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  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Digital Economy or Manic Digitalization: the Choice of Russia1</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Plekhanov Russian University of Economics</institution>
          ,
          <addr-line>Stremyanny lane, 36, M oscow, 117997</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>1977</year>
      </pub-date>
      <fpage>0000</fpage>
      <lpage>0002</lpage>
      <abstract>
        <p>What is the digital economy? The answer can be presented as a result of the development of the traditional economy, combining the realization of three directions. The first direction - all data are digitized, the second - ensuring transparency and transparency of data, the third - ensuring inclusiveness of the economy. In 2017, the Government of the Russian Federation developed and approved a Program to create conditions for the country 's transition to a digital economy. The ecosystem of the digital economy is based on a number of areas of a cluster nature, expressed in the aggregate of the planned characteristics of the digital economy. In this paper, the data of analysis and compliance of the objectives and indicators of the Program to the three basic fairways of the digital economy are presented. The results of analyzing the prop ortions of clusters and the dynamics of the implemented activities form an idea of the actual priorities of the Strategy. This study provides an answer to the question of whether Russia is moving towards the creation and development of the digital economy or replacing this activity with maniacal and little-promising digitalization. A reference has been searched for verification of the digital economy projects specified in the Program for the conditions for the transformation of the economy into a digital one. For this purp ose, data of official statistics, ICT Development Index, Digital Economy and Society Index, Networked Readiness Index were used. The results of the study do not confirm the trend towards manic digitization of data, but did not reveal significant changes that ensure the inclusiveness of the economy.</p>
      </abstract>
      <kwd-group>
        <kwd>Digital Economy</kwd>
        <kwd>Digitalization</kwd>
        <kwd>Government Program</kwd>
        <kwd>Networked Readiness Index</kwd>
        <kwd>ICT Development Index</kwd>
        <kwd>Graph M ethod</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>-</title>
      <p>What is a digital economy? This can be done as a result of the transformation of the
traditional economy. The first condition is that all data is digitized (accumulation and
processing of data according to the principle of man-machine interaction in the “C2C”
format), the second is to ensure the transparency and security of data, the third is to
ensure inclusiveness (accessibility) of the economy .</p>
      <p>In 2017, the government of the Russian Federation developed a program for the
transition to a digital economy - the Digital Economy Program. In 2019, it became invalid
due to the continuity of the National Program “Digital Economy of the Russian
Federation” (Order of February 12, 2019 No. 195-p). The National Program (hereinafter
referred to as the Program) was adopted with the aim of avoiding duplication of
program documents in the field of the development of the digital economy.
The program is designed to form a digital economy and includes a number of federal
projects. Characteristics are not an abstractive expression, they are qualitative and
quantitative indicators as of 2024.</p>
      <p>Among the most common ambitious indicators, it should be noted that at leas t 10
successfully competing world leaders, as well as at least 500 successfully operating
digital platforms and at least 500 successfully operating small and medium enterprises
in the field of creating digital technologies and platforms and providing digit al
services .</p>
      <p>The study presents data, goals and indicators that allow you to find out whether the
selected trends can lead to results that transform the traditional economy into a digital
one. The hypothesis is the statement that the results of the analys is of the proport io n s
of clusters and total costs form an idea of real priority programs. This study answers
the question of whether it is a question of the existence of economic and economic
activity.
2</p>
    </sec>
    <sec id="sec-2">
      <title>Materials and Methods</title>
      <p>
        In Russia, until 2012, the IT industry developed under the usual market laws under
the conditions of the compensatory mechanism of state regulation and control. Since
2012, the situation has changed dramatically, as experts note - the era of
unprecedented attention to the IT industry from the state began [
        <xref ref-type="bibr" rid="ref1 ref2">1, 2</xref>
        ]. With the adoption of the
Program, Russia became one of the countries that focused their policies on creating
the conditions for the transition to a digital economy.
      </p>
      <p>
        The starting point of the study is the position of the report o f the Organization for
Economic Cooperation and Development (hereinafter - the OECD), according to
which “Digital economy is an economy in which value added is created using digital
(information) technologies. It functions due to the connection and depende nce of
online economy and offline economy. At the same time, its development is
determined by “smart data” [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ]. Hence we formulate the thesis that the level and dynamics
of the process of digitalization of the economy is determined by the level and
dynamics of the value added indicator.
