Паттерн-анализ и кластеризация в исследовании государственной состоятельности: "адаптивная оптика" для политической науки
The central focus of this paper is a methodological one. Using the set of indicators
of state capacity, we demonstrate a specific strategy for identifying sustainable
structures in multidimensional data sets that reflect complex and ambiguous concepts of
political science. A key feature of this strategy is the application of related, but significantly
different technically, multidimensional methods – cluster and pattern analyses.
We use hierarchical clustering with various combinations of metrics and amalgamation rules, as well as ordinal-invariant pattern-clustering. Properties of pattern analysis as a
method for studying multidimensional data are shown for the first time (to the best of
our knowledge) in the political science literature. Since clustering has been actively
used in political science for a long time, pattern analysis is still practically not adopted
in our science. This situation requires correction, since pattern-analysis has some important
and in many ways unique capabilities.
It was shown that the combination of pattern and cluster analyses makes it possible
to identify consistent structures that have a clear interpretation in terms of political
science. Thus, in the course of our study, several types of state capacity were identified
(although this task was rather illustrative for us).
We use a set of empirical indicators of state capacity: the share of military
spending in GDP, the share of military personnel in the total population, the share of
tax revenues in GDP, the total rate of homicides and victims of internal conflicts, and
the quality of government institutions. Data for more than 150 countries are taken for
1996, 2005 and 2015. Stable combinations of the values of these indicators, identified
simultaneously via pattern and cluster analyses, form the structures of state capacity.
In conclusion, we show the most promising directions for the development of
the methodology described in this paper. One of the most important is the analysis of
the dynamics of countries within the pattern-cluster structures of state capacity.
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.
We present a complex analysis of business models for large, medium and small Russian commercial banks from 2006 to 2009. The Russian banks are grouped based on homogeneity criteria of their financial and operational outcomes. The banks’ structure of assets and liabilities, profitability and liquidity ratio are taken into account. The results show how the banks are adjusted their business models before and after the financial turmoil taken place in 2008. In addition, the prevailing banking business models observed for the leading banks in Russia are defined. The banks often changing their business models are found and analyzed.
Data Correcting Algorithms in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.
For the development of technological innovations it is essential to ensure competent and modern commercialization within the framework of balanced business models. Multifactor cluster analysis of business models of contemporary high-technology companies and industries shows that the most effective commercialization emanate in the framework of four basic models. Company's profitability does not depend directly on the level of its technologies, but is determined by the quality of these business models. Besides trends in high-technology industries demonstrate raising segmentation and differentiation of markets and more frequent utilization of value network models.
The analysis of region differentiation of microentrepreneurship development and indexes of judicial statistics based on the current data of statistical recording are given in the article. The capabilities of cluster analysis for revelation of typological groups of the Russian region depending on the level of entrepreneurial activities and the results of law enforcement practice are represented.
This paper presents a pattern behavioral analysis of 100 largest Russian commercial banks by total assets during an eight- year period: from the first quarter of 1999 to the second quarter of 2007. Bank performance indicators are analyzed. Structural similarities in the development of the banks are examined. A cluster analysis is applied to determine banks with a similar structure of operations. This analysis allows to estimate how the structure of the Russian banking system has been changing over time. In particular, it allows to identify prevailing patterns in the behavior of Russian commercial banks and to analyze the stability of their position in a particular pattern.
How seriously does the degree of trust in basic social and political institutions for people from different countries depend on their individual characteristics? To answer this question, three types of models have been estimated using the data of the fifth wave of the World Value Survey: the first one based on the assumption about a generalized relationship for all countries, the second one taking into account heterogeneity of countries (using introduction of the country-level variables), the third type applying a preliminary subdivision of countries into five clusters. The obtained results have been used for suggestion of possible actions to increase public confidence in the basic institutions.
The article deals with the processes of building the information society and security in the CIS in accordance with modern conditions. The main objective is to review existing mechanisms for the formation of a common information space in the Eurasian region, regarded as one of the essential aspects of international integration. The theoretical significance of the work is to determine the main controls of the regional information infrastructure, improved by the development of communication features in a rapid process.The practical component consists in determining the future policies of the region under consideration in building the information society. The study authors used historical-descriptive approach and factual analysis of events having to do with drawing the contours of today's global information society in the regional refraction.
The main result is the fact that the development of information and communication technologies, and network resources leads to increased threats of destabilization of the socio-political situation in view of the emergence of multiple centers that generate the ideological and psychological background. Keeping focused information policy can not be conceived without the collective participation of States in the first place, members of the group leaders of integration - Russia, Belarus and Kazakhstan. Currently, only produced a comprehensive approach to security in the information field in the Eurasian region, but the events in the world, largely thanks to modern technology, make the search for an exit strategy with a much higher speed. The article contributes to the science of international relations, engaging in interdisciplinary thinking that is associated with a transition period in the development of society. A study of current conditions in their relation to the current socio-political patterns of the authors leads to conclusions about the need for cooperation with the network centers of power in the modern information environment, the formation of alternative models of networking, especially in innovation and scientific and technical areas of information policy, and expanding the integration of the field in this region on the information content.