<?xml version="1.0" encoding="utf-8"?>
<journal>
  <titleid/>
  <issn>2782-6015</issn>
  <journalInfo lang="ENG">
    <title>π-Economy</title>
  </journalInfo>
  <issue>
    <volume>10</volume>
    <number>2</number>
    <altNumber> </altNumber>
    <dateUni>2017</dateUni>
    <pages/>
    <articles>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>7-20</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>J.</surname>
              <initials>Boehlke</initials>
            </individInfo>
          </author>
          <author num="002">
            <individInfo lang="ENG">
              <surname>M.</surname>
              <initials>Faldzinski</initials>
            </individInfo>
          </author>
          <author num="003">
            <individInfo lang="ENG">
              <surname>M.</surname>
              <initials>Galecki</initials>
            </individInfo>
          </author>
          <author num="004">
            <individInfo lang="ENG">
              <surname>Osinska</surname>
              <initials>Magdalena</initials>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Dynamics of economic growth in Ireland in 1980–2014</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">This paper is aimed at modelling a GDP growth rate in Ireland in order to separate the periods of particularly intense growth which are particularly important from the perspective of economic miracle definition. We applied a threshold error correction approach to cover several perspectives of the growth dynamics using different thresholds. A threshold cointegration approach allows to identify a long-run equilibrium within the context of different regimes, which provides a way of identification of asymmetric adjustment in both: short and long horizons. We extended the procedure of threshold identification by using individual economic variables as threshold variables and we further used a model with statistically significant parameters as a basis of testing. Enders and Siklos (2001) introduced the methodology to measure the long-run equilibrium in different ways, i.e., as SETAR and Momentum TAR. In general, GDP growth rate observed in 1980–2014 is the subject of analysis but we validate the results using a longer sample starting from 1973. We find that structural changes are most often identified in the period of recession of 2008–2009. Best models are obtained with the following thresholds: net income from the EU and GDP growth rate. This stresses the important role of investment and the source of its funds.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10201</doi>
          <udk>3.33.338</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>intense economic growth</keyword>
            <keyword>Ireland</keyword>
            <keyword>threshold cointegration</keyword>
            <keyword>validation</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.1/</furl>
          <file>01_boehlke_faldzinski_galecki_osinska.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>21-32</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Aleksandrova</surname>
              <initials>Ariadna</initials>
            </individInfo>
          </author>
          <author num="002">
            <individInfo lang="ENG">
              <surname>Ostapovets</surname>
              <initials>Ekaterina</initials>
            </individInfo>
          </author>
          <author num="003">
            <individInfo lang="ENG">
              <surname>Klochkova</surname>
              <initials>Alexandra</initials>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Directions of improving the public procurement system in the Russian Federation</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">Problems and development issues of the state of the procurement system in the Russian Federation are analyzed in the paper. The state (municipal) order as a competitive method for the determination of the contractor (supplier) is considered in order to formulate its optimal characteristics and competition (bidding) as the best method to select the contractor (supplier). The methods of increasing economic interest of private organizations in public services provision are examined. The differentiation of public services prices as a tool of increasing economic interest is researched in two aspects: differentiation of prices on public services based on standards and division of public service rates by groups of agents (suppliers). The barriers hindering the access of non-governmental organizations to public service markets are identified. Also the analysis of normative regulation of the public procurement system and its disadvantages, statistical data, problems encountered by the participants is done. The actions of customers and suppliers are considered to identify the presence of weak points in the legislation. The costs incurred by customers including mandatory staff training, preparation of extracts from USRLE, certificate of origin ST-1 form, obtaining digital signatures, postage are analyzed. The ROS and UIS systems and their new options useful for participants are compared. The method of assessment of contracts for monetary and non-monetary criteria is proposed. International practice of state procurement is investigated; the public procurement system of the Russian Federation is evaluated by objective indicators, the main directions limiting access of foreign companies to the public procurement market are identified. The combined analysis included a comparison of the public procurement systems of the Russian Federation and countries of the Organization for Economic Cooperation and Development (OECD) as a group of countries with the highest incomes per capita.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10202</doi>
          <udk>336.25</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>public procurement system</keyword>
            <keyword>state regulation</keyword>
            <keyword>public procurement</keyword>
            <keyword>international experience</keyword>
            <keyword>competitive procedures</keyword>
            <keyword>barriers</keyword>
            <keyword>public services</keyword>
            <keyword>state (municipal) order</keyword>
            <keyword>evaluation</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.2/</furl>
          <file>02_aleksandrova_ostapovets_klochkova.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>33-43</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Balashova</surname>
              <initials>Elena</initials>
              <email>elenabalashova@mail.ru</email>
            </individInfo>
          </author>
          <author num="002">
            <individInfo lang="ENG">
              <surname>Gnezdilova</surname>