      </p>
      <p>
        In the Program, digital economy is represented by 3 levels:
− markets and sectors of the economy (areas of activity) - in Russia the
emphasis is on such areas as energy, transport, industry [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ];
− platforms and technologies, where competencies are formed for the
development of markets and sectors of the economy (fields of activity) - special
attention is paid to so-called cross-cutting digital technologies (technologies
used in various fields of activity);
− an environment that creates the conditions for the development of platforms
and technologies (covers regulations, information infrastructure, personnel,
and information security).
      </p>
      <p>The last two levels are recognized as the basis for the application of the regulatory
mechanism of public administration, the program is focused on them. Although here
lies a certain contradiction. After all, the most ambitious (equally -labor-intensive)
indicators of the Program include indicators that cannot be formed without
entrepreneurial initiative and outside entrepreneurial activity, using mainly the regulatory
mechanism.</p>
      <p>The key federal projects (hereinafter referred to as projects), within which the
conditions for the development of the digital economy are created, are designated:
1. Ecosystem of the digital economy (regulatory regulation of the digital
environment and digital public administration).
2. Personnel and education.
3. Digital technologies (formation of research competencies and technological
groundwork).
4. Information infrastructure.</p>
      <p>5. Information security.</p>
      <p>All five of these projects are needed to create an economy in which data in digital
form is a key factor in production. The program is calculated until 2024 and provides
for specific indicators specified in the Program’s passport.</p>
      <p>It is required to solve the problem of verifying digital economy projects specified in
the Program to the conditions for transforming an economy into a digital one. To do
this, it is necessary to compare the planned indicators of the Program with a
conditional benchmark, objectively reflecting on a global scale the level and dynamics of
digitalization of the economy. To determine this benchmark, several statistical
indicators and indices were studied. The data on the development of information and
communication technologies (hereinafter referred to as ICT) were taken as the basis, since
it is with this sector of the economy that all the elements of the Program are
connected.
3</p>
    </sec>
    <sec id="sec-3">
      <title>Results Of the Study</title>
      <p>
        In Russia, data on the development of the ICT sector can be obtain ed from a variety
of statistical indicators. The main sources of statistical data are the data of Rosstat [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]
and HSE [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ]. Let us illustrate, for example, significant statistical indicators -
indicators of value added growth (Table 1), which is consistent with the previously
advanced thesis that the level and dynamics of the digitalization process of the economy
is determined by the level and dynamics of the value added indicator.
      </p>
      <p>Table 1. Indicators of value added.</p>
      <p>Data source</p>
      <p>Name of the indicator</p>
      <p>Year
201</p>
      <sec id="sec-3-1">
        <title>Rosstat (Monitor</title>
        <p>ing the development
of the information
society in the Russian
Federation)</p>
        <p>Rosstat
(Information Society)</p>
      </sec>
      <sec id="sec-3-2">
        <title>Rosstat (Science and Innovation)</title>
      </sec>
      <sec id="sec-3-3">
        <title>Statistical collections HSE (Science. Technology. Innovation)</title>
        <p>Statistical
collections of the HSE
(Digital Economy)</p>
      </sec>
      <sec id="sec-3-4">
        <title>The share of high-tech and knowledge-intensive industries in GDP, in%</title>
      </sec>
      <sec id="sec-3-5">
        <title>Share of domestic expendi</title>
        <p>tures on research and
development in GDP, in%</p>
        <p>Internal expenditures for
research and development
(information and
telecommunication systems), million
rubles</p>
        <p>The ratio of the growth rate
of domestic spending on
research and development to the
growth rate of GDP, in%</p>
        <p>Share of ICT sector in</p>
        <p>
          GDP,%
Using statistical data, it is necessary to take into account the difference in the
calculation methodology - Rosstat data is based on the OKVED classifier, HSE data is based
on the OECD standard [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ]. To form a complete picture, you need to be patient and
consistently look for indicators that are directly or indirectly related to the Program
among a multitude of indicators calculated for the Russian Federation and the subjects
of the Russian Federation; by types of economic activity; by industry; in priority
areas; for socio-economic purposes and other classification criteria. Therefore, we
conclude that it is inexpedient to use indicators of official statistics as a reference for
verifying the digital economy projects specified in the Program for the conditions for
transforming the economy into a digital one. The reasons for this conclusion are the
following: excessively labor intensive work; the lack of a unified method of
calculation; difference in the scale of statistical sampling.
        </p>
        <p>
          The next option in defining the benchmark was the ICT Development Index (IDI).
