2016. No. 2 (36)

Tatiana K. Bogdanova - Associate Professor, Department of Business Analytics, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: tanbog@hse.ru

Dmitry Yu. Neklyudov - Chief Specialist for Marketing Business Analysis, MegaFon PJSC; Senior Lecturer, Department of Business Analytics, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: dyuneklyudov@hse.ru

      According to most analysts, the era of extensive growth in the telecommunications market has almost finished. The ongoingcompetition between leading telecommunications companies is bringing the problem of developing a rational telecommunications policy to the forefront.
      The ever-changingtelecommunications market, subscribers’ preferences, the expanding variety of services, the need for updating user data, the inadequate efficiency of the existing systems to form exact subscriber definitions demonstrate the need for more flexible tariff methods and policy. In spite of Russian and foreign scientists taking into consideration the pricing problems in forming tariff plans, the main accent is placed on price formation according to the profits either of the whole telecommunications field or company expenses in most attempts. The problem of differentiation of tariff plan characteristics with the purpose of subscribers’ preference calculations has not been sufficiently explored. Moreover, the structural problems of tariff plans, where phone subscribers’ preferences should be taken into consideration, and the whole tariff policy, in which formation of the entire complex of existent and prospective tariff plans should be taken into consideration, have not been properly researched. For solving these problems, we have offered a model of forming telecommunications company tariff policy using methods of intellectual data analysis and taking into consideration discovered preferences of subscribers and investors.

Emil K. Kamalov - Postgraduate Student, Department of Business Analytics, Doctoral School of Management, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: ekkamalov@gmail.com

      The article proposes a concept of reference models for automated budgeting systems designed to highlight the cross-subject area between information technologies and budgeting theory. The paper identifies methods of automation of budgeting systems, their reference elements and interaction with the organization budgeting system. In particular, the extension of functionality of spreadsheets, the development of functionality of ERP-systems, customized development of automated budgeting systems, task-oriented budgeting systems and systems available within the “software as a services” (SaaS) model are considered as the main approaches to budgeting automation.
      Reference models are taken to mean models of automated budgeting systems which describe the information system configuration for certain sectors or types of production, i.e. a meta description based on which a specific system can be configured and implemented.
      For description of a reference model, such documents as a directory of budget items grouped within the analytical dimensions, album of forms (including data entry forms and report forms), as well as passport of algorithms, which describes methods of calculation of budget accounts are proposed to be used. This documentation covers three main areas within which the information systems are designed, namely, design of data objects, design of screen forms and reports, and record of the technology being used.
      Reference models of the budgeting systems enable consulting companies to formalize and systematize the project experience to achieve a competitive position through reduction of terms and enhancement of the system integration.

Lyubov A. Pirogova - Project manager LEAN, Lamoda Company
Address: 10, Letnikovskaya Street, Moscow, 115114, Russian Federation
E-mail: lbaydalina@gmail.com

Vladimir I. Grekoul - Professor, Department of Information Systems and Digital Infrastructure Management, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: grekoul@hse.ru 

Boris Е. Poklonov - Associate Professor, Department of Information Systems and Digital Infrastructure Management, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: bpoklonov@hse.ru  

      Under current conditions, we see growth in demand for IT outsourcing services. This implies the activation of design and construction processes for data processing centers (DPC). Since a DPC is a complicated and expensive system, there arises the issue of justifying selection of the future project based on the estimated costs of designing and operating data processing centers.
      This paper analyzes one of the possible complexes of measures to estimate costs for development and operation of data processing centers. The analysis identified main groups of capital cost in development of data processing centers which were not fully taken into account in assessments of the total volume of capital investments in previously proposed methods. The article proposes regression models to evaluate processing center construction projects based on two measures. We propose to estimate the capital cost as a function of the projected floor space of service platforms and projected number of server racks. On the basis of the models developed,  analysis of the construction sites of processing data centers was conducted. This showed the model’s suitability to real data. The main groups of operating costs for DPC maintenance were established, and a regression model of their evaluation was proposed. Based on the regression equation, we propose to calculate the processing center’s power consumption depending on the area of the service platform or the number of server racks. The operating cost of the data processing center is determined by the power value. Analysis of information on the operating cost of various data processing centers is in fairly good agreement with the calculations obtained on the basis of the model developed.
      The proposed models make it possible to evaluate with reasonable accuracy the project characteristics of development and subsequent operation of a data processing center.

