Regional balance of technology transfer and innovation in transitional economy: empirical evidence from Russia
During the last decade, the role and meaning of research and technology organisations (RTOs) and their contribution to the innovation potential of countries has been questioned. In this paper, RTOs are understood as “…organisations with significant core government funding (25% or greater) which supply services to firms individually or collectively in support of scientific and technological innovation and which devote much of their capability (50% or more of their labour) to remaining integrated with the science base…” (Hales, 2001). Transitional economies like Russia face substantial challenges with national and regional innovation policies for supporting and enabling knowledge transfer. In this context, RTOs often maintain obsolete behavioural schemes of non-market public institutions isolated from the real economic sector. The purpose of this paper is to illustrate and explain some unexpected knowledge transfer phenomena crucial for efficient regional innovation policies using Russian RTOs as example.
This article sets out to describe the current situation in the social housing sector in Russia. The author presents the historical background of social housing in Russia, it’s development and current conditions in the context of the transition from planned housing sector to one governed by market relations. The article also contains the analysis of the key structural elements of the social housing sector and expert evaluation of how well the social housing works as a mechanism for improving the housing conditions of the poor and vulnerable groups of population. The important role in the article is given to the legal status of social housing tenants, rent-setting policies and the problems of social housing finance. The main development opportunities and the main challenges for housing policy are revealed in the final sections of the article.
The ISSI 2017 Conferences provide an International forum for scientists, research managers and administrators, as well as other professionals related to information and communication science to share research and debate the new advancements of Informetrics and Scientometrics theories and applications. The theme of the 16th International Society of Scientometrics and Informetrics Conference is the theory, method as well as principle of five metrices science concepts including Bibliometrics, Informetrics, Scientometrics, Webometrics and Knowledgometrics.
The problem of effective knowledge management is one of the key objectives of improving the competi-tiveness of both individual companies and entire regions and states. The process of socio-economic systems devel-oping is a nonlinear function that characterizes the dynamics of the efficiency of the system functioning, depend-ing on the phase of the observed cycle. At the same time, microeconomic cycles are imposed on the waves of mac-roeconomic dynamics. Due to the relatively recent global formation and development of knowledge management systems, most researchers adhere to the concept of a rising wave in the context of the problems of knowledge management in macroeconomic terms. Our research covers the period of market transformation of the Russian economy, and the retrospective period of a planned economy in the USSR, starting from 1947. The results ob-tained show that knowledge management cycles have started long before the day when the term "knowledge management" appeared.
The article argues that the results of modernization are determined by the growth of innovation potential. The success of modernization depends on the coherence of technological, educational and communication strategies.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.