Article
Являются ли кластеры эффективными для развития промышленных предприятий в странах с бывшей плановой экономикой?
One of the goals of the first edition of this book back in 2005 was to present a coherent theory for K-Means partitioning and Ward hierarchical clustering. This theory leads to effective data pre-processing options, clustering algorithms and interpretation aids, as well as to firm relations to other areas of data analysis. The goal of this second edition is to consolidate, strengthen and extend this island of understanding in the light of recent developments. Moreover, the material on validation and interpretation of clusters is updated with a system better reflecting the current state of the art and with our recent ``lifting in taxonomies'' approach. The structure of the book has been streamlined by adding two Chapters: ``Similarity Clustering'' and ``Validation and Interpretation'', while removing two chapters: ``Different Clustering Approaches'' and ``General Issues.'' The Chapter on Mathematics of the data recovery approach, in a much extended version, almost doubled in size, now concludes the book. Parts of the removed chapters are integrated within the new structure. The change has added a hundred pages and a couple of dozen examples to the text and, in fact, transformed it into a different species of a book. In the first edition, the book had a Russian doll structure, with a core and a couple of nested shells around. Now it is a linear structure presentation of the data recovery clustering.
A wireless sensor network of rectangular mesh confi guration and between 20 and 260 clusters of smart sensors is studied. The probability of failure-free operation and the duration of the polling cycle are estimated.
In this paper we describe the cluster modification for the method of conjugated interactions for resource allocation in real time. In contrast to the original method, this modification allows to guarantee an arbitrarily high stability of the structure of resource allocation regardless of the volatile context of solving the problem.
In this paper we describe the cluster modification for the method of conjugated interactions for resource allocation in real time. In contrast to the original method, this modification allows to guarantee an arbitrarily high stability of the structure of resource allocation regardless of the volatile context of solving the problem.
This article examines the evolution of the significance of cluster territories in resource - driven economies. Authors provides an analysis of factors in turning a territory into a habitat for an industrial cluster. Authors proposes stages in transforming an industrial cluster into an innovation cluster based on saturating the base territory with spatially affined production and scientific units, strong direct and indirect relations, and intensive knowledge flows. The outcome of geographic concentration is expected to be the cluster synergy effects, which "turns into" the cumulative territory effect with reflection in positive social - economic processes. Authors have conducted the testing of particular cluster territories for the intensity of using a cluster territory.
Modern international economic environment is exposed to profound transformations of business operating conditions due to consequences of the financial crisis. Currently the organizational flexibility becomes the most important characteristic of enterprises. In its turn it presumes the adoption of such organizational structures where business relationships and aligned IT infrastructure are recognized as a specific type of the resource that a company can use to achieve competitive advantage. This research analyzes various issues of flexible organization and enterprise models which influence functionality and architecture constraints of enterprise information systems. For the analysis the authors have applied a transactions mechanism concept and specific design methodology. This paper offers an insight into key properties of four flexible organizational forms in tight connection with Enterprise Ontology formal modeling approach and DEMO, which follow the language-action perspective.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
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.