Evgeniy N. Efimov - Professor, Department of Information Technologies and Information Protection, Rostov State Economic University
Address: 69, Bolshaya Sadovaya Street, Rostov-on-Don, 344002, Russian Federation
E-mail: efimov46@mail.ru

      Implementation of a balanced scorecard in an enterprise requires a significant investment of time and resources. Modeling parameters substantially improves their design process and allows us to specify a situation and to track changes adjusting the strategy in parallel. It is possible to identify and, if necessary, to correct causal relationships of a complex of strategic goals, as well as to pre-define actions, resources, timelines and responsibility necessary to implement the defined goals. In this case, the analysis of scenarios obtained when modeling allows us to choose an optimal trajectory for developing the enterprise over a certain period.
      Using of the method of cognitive modeling opens the possibility to create a simple and intuitive algorithm to achieve this goal. This is a safe way to form an image of its future, to see the possibilities and consider the risks before beginning active operations.
      This method of modeling facilitates combination of elements of the enterprise’s internal and external economic environment into a single system, as well as analysis of the system as a whole and of its separate components without losing the relationships between them and taking into account both quantitative and qualitative characteristics of the processes.

Ainura T. Kasymalieva - Associate Professor, Department of Information Systems in Economics, Kyrgyz State Technical University named after I. Razzakov
Address: 66, Prospect Mira, Bishkek, 720044, Kyrgyz Republic
E-mail: aisu@rambler.ru

      When developing projects of integrated enterprise systems with focus on further expansion of functions, it is necessary to remember about continuity of models created and the timeliness of updating them. These refinements relate to the future development of organizations or their units involved in development of information systems (IS) or other software products (SP), extension of functionality of integrated enterprise information systems (IEIS), as well as development environments for design and programming. In this regard, the author proposes to apply the extended level scheme of data and database modeling. 
      When investigating the functions of each department and building their model description in subsystems (private models), it is possible to identify the same objects for providing functionality. Coherence is one of the advantages of the resulting model, providing typing and standardization of the creative processes of IS.
      We use data distribution mechanisms, which today are very topical. The proposed solution is based on a semantic dictionary reflecting the basic terms and concepts of the functional tasks of the business environment of an enterprise being modeled; it allows us to unify the application development and complements the data distribution strategy across the nodes of the enterprise.
      This article presents the principles for forming a family of harmonized data models. It provides a formal description of them, the algorithms and the possible core formation practices. The advantages of using this and approaches to possible use are discussed. 

Maxim A. Maron - Postgraduate Student, Department of Business Analytics, Doctoral School of Computer Science, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: maxim.tbconsulting@gmail.com

       This article is devoted to a problem of controlling implementation of multiscenario projects when it is necessary to provide not one, but several scenarios of performance differing from each other in structure of works. As a control method, we propose carrying out intermediate checks. The task is to determine after which works you have to carry out the checks. A heuristic method of the solution of this task is offered on the basis of an information approach. The places of performance of checks (control points) are defined step by step. Each check is chosen so that it gives maximum information (according to Shannon) concerning the work from those already completed that has been performed incorrectly. In calculations, we consider not only previously established control points, but also probabilities of implementation of various scenarios of implementation of the project under examination.
      The solution for two very important practicalcases is proposed: when the number of admissible intermediate checks is set and when their number is not set but achievement of a certainlevel of information completeness of control is required. In practice, the number of intermediate checks is limited from above by the budget for costs of control which is selected by the sponsor of the project. Information completeness of the diagnosis, in turn, is inversely proportional to the risk that the wrong implementation of the project will be revealed only after it ends. In this regard, the project manager demands that information completeness of control be no lower than a certainlevel.
      The results received are sought, first of all, by heads of design offices of  large construction companies realizing standard projects in various natural and climatic conditions (in their practice practically all projects are multiscenario). Results can also be requested in the practice of the Ministry of Emergency Situations.