              <initials>Olga</initials>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Innovations in russian industry: government support, expectations and reality</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG"/>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10203</doi>
          <udk>338.22</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>Industry</keyword>
            <keyword>industrial economics</keyword>
            <keyword>technological development</keyword>
            <keyword>innovative strategy</keyword>
            <keyword>industrial policy</keyword>
            <keyword>regulatory legal acts</keyword>
            <keyword>government support</keyword>
            <keyword>innovative activity</keyword>
            <keyword>innovations</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.3/</furl>
          <file>03_balashova_gnezdilova.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>44-53</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Milskaya</surname>
              <initials>Elena</initials>
              <email>santa-2000@mail.ru</email>
            </individInfo>
          </author>
          <author num="002">
            <individInfo lang="ENG">
              <surname>Bychkova</surname>
              <initials>Anastasia</initials>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Analysis and evaluation of innovation and investment activities potential of economic entities (for example, the Northwestern Federal District)</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">The current situation of the economic entities of the Northwestern Federal District (NWFD) has been analyzed in this article. Regional innovative activity evaluation is an actual topic of studies among Russian economic scientists, research centers and departments. The current innovation and investment situation in Northwestern Federal district has been characterized and statistical data for the period of 2005–2014 was analyzed by authors. The result of this work concludes the uneven distribution of innovative activity among economic actors that are members of the Federal district. Due to the significant role of the government in the formation of investment activity in the regions, an analysis was conducted of the directions of industrial policy of innovative-investment activity of economic entities. The results of the study showed that nowadays in each subject of the Northwestern Federal District there are a lot of actions that are made to strengthen innovation activities, developed plans and strategies for its development. Moreover, authors carry out evaluation of existing methods for the analysis of innovative activity and innovative potential of the region. In total number, nine methods developed by Russian institutions, organizations and scientists were reviewed there. Using this information, the comparative analysis of all methods was released; the advantages and disadvantages of each were mentioned. Based on this, authors have selected only one methodology and used it in further calculations. The authors have performed analysis of innovative-investment activity of economic entities in the Northwestern Federal District, as well as the evaluation of innovative potential of each actor of the region. The results showed that in most regions of the northwestern Federal District it is necessary to strengthen government’s actions in order to stimulate innovative activity at the enterprises. The final part of the work authors have made a forecast of the volume of innovative goods, works and services, produced by enterprises of the Federal District. The linear regression equation was used to build a forecast for 2015–2025. The results of the study can be used for the formation of the policy for further regional development, creation of innovation and investment strategy and development of the actors and the region in general.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10204</doi>
          <udk>338.2</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>The Northwestern Federal District</keyword>
            <keyword>innovation</keyword>
            <keyword>investment and innovative activity</keyword>
            <keyword>regression analysis</keyword>
            <keyword>measures of state support</keyword>
            <keyword>correlation analysis</keyword>
            <keyword>economic entity of the region</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.4/</furl>
          <file>04_milskaya_bychkova.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>54-63</pages>
        <authors>
          <author num="001">
            <authorCodes>
              <orcid>0000-0003-2978-9757</orcid>
            </authorCodes>
            <individInfo lang="ENG">
              <orgName>Vologda State University</orgName>
              <surname>Shichkov</surname>
              <initials>Aleksandr</initials>
              <email>shichkov@vologda.ru</email>
              <address>Lenina St.,15, Vologda, Russia, 160000</address>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Operations management: converting manufacturing capital in manufacturing-technological systems of engineering business</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">The article is dedicated to rethinking Kondratyev’s research of economic environment in countries having the developed market economy. The methodology and the results of his research allowed us to conclude that there is no national economy, but there are national economic models. The initial parameters in these models are the needs of people ensuring their life activity. These conclusions have been made by analyzing prior indicators of different countries and the improvement rate of technological and manufacturing assets. Kondratyev’s waves are the results of human activity in an objective economic environment directed at fulfilling people’s needs. Shumpeter also suggested improving economic models based on continuous human needs in innovative products, technologies and efficient manufacturing structures. To respond to these challenges, we offer to use the first and second laws of thermodynamics. Based on these laws we have developed a mathematical model for converting manufacturing capital into monetary capital in the form of produced and sold products and services. The studies of a conversion operating cycle in real engineering business have shown that the market cost of business on the stock market and its result in the form of sold products are determined by a criterial equation including five similarity criteria. The mathematical model of operations management has been created based on an operating cycle converting the manufacturing capital into monetary capital in the form of produced and sold products and services. Further research will be dedicated to extending this approach in evaluative technologies of tangible and intangible assets, estimation of business by the market capital method, designing innovative projects, organization of manufacturing processes based on transfer operating costs within technological stages being at the same time the zones financial responsibility, organization of management accounting</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10205</doi>
