The article aims to discuss the practical problems and inconsistencies of industrial policy in Russia since 2000, to analyze positive and negative experiences, and to draw up some lessons which are essential for a new technology-industrial policy.
The evolution of approaches to industrial policy in Russia is considered, which results particularly in convergence between innovation and industrial policies. Basic state interest groups are revealed, whose interaction determines the industrial policy design. The authors compare two recent significant industrial policies: in automotive industry and nanoindustry. On this basis, we highlight some prerequisites for successful policies.
The following main lessons are drawn:
First, global experience shows that the requirements for industrial policy and its opportunities change significantly with time. Such policies in any given country and at any particular point of time need new ideas and solutions; it is extremely difficult to replicate the success of different countries’ industrial policies.
Second, examples of successful industrial policy typically aim to enter a foreign market, become globally competitive, and attract foreign investment. The implementation of industrial policy without definite and sufficient conditions for the free entry and exit of major players and without the participation of foreign partners is doomed to merely simulate progress, to have strong informational asymmetry, and to create antagonist images of what is actually happening in the economy in the eyes of the society and the public authorities.
Third, the problem of correctly assessing the scientific and technological potential is of great importance for implementing technological-industrial policy. Numerous assessments appear to be unreliable since they do not take into account changes in business demand for technology. The tendency to use the legacy of past decades sometimes becomes a political problem, blocking new approaches and the development of international technology co-operation.
Fourth, a negative attitude towards particular policies should not be regarded as a ‘taboo’ against studying related issues. Due to the fact that for a long time in Russia it has been as if ‘there were no kind of industrial policy’, the country now has a low quality of both industrial policy and research.
The article aims to discuss practical problems and inconsistencies of industrial policy in Russia since 2000, to analyze positive and negative experiences, and to draw lessons, which are essential for the new technology-industrial policy.
The evolution of approaches to industrial policy in Russia is considered, which particularly results in convergence between the innovation and industrial policies. Basic state interest groups are revealed, whose interaction determines the industrial policy design. The authors try to make a comparison between two recent significant industrial policy examples: the automotive industry and the nanoindustry. On this basis some prerequisites for successful policies are revealed.
The following main lessons are drawn:
First. World experience shows that the requirements for industrial policy and its opportunities change significantly with time. Such policies in each country and at a given time need new ideas and solutions; it is extremely difficult to replicate the success of the industrial policies of various countries.
Second. Quite successful industrial policy examples are typically aimed at entering foreign market, becoming globally competitive, and attracting foreign investment. The implementation of industrial policy without definite and sufficient conditions for the free entry and exit of major players and without the participation of foreign partners is doomed only to simulate progress, to have strong informational asymmetry, and to create antagonist images of what is actually happening in economy in the eyes of the society and of the public authorities.
Third. The problem of correctly assessing the scientific and technological potential is of great importance for the technological-industrial policy implementation. Numerous assessments appear to be unreliable since they do not take into account changes in business demand for technology. The tendency to use the legacy of past decades sometimes becomes a political problem, blocking some new approaches and the development of international technology cooperation.
Forth. A negative attitude towards particular policies should not be regarded as a “taboo” against studying the related issues. The fact that for a long time in Russia it has been as if “there were no kind of industrial policy” led to the low quality of both industrial policy and its research.
Keywords: ; science, technology and innovation policy; priority industries; priority technologies; interest groups; state institutions.
Strategic documents that reflect future S&T priorities are often formulated without sufficiently taking into account the social context of S&T developments. The paper discusses the capabilities of social sciences for a deeper contextual analysis when setting priorities and, consequently, for helping to make the diffusion of advanced technologies more efficient. The methodological basis of the analysis is the concept of the social construction of technology (SCOT). The list of critical technologies of the Russian Federation serves as an illustrative example of a strategic document defining S&T priorities. The authors point out developments with the highest potential for social embeddedness, which could be fully used only if coupled with an understanding of related social matters. These developments are divided into four groups (clusters): biomedicine and health, energy, environment, and transport. We identify for each cluster the social groups that would be affected by the relevant technologies, the potential for multiple interpretations of a technology and a framework of interaction between members of relevant social groups. The paper proposes prospective areas of sociological research, allowing a deeper understanding of the real context in which new technologies might be developed and implemented, and thus may help optimize efforts for the diffusion of these technologies.
