Регионы России: стратегии и механизмы модернизации инновационного и технологического развития. Труды Восьмой международной научно-практической конференции 31 мая-1 июня 2012 г
The sector of knowledgeintensive business services (KIBS) not only contributes to its own dynamic and innovative development but also to the development of the external environment through the creation, accumulation, and dissemination of knowledge. Therefore, it is considered one of the key pillars of the knowledgebased economy. This article addresses the problem of its spatial distribution in Russia. The basis of the study is uniquely empirical, obtained through a series of largescale surveys among Russian pro ducers and consumers of KIBS. The collected data provide quantitative evidence for the spatial dimension of the sector. Comparative analysis of the production and consumption of KIBS in Russia’s federal districts makes it possible to classify the latter in terms of the exchange of related services and mapping of the intensity of their interregional supply and demand across federal districts. It is established that companies offering KIBS in Russia are largely concentrated in big cities. The demand for KIBS is more distributed, but not spa tially neutral. This paper may be of interest to researchers focusing on the spatial distribution of elements of the innovationbased economy in Russia. It is also relevant for regional authorities, because it can help them assess the development capacity of their regions.
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.
Article gives a characteristics of workforce and examines principals and approaches to development of it s innovation in modern conditions.
Prospects of modernization of Russian education on the basis of realization of the possibities given by an information society are discussed. Conditions of formation and development of the information-communication educational space are studied. The concept of the intellectual control system of innovative development of the Russian educational complex in the conditions of information society is stated/
The concept of an information-analytical Internet-portal of the Russian medical industrial complex as the basis of the intellectual control system of innovative development of the MIC is stated.