Balanced of countries development determinants: barycentric model
TETYANA VASILYEVA,
Department of Finance and Entrepreneurship,
Sumy State University, UKRAINE,
:
HANNA YAROVENKO,
Department of Economic Cybernetics,
Sumy State University, UKRAINE,
SVITLANA BESTUZHEVA,
Department of International Economics and Management,
Simon Kuznets Kharkov National University of Economics, UKRAINE,
NATALIIA FROLOVA,
Department of Management and Administration,
Educational and Scientific Institute “karazin Business School”, V.n. Karazin Kharkiv National University,
UKRAINE,
TETIANA SMIRNOVA,
Department of Finance,
Lviv Polytechnic National University, UKRAINE,
NADIIA SHYLOVTSEVA
V.n. Karazin Kharkiv National University, UKRAINE
Abstract: - The authors investigate the issue of modelling the balance of countries development determinants
based on determining the center of mass. They have identified the most relevant factors characterizing countries'
social, economic, political spheres, digital capability and cybersecurity. The research has been carried based on
empirical values of the selected 17 indicators for 127 world countries in 2018. As a result, the four-pole
barycentric models were built as quadrangles, the vertices of which are composite targets formed by the
determinants of the four spheres. The models' calculations were carried out taking into account three components:
the values of the composite targets (as a geometric mean), the level of pairs balance (as the sum of opposite pairs
of quadrilateral angles), and all four targets (as the distance between the actual and standard value of the center
of mass). According to the analysis result of the first component, developed countries have the most effective
targets (top five - Switzerland, Denmark, Norway, Finland, the Netherlands). Research of the results of the second
component has revealed an imbalance in target pairs for most countries. Determinants of socio-political
development are the most effective for developed countries. The economic sphere is most unbalanced for the
least developed countries. Various determinants can cause an imbalance for developing and new industrial
countries. The analysis of the center of mass distances revealed that not only developed countries could be
balanced, but also developing, new industrial and the least developed, that indicates a balanced development of
their determinants, which is pretty slow. New Zealand, Mauritius, South Africa and Mali were the most balanced
in each group of countries economic growth.
Key-Words: - Barycentric model; center of mass; cybersecurity; digital capability; economic determinants; social
determinants; political determinants.
Received: March 15, 2022. Revised: March 9, 2023. Accepted: April 15, 2023. Published: May 30, 2023.
1 Introduction
Today, the dynamic processes in society lead to
the fact that some areas of its life are not developing
evenly enough. It can be seen through the rapid
development of information technology, which has
led to the transformation of many processes in the
economic, political and social spheres over the past
decade. In this context, its consequences are more
favorable for society and the country since they lead
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Tetiana Smirnova, Nadiia Shylovtseva
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to the construction of new IT companies, creation of
new jobs, human empowerment through the latest
developments. As for other aspects that also affect
the country's development, their impact can be both
positive and negative. Accordingly, this problem
needs to be studied and improved in identifying the
determinants that affect the country’s sustainable
development, balancing the needs of society and
protecting the future generations’ interests, and the
balanced development of all social spheres. It should
be in line with the United Nations Sustainable
Development Goals announced at the UN Summit on
25 September 2015 and the development strategies of
countries being developed in line with their priorities.
That is why this study aimed to determine the level
of balance of social, economic, political determinants
and determinants of digital capability and
cybersecurity, as composite targets, typical for any
country in the world. The formation of an appropriate
model will identify the targets that affect the
imbalance of the country's development, as well as
outline the relevant areas of government policy to
develop effective strategies that set priorities for
improving the population welfare, quality of social
and living standards, overcoming political and
military conflicts, solving environmental problems in
terms of those challenges to a society that generate
global problems.
2 Problem Formulation
2.1 Literature review
The country's balanced development assumes that
its changes are systemic and have an equal impact on
all areas. It can be ensured by several determinants,
among which the most influential are economic
(Kendiukhov & Tvaronaviciene, 2017). Significant
imbalances in countries' economies are caused by an
imperfect legal framework and the presence of a
corruption component, the impact of which violates
macroeconomic stability (Lyulyov et al., 2021a).