We conclude that many prospective technologies, which by nature belong to the 'physical' world, would be more efficient if their implementation, and possibly also development, were accompanied (and in some cases preceded) by the outputs of relevant social science and humanities studies. In this sense, we propose the use of the 'social embeddedness of technology' concept. We argue that this is an important factor affecting the success of technology implementation, and sometimes, technology configuration
Relations between the human and hi-tech worlds, even until recently considered the subject of science fiction, are taking a more real shape and becoming the focus of expert discussions. Some specialists suggest that in the future machines can become the principal creator of new technologies and race far ahead of humanity. However, emerging technologies for human enhancement offer new possibilities for humans to remain competitive against machines and to acquire more advanced physical and mental capacities. These techniques are interdisciplinary, drawing primarily on advances in medicine, pharmacology, nutrition, mobile communications, neuroscience and cognitive sciences. This paper provides examples of such developments, analyzes their contribution to the expansion of human capabilities and, consequently, implications for the future working environment. It addresses ethical issues and risks associated with human enhancement technologies, in particular, the emergence of the new social divide - between the users of such technologies and people lacking access to them. Finally, it discusses some wild cards that may cause future surprises and shocks, i.e. machines that can control a human-excluded world, a virtual level of human life that dominates real life. The author notes that such conditions will require rethinking established views of personality, human responsibility and mutual obligations that will help the establishment of new behavioral patterns.
The issue of forecasting demand for liquid fuels has become particularly significant in recent years with technological development and much tougher inter fuel competition in the transport sector. In future, these developments could radically transform the oil, gas, and electricity markets. Therefore there is a greater need for improved forecasting methods that take into account the dynamics of market factors, primarily those related to the use of new technologies. We analyse the difficulties of forecasting demand for liquid fuels in conditions of uncertainty related to future technological developments in car transport. We classify the technologies driving demand for motor fuels by the nature of their impact on the demand for petroleum products: technologies aimed at improving the energy efficiency of traditional cars, as well as drivers of inter-fuel competition, both in terms of direct and indirect substitutes for petroleum products. To resolve the problem of limited input information, the methodology incorporates clustering instruments, which enable us to group countries according to certain criteria. The use of economic and mathematical tools with optimizing units enables us to make integrated calculations that model the market for liquid fuels and assess its interactions with the markets of other energy resources. Our proposed system for forecasting demand for liquid fuels, including petroleum products, can be used as an instrument to assess the future impact of technological innovation on the development of the oil industry when carrying out Foresight studies.
Over the past decades due to increasing economic pressure and rising demands by government and society, the organizational landscape of higher education is changing while university activities become more diversified. The focus of public support is shifting from funding current activities of universities towards rewarding outcomes. There are, as a result, many strategies to adapt and develop universities in this changing environment. For example, emerging typologies for structuring a network of higher education institutions (HEIs) taking into account their diversity are at the forefront in many countries of agendas for greater efficiency in higher education. We advance a typology for HEIs in Russia taking into account indicators of research and teaching activities. We present an overview of best practices for HEIs, some typologies, a set of indicators and mathematical tools for constructing a typology of Russian public HEIs. This typology is based on clustering the input (resource allocation) and output (performance) indicators that characterize academic and educational achievements of HEIs. The proposed classification differentiates types of universities and contains a decision tree that allows assigning universities to one category or another. It can be used as a basis for a comprehensive analysis of diverse Russian universities and for government policies to address each of the identified HEI types, depending on their characteristics.