          <udk>658.012.5</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>conversion operating cycle in engineering business</keyword>
            <keyword>operations management</keyword>
            <keyword>criterial equation of conversion operating cycle</keyword>
            <keyword>similarity criteria of operating cycle</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.5/</furl>
          <file>05_shichkov.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>64-74</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Grishunin</surname>
              <initials>Sergei</initials>
              <email>sg279sg279@gmail.com</email>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Developing the mechanism of qualitative risk assessment in strategic controlling</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">A mechanism has been developed for assessing a company’s strategic risks and selecting the risk factors on which the risk management actions of the company must be focused. The risk factors are projections of the company’s internal and external environment which create its competitive advantages but are exposed to the most dangerous threats. The mechanism is an integral part of strategic risk controlling, the application of strategic controlling to risk management, and was built as a set of interrelated procedures which perform the selection of risk factors. The design of the mechanism is based on the integration of strategic analysis of fthe company’s value chain and failure mode and effects analysis (FMEA). This design, unlike that of the alternatives, allows maximum accounting for the majority of links and correlations among strategic goals, projections and risks. The paper elaborates on the main tasks and functions of strategic risk controlling and shows the advantages of integration of value chain analysis and FMEA in a single risk assessment mechanism. It works out the flow chart of the mechanism of assessment of the company's strategic risks. It develops the procedure of calculation of FMEA’s risk scores (risk priority numbers (RPNs)) for individual end-risks; at the level of each strategic perspective and at the level of the entire strategy. It develops the procedure of selecting the optimal strategy among the strategic alternatives using the Hurwicz minimax criterion in which strategy-level PRNs are utilized as the measures of risks. Finally, the paper works out the procedure for choosing the risk factors among strategic perspectives and develops the key tool of this procedure, the risk-factor positioning matrix. This matrix allows searching for the optimal ways and tools of risk control. The mechanism allows increasing the efficiency of risk management in strategic controlling and concentrating the management’s attention on the company’s strategic factors which are exposed to the most dangerous risks.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10206</doi>
          <udk>65.012.123</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>risk management</keyword>
            <keyword>strategic controlling</keyword>
            <keyword>risk controlling</keyword>
            <keyword>analysis of company value chain</keyword>
            <keyword>failure mode and effects analysis (FMEA)</keyword>
            <keyword>strategic risk assessment</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.6/</furl>
          <file>06_grishunin.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>75-87</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Lipuntsov</surname>
              <initials>Iurii</initials>
              <email>lipuntsov@econ.msu.ru</email>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Information and analytical components in modern applications</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">The potential of an information system is determined by a combination of the information and economic-mathematical models implemented in it. These models serve as a basis for the information and analytical components. They fulfill various functions: the information component corresponds to the information content and access to data, while the combination of economic-mathematical models of the analytical component determines the intelligence of the data processing. With the development of distributed systems and cloud technologies, the need arises to examine the two components separately. The need to distinguish these two components arises especially acutely in large-scale projects such as the creation of a government infrastructure. Under the conditions of industrial data delivery, when the majority of the participants in an economic activity are acting in the role of producers and consumers of information, standardization of how the data are presented and of the methods of processing them becomes essential. This article handles the two components of an information system as two independent subsystems, the separate stages of creating models are described, and the logic of their interaction in the system is shown. The interrelationship of the components is presented in the form of a reflection of the separate activity logic elements on the information level and further on the program level, as well as the feedback from the applications onto the information and logic of the activity. The description of the components is focused on subject matter experts whose role is growing at the present level of informatization. Most local and simple elements of activity have passed the stage of primary informatization and the task of establishing interaction among the systems and integrating them is becoming urgent. These tasks require a deep understanding of the subject domain in order to embody them in integrational information systems. The training of economic-mathematical and cybernetics specialists is frequently limited by the disciplines of economic-mathematical modeling without proper presentation of these models in information models and applications.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10207</doi>
          <udk>330.47; 330.46</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>information modeling</keyword>
            <keyword>economic-mathematical modeling</keyword>
            <keyword>transaction systems</keyword>
            <keyword>integration systems</keyword>
            <keyword>methods of data processing</keyword>