Brychko et al. (2021) empirically proved that the
financial sector's crisis of confidence also
destabilizes the economy. Melnyk et al. (2018) have
investigated the dependence of macroeconomic
stability on fiscal decentralization and focused on
expenditure decentralization, revenue
decentralization and expenditure decentralization
simultaneously. The formation of a sustainable
development financing system is one of the main
strategic priorities, which should consider the
specifics of the functioning of the corporate sector
(Chigrin & Pimonenko, 2014; Brychko, 2013).
Kobushko et al. (2021) prove that money is not only
an instrument of payment but also acts as a tool for
propaganda and laundering of illegal income, which
leads to the development of the shadow sector of
economics. In turn, it affects the innovative potential
(Vysochyna et al., 2020a). The formation of a
favorable investment climate in the country is one of
the ways to improve the welfare of the country's
population, which is mathematically proven by
Leonov et al. (2014). The optimal distribution of the
portion of private and public investment was
modelled in the context of economic development by
Hrytsenko (2014).
The country's development level significantly
affects the conditions for ensuring public welfare and
the formation of stable paradigms for its
improvement, which leads to qualitative changes in
social relations. However, social determinants form
the corresponding model of social life, the
consequences of which are the driver of sustainable
development (Dave, 2017). For this aspect, it is
crucial to ensure precisely social security when there
are minimal risks to the life of the population in the
country (Didenko et al., 2020). The formation of a
better social climate in the country is one of the
primary sources of attracting investment (Bagmet &
Haponova, 2018). The features of the insurance
system construction create the preconditions for its
formation (Kuzmenko, 2014). Besides, quality
education (Lyeonov & Liuta, 2016) and the
healthcare system (Samoilikova & Kunev, 2020)
form a model of a prosperous society. The triad of the
influence of economic, social and political
determinants was analyzed by Sineviciene et al.
(2018) to ensure the countries' national security
growth. As a result, a forecast of the level of
innovative changes was constructed using the
exponential smoothing method. Harust & Melnyk
(2019) have proved using the 2SLS method that
political instability negatively affects the country's
economic security.
In addition to economic, political and social
determinants, environmental factors can also affect
the development of a country. This issue was
investigated by Lyeonov et al. (2019) and determined
a link between gross domestic product per capita,
greenhouse gas emissions, renewable energy in total
final energy consumption and green investments,
which positively impact the development of certain
spheres of life. Similar findings were obtained by
Bilan et al. (2020). Vasylieva et al. (2019)
investigated the relationship between economic,
social, and environmental aspects of development
and built an environmental Kuznets curve for
Ukraine and the EU. The synergistic effect of the
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interaction of green investments and institutional
determinants manifests itself in the national
economy. It leads to a decrease in its energy
efficiency (Lyulyov et al., 2021b). The convergence
between tax and ecological systems has been proven
based on the beta and sigma convergence by
Vysochyna et al. (2020b). It also should consider that
world crises and global phenomena also directly
impact the balanced development of countries. The
negative consequences confirm that most countries in
the world have suffered due to the COVID-19
pandemic (Minchenko & Demchuk, 2021; Tiutiunyk
et al., 2021).
The consequences of the fourth industrial
revolution contributed to the digitalization of many
processes. First of all, it has affected the dynamism
of the country's economic development and increased
the level of its national security (Novikov, 2021b).
Novikov (2021a) has proved, based on bibliometric
analysis of research, that the balanced development
of a country depends to a greater extent on its social,
economic and information security. Informatization
processes are also relevant for the economy's
financial sector, where there is the greatest need to
digitalize financial services (Pakhnenko et al., 2021).
With the growth of information flows, the
confidentiality of big data must be ensured
(Karaoulanis, 2018). In parallel, the risks of financial
losses also increase due to the implementation of
massive cyberattacks, which destabilize processes
and systems and inhibit their development
(Yarovenko et al., 2021). Although most countries
are trying to solve this problem using artificial
intelligence technologies (Obeid et al., 2020),
unfortunately, preventing cyberattacks is essential for
ensuring the countries' national security. Therefore,
when determining the determinants, one should
consider not only the factors characterizing the
development of the IT industry but also the direction
of information security (Leonov et al., 2019;
Vasylieva et al., 2017). The relationship between
them was investigated by Petroye et al. (2020) based
on correlation and cluster analyses.