The ICT Development Index (IDI) is an index published by the International
Telecommunication Union of the United Nations (ICT) based on combined ICT indicators
[
          <xref ref-type="bibr" rid="ref8">8</xref>
          ]. It is a standard tool for benchmarking the most important indicators of the
development of the information society and measuring the digital divide, comparing ICT
indicators within and between countries. The ICT Development Index is based on 11
ICT indicators grouped into three subindexes: A ccess to ICT (Access subindex), Use
of ICT (Use subindex), Practical skills to use ICT (Skills subindex). The rating data of
the Russian Federation on the ICT Development Index (IDI) are presented in Table 2.
        </p>
        <p>Table 2. The place of the Russian Federation in the ranking (ICT
Development Index).</p>
        <p>Year 2012 2013 2014 2015 2016 2017
Position in rating * 41 (166) 42 (166) – 45 (167) 43 (175) 45 (176)
* in parentheses are the number of countries participating in the ranking
The index is calculated according to a standardized method, which is reduced to a
single criterion, is global in nature, and can be used for comparative analysis at the
global, regional and national levels. These benefits are unconditional, however, the
meaningful coverage of subindexes is limited to indicators related to access to ICT,
the use of ICT, as well as practical knowledge of these technologies by the population
of countries covered by the study. In the Program under study, only a part of the
indicators can be correlated with the indices of the subindexes. This leads to the
conclusion that it is inappropriate to use the ICT Development Index as the required
standard for verifying the digital economy projects specified in the Program for the
conditions for transforming the economy into a digital one.</p>
        <p>
          Another index considered as a benchmark was the Digital Economy and Society
Index (DESI). This is a composite index that summarizes the relevant indicators on the
effectiveness of digital technologies in Europe and tracks the evolution of EU
member states in the field of digital competitiveness. The Digital Economy and Society
Index (DESI) is a composite index that summarizes about 30 relevant indicators of
digital efficiency in Europe and tracks the evolution of EU member states in five main
dimensions: communication, human capital, Internet use, digital integration, digital
public services. Based on the DESI Index, the International Digital Economy and
Society Index (I-DESI) is formed, which measures the performance of the digital
economy of the EU-28 member states and the EU as a whole compared to 17 non -EU
countries using a methodology similar to the DESI index The EU. In particular, the
value of the index for Russia for the period 2013-2016 was 45.7 points on a scale (in
the range from 39.7 to 75.2) [
          <xref ref-type="bibr" rid="ref9">9</xref>
          ].
        </p>
        <p>Judging by the profile and components of the DESI Index, it is of interest for this
study. However, the idea of using it as a reference for verifying digital economy
projects had to be abandoned. The reason was that the Index’s methodological tools are
limited to an evaluative component of socio -economic indicators, which can be used
to judge the rate of digitization of data and their use. It does not take into account
other basic conditions for the formation of a digital economy - the inclusiveness of the
economy and ensuring the transparency (security) of data. In addition, the DESI Index
is not focused on a comprehensive assessment of the contribution of ICT to the
country's gross domestic product structure. And this, in turn, contradicts the thesis that t h e
level and dynamics of the digitalization process in the economy is determined by the
level and dynamics of the value added indicator.</p>
        <p>The final option for determining the benchmark was the Networked Readiness Index
(NRI). The NRI is a comprehensive indicator reflecting the readiness of the world
economy to use ICT to accelerate development.</p>
        <p>The index is published as part of the annual Global Information Technology
Development Report (Global Information Technology Report). The report for 2016, the
year before the adoption of the Program in Russia, says the following: “We are at the
dawn of the Fourth Industrial Revolution, which represents a transition to a new set of
systems combining digital, biological and physical technologies in new and powerful
combinations. These new systems are built on the infrastructure of the digital
revolution.” To assess the willingness of countries to reap the benefits of emerging
technologies and benefit from the opportunities provided by the digital revolution and
beyond, the NRI Index is used. The rating data of the Russian Federation on the NRI
Index are presented in Table 3.</p>
        <p>Table 3. The place of the Russian Federation in the rating (Index of Readiness
for the Network Society).
