indexed in the Web of Science Core Collection (WoS CC). A 5–10 fold lag of the Russian Federation was recorded for the most part of the priority areas identified by the passport of the NSP.

Factors of technological development

114-128 621
Abstract

The article analyzes the global trends of corporate venture financing (CFE) as a whole and for individual sectors of the economy. It is shown that the industries in which KFW is most actively and dynamically used are the Internet, mobile communications and healthcare. The maximum attention of corporate venture funds is attracted by start-ups in the early stages of raising capital, more than half of all venture capital deals are made at the Seed / Angel (seed stage) and Early Stage stages (the second stage of attracting start-up capital). The most common exit from venture capital deals during 2014–2018. For most industries, the redemption share of the FAC is a management startup (Management Buyout). It was concluded that Russia is poorly included in the use of corporate venture capital as a tool for building technological capacity: the country’s share in the number of corporate venture capital transactions in 2018 is 1.9% of the global total, and the total investment of Russian enterprises estimated at only 0.45% of the global total. It was suggested that it would be expedient to increase the activity of Russian corporations in the field of creating and using the capabilities of the FSC.

Economics of the education

129-142 643
Abstract

The statistics of research funding are reviewed, the experience of organizing research activities in Russian universities is summarized, and a model of its system support is proposed by the university itself. It is stated that in university science there is a “customer crisis”: the demand of the business sector does not provide the necessary volume of large and long-term orders for scientific research and studies rely mainly on the state budget. Organizational measures are proposed for a gradual transition from teaching to research with step-by-step confirmation of productivity: the creation of a new university subject – a “scientific unit” consisting of two or more employees, regardless of their academic title, with administrative rights and corresponding responsibility.

143-156 681
Abstract

The analysis of the positioning of 52 leading Russian universities in three world rankings (QS, THE, ARWU) was carried out over a seven-year time interval. It is shown that from the analysis of materials and the roughest predictions based on linear extrapolation of data, it can be concluded that none of the 52 leading Russian universities can enter the TOP-100 of the considered ratings. It was concluded that at the very beginning of the launch of the 5–100 project an unreasonable assumption was made that five leading Russian universities could be included in the TOP-100 of one or several of the three world rankings. It is shown that for successful implementation of the project it would be necessary to carry out imitating modeling previously.



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ISSN 2410-132X (Print)
ISSN 2949-4680 (Online)