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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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