2012 2013 2014 2015 2016 2017
56(142) 54(144) 50(148) 41(143) 41(139) –
Year
Position in rating *</p>
        <p>
          * in parentheses are the number of countries participating in the ranking
As a justification for the use of the methodology and data of the NRI Index as a
reference for verifying digital economy projects specified in the Program, the conditions
for the transformation of the economy into a digital one will proceed from the
following provisions:
− indicators of subindexes take into account all the projects of the Program,
which ensures the relevance of correlation of indicators of the Program and
indicators of subindexes;
− the NRI index is formed and used to study the role of ICT in stimulating
innovation;
− the NRI index measures the ability of countries to use ICT to increase
competitiveness and well-being;
− the results of the global rating using the NRI Index show a correlation with
the rating results on the Information and Communication Technology
Development Index (ICT Development Index) and correspond to the trends
recorded in the OECD report “Prospects for the Digital Economy” [
          <xref ref-type="bibr" rid="ref7">7</xref>
          ];
− the metadata that forms a number of indicators of subindexes are consistent
with the indicators of value added (in particular, ROIC, EVA, IRR [
          <xref ref-type="bibr" rid="ref10">10</xref>
          ]),
which makes it possible to use them to calculate and evaluate the dynamics
using the B. Stewart formula [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ].
        </p>
        <p>
          The framework translates into various main categories (su bindexes), 10 subcategories
(pillars), and 53 individual indicators distributed across the different pillars.
To establish the correspondence between the NRI Index indicators and Program
indicators, we use the graph construction method. Having labeled each of the 53
indicators with the vertices of the graph, we will connect them with the vertices
corresponding to each of the 12 indicators of the Program, distributed over 5 projects. Since the
number of vertices and edges of the graph is expressed by a finit e set, the decision on
the connection of the vertices was made on the basis of combinatorial estimation,
analysis, and enumeration of variants [
          <xref ref-type="bibr" rid="ref12">12</xref>
          ].
        </p>
        <p>To indicate on the graph of program indicators, we use the classification presented in
the passport of the National Program “Digital Economy of the Russian Federation”.
To designate the NRI Index indicators, we use the classification of the original data
set methodology (The Networked Readiness Index Historical Dataset © 2012-2016
World Economic Forum).</p>
        <p>The results are presented in Figures 1-5.</p>
      </sec>
      <sec id="sec-3-6">
        <title>Construction of the graph performs the following tasks:</title>
        <p>− reveals a qualitative relationship between the NRI Index indicators and the
Program indicators, verifying the contribution of each Program indicator to
the change in the values of the indicators and the final values of the NRI
subindexes;
− defines “growth points ”, “gap” and “bottlenecks ” in the implementation of
the Program to find the optimal solution for combining regulatory measures
affecting the decision making and execution process;
− makes it possible to organize the vertices of the graph by checking the
options for decomposition or aggregation of the graph with the prospect of
clustering of Program indicators.</p>
        <p>Conducting a correlation and regression analysis to confirm and determine the nature
of the relationship between the vertices of the graph is a natural continuation of the
course of the study, but is not presented in this paper.
4</p>
      </sec>
    </sec>
    <sec id="sec-4">
      <title>Findings</title>
      <p>The tree structure of the graph demonstrates the multiplicity of links for Program
indicators that ensure the growth of NRI Index indicators. The presence of a
connection from one indicator to several indicators of the Program (which is one of the
characteristics of the constructed graph) indicates a possible synergistic effect achieved
through the implementation of the indicators of the Program. From the perspective of
long-term planning, this effect can be considered as a justification for the
implementation schedule of the Program’s activities. The absence of null-graphs indicates that the
effect of the implementation of each indicator of the Program can be transposed into a
positive trend of the corresponding subindex.</p>
      <p>All the presented conclusions lead to the conclusion that the projects of the Program
implemented as a whole can lead to results that transform the traditional economy into
a digital one. Thus, we can say that the content of the Program corresponds to its
purpose.</p>
      <p>However, besides the content of the Program, there is also a context that, ultimately,
will determine which of the three conditions for the transformation of the economy
will become a driving force for Russia. The scale of th e Program’s indicators suggests
that an inclusive economy has been chosen as the locomotive. At the same time, the
activities of the Program in the period 2017-2018 were mainly aimed at the formation
of a legal field and information infrastructure. This co rresponds to another condition
ensuring transparency and data security - reflected by the IDI and NRI indicators,
which to a large extent ensure Russia's place in the ratings even today. And since the
installation basis created in this way cannot lead to a noticeable increase in the
position of the state in the NRI rating, changes in the rating can be expected after 2019.
Then the structure of the formed graph can answer the question, at the expense of
which context of the Program the changes were made.</p>
      <p>The trend to manic digitization of data does not confirm the results of the study, but
did not reveal any significant changes that ensure the inclusiveness of the economy.