Valentine K. Zharov - Professor, Head of Department of Fundamental and Applied Mathematics, Russian State University for the Humanities
Address: 6, Miusskaya Square, Moscow, 125993, Russian Federation  
E-mail: valcon@mail.ru

Yulia V. Taratukhina - Associate Professor, Department of Innovation and Business in Information Technologies, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: jtaratuhina@hse.ru

      In contemporary society, teachers often have to deal with a multicultural student audience, both in a traditional format, and in the process of online training. In general, the culture of each country has an impact on the educational process and largely determines is. This, in turn, implies a uniqueness of the educational content, objectives, value and tasks of education, teaching methods, pedagogical discourse, specifics of building an educational path, etc.
      This paper traces the relationship between the cultural influence and educational practices expressed in target, value and communication formats. Many teachers call attention to the problem of constructive knowledge transfer in a multicultural teaching environment as the main problem in this context, in addition to the specifics of cognitive, communication and psycho-pedagogical factors. However, the multicultural environment is taken to mean not only national differences, but also a different previous professional “background” (this refers to students of master's programs, etc.).
      In this paper, we share the experience of selecting criteria for the possibility of building a cultural cognitive model of communication with students (tactical and strategic methods of developing various types of discourse) in order to optimize the teaching process in the multicultural environment. The criteria based on which a new-generation multicultural educational environment is to be built and which is able to provide constructive knowledge transfer are presented as follows: communication criterion (change of traditional communication forms in the “teacher – student” system), methodological criterion (emergence of the cultural and adaptive methods of work with educational information), content criterion (differentiation and possible inhomogeneity of the educational content in the educational process) and information criterion (development and use of educational resources taking into account cultural specifics of information perception and handling). The aforementioned points, in turn, cannot but affect the transformation of some institutes of the existing information and pedagogical environment.

Andranik S. Akopov - Professor, Department of Business Analytics, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: aakopov@hse.ru

Armen L. Beklaryan - Lecturer, Department of Business Analytics, National Research University Higher School of Economics
Address: 20, Myasnitskaya Street, Moscow, 101000, Russian Federation
E-mail: abeklaryan@hse.ru

Armen K. Saghatelyan - Director, Center for Ecological-Noosphere Studies, National Academy of Sciences of the Republic of Armenia
Address: 68, Abovian Street, Yerevan, 0025, Republic of Armenia
E-mail: ecocentr@sci.am

Lilit V. Sahakyan - Deputy Director, Center for Ecological-Noosphere Studies, National Academy of Sciences of the Republic of Armenia
Address: 68, Abovian Street, Yerevan, 0025, Republic of Armenia
E-mail: lilit.sahakyan@cens.am

      The article examines a system for controlling the ecological modernization dynamics of enterprises developed with the help of simulation modelling methods and implemented using the example of the Republic of Armenia (RA). The system has been developed for strategic decision-making directed at modernization of enterprises of RA, their transformation from an initial non-ecological state towards the state of ecologically pure manufacturing.
      The main feature of the software developed is an original agent-based model describing the dynamics of the ecological-economics system. The system has been implemented using the AnyLogic platform. This model is integrated with a multidimensional data warehouse, genetic optimizing algorithm (modified for the bi-objective optimization problem of an ecological-economics system), a subsystem of simulation results visualization (Graphs, Google Maps) and other software modules designed with use of the Java technologies.
      The target functionalities of the bi-objective optimization problem of the ecological-economics system are minimized integrated (accumulated) volume of total emissions into the atmosphere and maximized integrated (averaged) index of industrial production of the agent’s population. The problem was formulated and solved for the first time. Moreover, values of objectives are calculated by means of simulation, as the result of activity of all agent-enterprises in a population and taking into account their internal interaction. The 270 enterprises of RA which are the main stationary sources of emissions of harmful substances were selected for the research. In addition, there is a generalized agent-consumer and the agent-government completing ecological regulation through the mechanisms of penalties, subsidies and rates of emissions fees. The simulation core is the developed algorithm of behavior for each agent-enterprise providing the mechanism of agent transition from an initial non-ecological state towards other possible states. At the same time, control of the evolutionary dynamics of agents is implemented with the help of the suggested genetic algorithm. As a result, the system we developed makes it possible to search Pareto-optimal decisions for a bi-objective optimization problem of the agent-based ecological-economics system.    

[1] This work was supported by the Russian Foundation for Basic Research (grant no. 15-51-05011).