Неколичественные наблюдения и методы их обработки в части статического анализа развития российского рынка информационных технологий
This document presents results of non-quantitative observations application and their processing methods, which significantly widen the analytical capabilities of the statistical measurement of the Russian IT market. The need to expand statistical tools that allow to reflect current and future trends in the sectoral development of IT sphere in a fast and visible manner, due to the rapid character of penetration of these services into the Russian market, is argued in the paper.
With the help of business climate indicators and construction of different homogeneous behavior models, analysis of business trends in the financial and economic activities of IT organizations is presented, highlighting the specifics of them functioning within the various cyclic episodes of 2010-2017.
Intellectual capital is very heterogeneous so it’s usual practice to divide it into some groups of more similar and homogeneous intellectual assets. It’s widespread to distinguish human capital (knowledge, skills of employees etc.), structural capital (business‐processes, innovations, corporate culture etc.) and relational capital (brand, reputation, relationships with customers etc.). The literature supports the significance of intellectual capital influence on company’s value creation. Researchers find a strong dependence of corporate performance on intellectual assets in different countries and economy branches. But their findings about a character of intellectual capital transformation in corporate value are ambiguous. Importance of human, structural and relational capital and interrelationships between them vary highly across papers. It may be explained by high firm specificity of corporate value creation. It doesn’t mean impossibility of intercompany research but requires a comparability of analyzed firms. Empirical researches on the theme of intellectual capital are often limited to particular country and industry. This restriction makes investigated companies more comparable. But we suppose there is a lot of other significant aspects of firm specificity that may impact on transformation of intellectual assets into corporate value such as firm size, amount of intangible assets, total firm efficiency etc. These variables are sometimes considered as additional factors of corporate value. But we suppose these criteria may define the model of corporate value creation in principle. This study is targeted to reveal some main types of companies and investigate a specificity of corporate value creation model for each of them. We expect to discover significant differences in models mostly related to importance and significance of particular intellectual assets. This paper is empirical and quantitative. Our sample embraces about 200 large public European industrial companies from 7 countries (Denmark, Germany, Great Britain, Finland, Netherlands, Portugal and Spain) for 2005‐2009 years. The database includes: 1. Information from financial statement. The source is Amadeus database (Bureau Van Dijk). 2. A set of nonfinancial proxy indicators (quantitative and qualitative) displaying a state of human, structural and relational capital. This data has been collected from open Internet sources such as companies’ sites. Methodology of the research combines statistic methods (cluster analysis and factor analysis) and econometrics (regression analysis). Clustering distinguishes some main types of companies. Factor analysis constructs integral indices for human, structural and relational capital on the base of initial proxy set. Regression is an instrument of modeling the corporate value creation. We found significant differences between models of corporate value creation. Human, structural and relational capitals differently transform into firm value in each type of companies. Our findings have some practical implications. For example prioritizing investments in intellectual assets should take into account a firm’s specificity more deeply. This study comprises research findings from the ‘Intellectual Capital Evaluation” Project carried out within The Higher School of Economics’ 2011 Academic Fund Program.
In the current climate of sanctions imposed against Russia by several countries in 2014, special attention should be given to high-tech sectors of the economy as a key source of import substitution on the domestic market. One of the important policy measures is to support the development of high-tech, specialized clusters by forming new linkages and strengthening existing ones between small and medium-sized businesses, large enterprises, and research organizations. The starting point for an effective cluster policy is to define areas with high potential for clustering of these industries. The paper presents an original method to identify potential clusters and tests the method on Russian regions. We show that most of the state-supported pilot innovative territorial clusters are being developed in regions and sectors that have a high level of cluster potential. A typology of existing clusters depends on the index of clustering potential. We identified regions that have similar or comparatively favourable conditions for creating clusters in the pilot sectors.
The textbook includes a set of tasks linked by the theme “The Use of Information Technologies in the Modern World”. The textbook is designed to develop academic reading skills and aims at the efficient IELTS exam preparation for the aspect of reading. The textbook can be used in a traditional classroom as well as for a self-study. It can be used independently or as a supplementary material for ‘Infotech (English for Computer Users)’, Cambridge University Press (2014) by Santiago Remacha Esteras. The textbook is recommended for the students studying at the Faculty of Business and Management and the Faculty of Computer Science for a Bachelor’s degree in “Business-Informatics”, “Software Engineering” and "Computer Security".
The author researches the issues of usage of economical and statistical indices of functioning of special economical zones. The combination of economical approach with technocratic favors the creation of complex method of assessment of usefulness and efficiency of innovations, their screening, distribution of limited resources and also presupposes formation of wide applied aspect.
Purpose: Today many programs supporting clusters are introduced in Russia and other countries. The purpose of the research is to provide a relevant quantitative study assessing the effectiveness of cluster policy. Design/methodology/approach: In this paper, the effectiveness of Russia's cluster policy is analyzed using regression analysis. The survey covers data on 516 Russian enterprises divided into two groups: companies from supported clusters and firms that are members of similar but not supported clusters. To the classical variables of Cobb-Douglas production function (companies’ revenue, number of workers, capital of the company) we added cluster program dummy variable. The main question of the research is whether companies in supported clusters operate more effectively than other companies. Findings: The analysis provided quite interesting results. It was found that governmental support which was received by 27 innovative clusters didn’t have any effect on the revenue of the companies. This means that Russian innovation clusters work equally efficiently, regardless of whether they have government support. Research/practical implications: We have not found short-term effects on the enterprises associated with the supported clusters. The obtained results indicate that cluster policy conducted from 2012 to the present time requires adjustment. In this regard, the authors propose recommendations on further implementation of cluster policy. Originality/value: We have described the production function of Russian companies which work in the clusters. We have found that there is no significant effect on companies' output from government supporting of the clusters in Russia. Effectiveness of cluster policy has never been evaluated empirically before this research. Keywords: Cluster, Cluster Policy, Cluster Policy Impact Assessment, Innovative Territorial Clusters
IT Platform Choice Taking Into Account Economic Characteristics
IT Platform Choice Taking Into Account Economic Characteristics
We consider certain spaces of functions on the circle, which naturally appear in harmonic analysis, and superposition operators on these spaces. We study the following question: which functions have the property that each their superposition with a homeomorphism of the circle belongs to a given space? We also study the multidimensional case.
We consider the spaces of functions on the m-dimensional torus, whose Fourier transform is p -summable. We obtain estimates for the norms of the exponential functions deformed by a C1 -smooth phase. The results generalize to the multidimensional case the one-dimensional results obtained by the author earlier in “Quantitative estimates in the Beurling—Helson theorem”, Sbornik: Mathematics, 201:12 (2010), 1811 – 1836.
We consider the spaces of function on the circle whose Fourier transform is p-summable. We obtain estimates for the norms of exponential functions deformed by a C1 -smooth phase.