World practice shows that the IT industry itself is self-sufficient and independent.
Therefore, it is important for the state to maintain the regulatory trend in the
“supporting” and “stimulating” regimes. The change in the regulatory trend to “total control
over the national zone” in the context of the cross -border nature of the digital
economy will lead to the fact that such directions of development as import substitution and
support for IT exports cannot be implemented in principle. Government control over
the development of the digital economy should function within the framework of
ensuring national legislation and to ensure national security without violating the
principle of inclusiveness of the economy.</p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Dneprovskaya</surname>
          </string-name>
          , N.:
          <article-title>Requirements for an innovative environment in the transition to a digital economy</article-title>
          .
          <source>Statistics and Economics</source>
          <volume>15</volume>
          (
          <issue>6</issue>
          ),
          <fpage>58</fpage>
          -
          <lpage>68</lpage>
          (
          <year>2018</year>
          ). https://doi.org/10.21686/
          <fpage>2500</fpage>
          -3925-2018-6-
          <fpage>58</fpage>
          -68.
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Pavlekovskaya</surname>
            <given-names>I.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Staroverova</surname>
            <given-names>O.</given-names>
          </string-name>
          <string-name>
            <surname>Urintsov</surname>
            <given-names>A.</given-names>
          </string-name>
          :
          <article-title>The influence of scientific and technical progress on the development of the information society</article-title>
          .
          <source>Journal of Economic Security</source>
          ,
          <volume>3</volume>
          ,
          <fpage>212</fpage>
          -
          <lpage>217</lpage>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>OECD</surname>
          </string-name>
          ,
          <article-title>M easuring the Digital Economy: A New Perspective</article-title>
          , OECD Publishing, Paris, https://doi.org/10.1787/9789264221796-en, (
          <year>2014</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          <article-title>4. The Roadmap of the National Technology Initiative (NTI) for the development of the cross-sectoral direction “Advanced Production Technologies”</article-title>
          (PPT), http://www.nti2035.ru/technology/technet, last accessed
          <year>2019</year>
          /04/01.
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <article-title>M onitoring the development of the information society in the Russian Federation</article-title>
          , http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statis tics/publications/catalog/ ed821e8043600761a7cea7fa17e1e317, last accessed
          <year>2019</year>
          /03/30.
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <surname>Statistical collections</surname>
            <given-names>HSE</given-names>
          </string-name>
          , https://www.hse.ru/org/hse/primarydata/,
          <source>last accessed</source>
          <year>2019</year>
          /03/30.
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7. OECD,
          <source>Digital Economy Outlook</source>
          <year>2017</year>
          ,
          <article-title>Access and connectivity</article-title>
          , DOI: http: //dx.doi.org/10.1787/9789264276284-6-en (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <article-title>Rating of the countries of the world in terms of the development of information and communication technologies</article-title>
          , https://gtmarket.ru/ratings/ict -development
          <article-title>-index/ictdevelopment-index-info</article-title>
          ,
          <source>last accessed</source>
          <year>2019</year>
          /04/01.
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <surname>I-DESI</surname>
          </string-name>
          <year>2018</year>
          :
          <article-title>How is digital is Europe compared to other major world economies? https://ec.europa.eu/digital-single-market/en/news/how-digital-europe-compared-</article-title>
          <string-name>
            <surname>othermajor-</surname>
          </string-name>
          world-economies,
          <source>last accessed</source>
          <year>2019</year>
          /04/01.
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10. Corporate Finance Resources.
          <source>Technical Knowledge. Finance Articles</source>
          , https://corporatefinanceinstitute.com/resources/knowledge/finance/,
          <source>last accessed</source>
          <year>2019</year>
          /04/01.
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11. EVA &amp;
          <string-name>
            <surname>Strategy</surname>
            <given-names>II</given-names>
          </string-name>
          :
          <article-title>Portfolio M anagement</article-title>
          .
          <source>Stern Stewart &amp; Co Research</source>
          , The Americas, (
          <year>2001</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <surname>Karelin</surname>
            ,
            <given-names>V.:</given-names>
          </string-name>
          <article-title>M odels and methods of grap h theory in decision support systems. Herald of the Taganrog Institute of M anagement and</article-title>
          <string-name>
            <surname>Economics</surname>
          </string-name>
          ,
          <volume>2</volume>
          (
          <issue>20</issue>
          ),
          <fpage>69</fpage>
          -
          <lpage>73</lpage>
          (
          <year>2014</year>
          ).
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>