A wide range of mathematical methods is used for
modelling economic, political, social, informational
development. Scientists have solved these problems
by building optimization models (Kozmenko &
Kuzmenko, 2011), structural modelling
(Samusevych et al., 2021), gravity modelling
(Lyeonov et al., 2020), using data mining methods
(Kuzmenko et al., 2020), fuzzy sets (Boyko &
Roienko, 2014), regression analysis (Shkolnyk et al.,
2017; Babenko et al., 2020), probabilistic methods
(Levchenko et al., 2018), econometric tools
(Aljaloudi & Warrad, 2020), statistical analysis
(Esmanov & Dunne, 2017). It is necessary to use a
more specific method, such as determining the center
of mass, to model the sustainable development. This
method will determine the level of balance based on
the development determinants. For the study, it has
been chosen a triad of economic, political and social
determinants, as well as determinants that
characterize the development of information
technology and cybersecurity, a group of which will
be referred to as digital capability and cybersecurity.
Since environmental factors have a narrower impact
on the country's development, in this paper, they will
not be taken into account to build a model.
3 Data and Methodology
3.1. Economic, social, political determinants
and determinants of digital capability and
cybersecurity
Various determinants can influence the balance of
countries’ development, which either increase or
decrease its level. The scientific knowledge methods,
which allowed to determine the most relevant
indicators for each composite target, were used to
substantiate their choice. Thus, the digital capability
and cybersecurity are evaluated under the influence
of trends in the development of the IT industry and
its components, the level of digital development and
the security component. Since there are no uniform
approaches to defining this dimension, this group
includes five key indicators that characterize:
countries' cybersecurity weaknesses and
opportunities by developing a cybersecurity strategy
and relevant standards (The Global Cybersecurity
Index); countries' readiness to counter cyber threats
and control cyber incidents (The National Cyber
Security Index), the level of information and
communication technology development in the
country (ICT Development Index), the country's
technological readiness degree to use the latest
information and communication technologies in
various spheres of life Readiness Index), the
country's digitalization compliance degree with its
cybersecurity level to form recommendations for
adjusting cybersecurity programs (Digital
Development Level). Since the value of these
indicators positively affects the integrated value of
evaluating digital capability and cybersecurity, i.e.,
with the increase of their value increases its level, we
consider them as indicators-stimulators. It is believed
that the country, which is characterized by a high
value of the composite target of digital capability and
cybersecurity, has a strong development of
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information technology, and is considered the
country with the highest level of information
security.
Factors of the country's economic development
form a key component in achieving its balance. They
enable to assess the citizens’ welfare level (The
Global Competitiveness Index), the conditions of
running the business in the country and protection of
property rights (Ease of Doing Business), the impact
of financial systems on growth, stability, and
inequality of different economies (Financial
Development Index), ethnic, racial, regional,
educational inequality that forms the economic
difference between these groups. It ultimately affects
the country's economic development (Uneven
Economic Development Index), human ability to
control their work and property, the level of own
consumption and investment (Economic Freedom
Index). The higher the country's economic
development, the more opportunities for it to be a
leader in world markets and ensure a high living
standard for its population. Among the selected
indicators, only the Uneven Economic Development
Index is a disincentive indicator, with the increase of
which the integrated level of the economic
development target grows. Other indicators are
stimulants in nature.
The social dimension is aimed at determining the
country's ability to provide the population with a high
living standard, which is to create favorable
conditions for the population to receive such social
benefits as education, quality health services,
"environmental footprint", ensuring and maintaining
peace within the country. Indicators measuring the
quality of the citizens’ current life (Happiness Index),
the level of basic human needs provision, their
welfare and opportunities for progress (Social
Progress Index) and such basic features of human
potential as living standards, literacy, education and
longevity (Human Development Index) were
selected to analyze this composite target. The
selected determinants are stimulant indicators, so the
high integrated level of social dimension will indicate
a high level of social living standards in the country.