            <keyword>methods of data integration</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.7/</furl>
          <file>07_lipuntsov.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>88-97</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Strelnikova</surname>
              <initials>Larisa</initials>
            </individInfo>
          </author>
          <author num="002">
            <individInfo lang="ENG">
              <surname>Lembrikova</surname>
              <initials>Marina</initials>
              <email>zhur@igms.info</email>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">Using economic and mathematical models and methods to assess the human capital of a company in the field of IT industry</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">The problem of effective use of human resources represents an extremely difficult socio-economic challenge, therefore, currently there has been a marked increase in interest in the evaluation of human capital as the most important resource that provides competitive advantages for modern companies in every field. The aim of this study is to assess human capital of the company’s employees on the basis of expert approach using a competence model and aggregated indices randomization method. The article clarifies the concept of human capital as the basic structural element of intellectual capital, presents a brief overview of the most common models and methods of human capital assessment and demonstrates the necessity of realization of a competence-based approach in the evaluation of the company’s employees and personnel segmentation. The possibility and the advantage of application of the aggregated indices randomization method (AIRM) to produce a comprehensive assessment of the level of competence of employees of the international division of a Russian company in the field of IT industry is demonstrated. The division based in St. Petersburg is engaged in the development of custom software and modernization of corporate information systems in the financial industry, telecommunications, online-travel, mobile development, Internet projects and media. This study employs mathematical methods (aggregated indices randomization method, expert score), comparative methods (analysis, synthesis, classification), as well as the general logic methods of scientific concept construction. The scientific novelty of the research lies in the fact that, based on existing research, the authors propose a new instrumental technique, realizing the algorithms for assessing the human capital of the company’s employees, the results of which reveal the priorities in the field of recruitment, development and motivation of the staff, thereby implementing a rational approach to using human and financial resources of the company. The practical significance of the study lies in the development of methodological tools for human capital assessment that can be used for managing other information technology companies.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10208</doi>
          <udk>338.984</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>human capital</keyword>
            <keyword>models and methods of human capital assessment</keyword>
            <keyword>competence</keyword>
            <keyword>competence</keyword>
            <keyword>competence model</keyword>
            <keyword>aggregated indices randomization method</keyword>
            <keyword>personnel segmentation</keyword>
            <keyword>competitiveness</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.8/</furl>
          <file>08_strelnikova-lembrikova.pdf</file>
        </files>
      </article>
      <article>
        <artType>RAR</artType>
        <langPubl>RUS</langPubl>
        <pages>98-115</pages>
        <authors>
          <author num="001">
            <individInfo lang="ENG">
              <surname>Tsatsulin</surname>
              <initials>Alaxander</initials>
            </individInfo>
          </author>
        </authors>
        <artTitles>
          <artTitle lang="ENG">The hybrid model of multivariate index analysis of current assets</artTitle>
        </artTitles>
        <abstracts>
          <abstract lang="ENG">This article discusses the principles and methods of constructing a hybrid model for multivariate index analysis of the circulation of tangible assets on the example of retail trade enterprises. Analysis of the time and circulation velocity of the current assets was carried out with respect to the on-hand inventory for homogeneous positions of the group assortment of a shoe department of an economic entity. The time model and the turnover rate were built separately. At the final stage, applying the so-called index crossing procedure, the author constructed a v|t-model, which contains five independent characteristic factors. Each of the considered characteristic factors corresponds to its standard statistical indicator, according to which the economic analysis is traditionally carried out depending on the formulated goals and tasks, both at enterprises and in special applied studies. The same factors serve as indicators of the financial performance of any economic entity, as comparative characteristics in assessing the subject’s competitiveness in the commodity markets and can be used in assessing the market value of a business. The resulting model is verified, reliable calculations have been made for it. The model opens up new horizons for financial and economic analysis of the circulation of the company’s tangible assets, allows to comprehensively study the parameters of velocity and time of commodity circulation. The latter is complicated, and sometimes even impossible at all, in econometric multifactor models due to multicollinearity of characteristic factors. This circumstance makes the future hybrid model constructed in the solution of problems of short-term forecasting and operational planning promising.</abstract>
        </abstracts>
        <codes>
          <doi>10.18721/JE.10209</doi>
          <udk>339.144</udk>
        </codes>
        <keywords>
          <kwdGroup lang="ENG">
            <keyword>simple index</keyword>
            <keyword>analytical index</keyword>
            <keyword>index crossing</keyword>
            <keyword>mixed-index analysis</keyword>
            <keyword>hybrid model of factor analysis</keyword>
            <keyword>primary and secondary feature</keyword>
            <keyword>working capital</keyword>
            <keyword>current assets</keyword>
            <keyword>index model</keyword>
          </kwdGroup>
        </keywords>
        <files>
          <furl>https://economy.spbstu.ru/article/2017.64.9/</furl>
          <file>09_tsatsulin.pdf</file>
        </files>
      </article>
    </articles>
  </issue>
</journal>
