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Authors

Halin V.

Degree
Dr of Economics, Professor St.‑Petersburg State University
E-mail
v.halin@spbu.ru
Location
Saint Petersburg
Articles

Substantial classification of decision support systems

The aim of the research is to analyze the methodological aspects of the decision support systems (DSS) processing and the DSS substantial classification. The novelty of the results lies in the fact that classification features and their possible values, being the subject and the goal of such a system, are suitable to the designed managerial decisions, as well as the classification can be used to create a specific DSS. Hypothesis: it is possible to allocate classification features of DSS, the list and the contents of which will determine the substantial (enlarged) DSS classification suitable to the construction of concrete DSS. Also, the selected classification features and their values can be used to construct DSS content, i. e. to design a block structure of created DSS. Method of research: systematic and logical analysis on the base of the subordination of the created DSS to aims and content of the generated managerial solutions. Results: based on the reasonable classification features and their values the substantial classification of decision support systems is built, as well as the block structure of the DSS, considered in the wide, and in the narrow sense as well. The research is supported by the grant RFBR 13.15.202.2016.
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Substantial classification of decision support systems (part 2)

The aim of the research is to analyze the methodological aspects of the decision support systems (DSS) processing and the DSS substantial classification. The novelty of the results lies in the fact that classification features and their possible values, being the subject and the goal of such a system, are suitable to the designed managerial decisions, as well as the classification can be used to create a specific DSS. Hypothesis: it is possible to allocate classification features of DSS, the list and the contents of which will determine the substantial (enlarged) DSS classification suitable to the construction of concrete DSS. Also, the selected classification features and their values can be used to construct DSS content, i. e. to design a block structure of created DSS. Method of research: systematic and logical analysis on the base of the subordination of the created DSS to aims and content of the generated managerial solutions. Results: based on the reasonable classification features and their values the substantial classification of decision support systems is built, as well as the block structure of the DSS, considered in the wide, and in the narrow sense as well. The research is supported by the grant RFBR 13.15.202.2016. The results published in the paper were presented at the International Scientific Conference «New Challenges of Economic and Business Development — 2016. Society, Innovations and Collaborative Economy», Riga, http://www.evf.lu.lv/conf2016. Read more...

Algorithmic and information support of innovative project management in conditions of uncertainty

The article presents the features of innovative projects of industrial enterprises that complicate the process of their management. The main groups of mathematical methods used to manage innovative projects are identified. The possible directions of further developing mathematical methods in the field of managing the complex innovative projects at industrial enterprises are determined. Algorithms of accounting the influence of uncertainty factors on the duration and costs that associate with implementing the innovation project works are presented. A distinctive feature of these algorithms is the usage of fuzzy production rules. These rules formulate recommendations for managing these projects based on the distribution of resources available in the organization depending on the results of each stage. It allows minimizing the execution time, both individual stages, and the entire innovation project as a whole. The variant of information support formation is offered that is presented in the form of a physical model of the database. This model allows storing all the information available in the industrial organization that necessary to manage these projects. A distinctive feature of this database is the ability to store information on the impact of uncertainties on the implementation effectiveness in a formalized form. This information is necessary for the implementing the developed algorithms.
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Do candidates and doctors of science in software engineering need to modernize and technological development of the Russian economy?

Creation of an information and communication infrastructure of the digital economy requires specialists capable of initiating, developing, and implementing projects the necessary software products, information resources and technologies. In Russia there is still no scientific specialty exactly named Software Engineering for the training of post-graduate students and doctoral candi-dates. Moreover, such a specialty is missing in the list of scientific specialties on which the degrees of the candidate and the doctor of sciences are defend-ed. The article provides an analysis of the status of Russian higher education in the field of bachelor’s and master’s training in Software Engineering and related specialties and formulates a proposal to include Software Engineering in the Nomenclature of Specialties of Scientists of the Russian Federation. To solve this problem, it is necessary to organize training for specialists in this area at the third level of higher professional education, namely the training of PhDs — candidates and doctors of sciences — in the field of Software Engineering. The research is partially supported by the grant RFBR 13.15.202.2016.
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Digitalization and its impact on the development of Russia

The article analyzes the impact of digitalization on the development of a particular country through the example of Russia. Digitalization can only be considered as a trend of effective world development under certain conditions. As the position of any country in the world community is largely determined by the influence of such trend, it becomes relevant to assess the degree of penetration of the digitalization into all aspects of its life. The Digital Economy and Society Index (DESI) and the International Digital Economy and Society Index (I–DESI) only evaluate the positive results of the influence of digitalization. As negative consequences are possible also, they must be assessed. The article separates the «digitization penetration» concept which only evaluates positive results of digitalization and the «impact of digitization» concept which evaluates both positive and possible negative consequences thereof. The example of Russia in the article reflects not only the penetration, but also the impact of digitalization on Russia’s life. Regretfully, the analysis showed insufficient consideration of the possible negative effects of digitalization. The article proposes a list of measures to manage the processes of digitization. Their implementation on the basis of management programs and regulatory environment should ensure positive results of digitization exceeding the possible negative ones. This will correspond to the effective impact of digitization on the economic and social life of Russia.
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Matters of economic ecosystem classification

Economic convergence and digitalization are the most important trends of the modern community development. It is their interaction that creates new opportunities for the improvement of competitive capability and performance in the framework of joint business conducted by representatives of the wide variety of segments and sectors of economy. In response to digitalization, an ecosystem becomes the main institutional and organizational form of business in the framework of inter-sectoral economic convergence. The purpose of this article is to define more exactly the concept of an ecosystem as a form of doing joint business in the environment of inter-sectoral economic convergence and digitalization, and to build a classification of ecosystems. The following hypothesis is put forward in the study: an ecosystem as an institutional and organizational form of doing joint business is the result of the concurrent impact of inter-sectoral economic convergence and digitalization thereon, and the "connection of the base product provided to customer by the inter-sectoral economic convergence initiator prior to creating an ecosystem with digital and/or information technology" may be a criterion for classification of economic ecosystems. The novelty of the approach is as follows. The consideration of an ecosystem as a form of doing joint business simultaneously influenced by economic inter- sectoral convergence and digitalization has made it possible to define more exactly the concept of an ecosystem, identify an ecosystem parameter to be applied for classification of ecosystems and the main characteristic thereof the values of which may be used to classify economic ecosystems. Read more...

Sber ecosystem – the product of digitalization impact on intersectoral economic convergence

The article contains the study of the experience of operation of the specific Sber financial ecosystem as a new form of entrepreneurial activity in the competitive economic environment which is driven by the impact of digitalization on the economic convergence processes – the modern trend in the social development in general. The study of the experience of the Sber financial ecosystem which is one of the most highly developed ones in Russia is both of theoretical and practical interest. The purpose of the article is to describe the actual experience of Sber ecosystem’s operation. The results of the performed analysis are as follows. Definitely the Sber ecosystem is a form of organization of joint business implemented in the framework of intersectoral convergence driven by digitalization. The impact of intersectoral convergence is manifested in the fact that the creation of the ecosystem was initiated by a financial institution - the largest Russian savings bank; and the participants in this ecosystem are representatives of a wide variety of sectors and segments of the economy. The impact of digitalization shows in the fact that the basis of joint business is a modern digital base which includes IT, IT platforms and networks. The modern mathematical and instrumental methods of data processing and IT startups are not only the digital specifics of the ecosystem functioning, but also effective tools to attract to a joint business – on a voluntary basis only – the partners from various fields of activity, and provide the Sber ecosystem with undoubted competitive advantages. Read more...