The political development of any country is an
integral part of its overall development, as it
describes the political life dynamics of the country,
its ability to interact with other countries in the
foreign policy space to establish a dialogue between
the state and the population. The political fluctuations
can destabilize the social mood of the population and
slow down economic development, so its evaluation
is extremely important to find the level of the
country’s balanced development. Therefore, to
determine its integral level, the following indicators
were chosen that measure: the probability that the
government can be destabilized or destroyed through
unconstitutional and violent nature (Political
Stability Index), the democracy quality in the country
based on assessments of the electoral process, civil
freedom, functioning of the government, political
culture (Democracy Index), quality of government
activities based on an assessment of the quality of
public services and bodies, quality of formation and
implementation of political measures, independence
degree on political pressure, etc. (Government
Effectiveness Index), corruption level in the public
sector (Corruption Perceptions Index). High values
of the selected determinants affect the growth of the
composite target level that indicates the political
stability in the country and its high political
development.
3.2. Research methodology
The balance of any system is its state, which
provides the optimal ratio of its components. It
enables to be in balance and be stable in the event of
external factors. Accordingly, the country’s balanced
development shows the uniform or balanced
development of its components, which ensures its
sustainability for a long time. For its modeling, the
most optimal models are those based on certain
centers of mass. It means that, depending on the
number of components that participate in evaluating
the development balance, a geometric figure is built,
the vertices of which are their composite values,
which are formed under the influence of various
determinants. This study observed four main areas -
economic, political, social, and digital capability and
cybersecurity, the most influential components or
targets for any country’s development. Thus, their
formation is carried out based on the chosen
determinants which most characterize their
development. Accordingly, this article formed a
barycentric model.
Kozmenko et al. (2009) popularized the approach
of determining the center of mass for the economic
sciences. The authors developed a triangle model to
determine the stability of the insurance and
reinsurance market, focusing on the calculation and
analysis of the circumscribed circle radius. The
methodology of building a barycentric model for the
analysis of business activity of companies was
proposed by Berzin et al. (2018), which did not
provide a graphical interpretation of the model and
there were no practical calculations. Yarovenko
(2021) continued its development to determine the
development balance level of the national economy.
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The method is based on the definition and analysis
of three components of the barycentric model: the
composite measurements, the balance of target pairs
and the balance of all four targets. It is necessary to
normalize the influencing determinants to find the
values of composite targets. This procedure is
required because the selected factors are different and
differ in their absolute values. Normalization will
reduce the values of all factors in the range from 0 to
1. Accordingly, it will simplify the data convolution
to determine the composite value of economic,
social, political and digital capability and
cybersecurity, which will also range from 0 to 1. If
the composite target approaches 1, it will indicate a
strong development of the relevant sphere of life in
the country. Otherwise, if it is closer to 0, it is the
development slowdown indicator.
There are different types of data normalization,
but this paper will use linear normalization for
stimulators (1) and Savage normalization for
destimulators (2), because the study data are spatial:



(1)



(2)
where 
normalized value of і-
determinant of the economic, social, political
dimensions, digital capability and cibersecurity
dimension for k-country;
 input value of the i-determinant of
economic, social, political dimensions, digital
capability and cybersecurity dimension for k-
country;
 and  the minimum and maximum
value of the i-determinant of economic, social,
political dimensions and the digital capability and
cybersecurity dimension among the observations,
i.e., countries.
The calculation of the composite target for
economic, social, political dimensions and the
dimension of digital capability and cybersecurity is
based on the geometric mean function (3). Its choice
is due to the fact that, as a result, we obtain an average
proportional value of the target for each country:


where geometric mean value of
composite targets, which were formed by the
normalized determinants of economic, social,
political dimensions and digital capability and
cybersecurity dimension, defined for k-country;
– the number of composite targets 󰇛󰇜;
n the number of determinants that form the
corresponding composite target ( for the
target of digital capability and cybersecurity; 
for the target of economic determinants; – the
target of social determinants; for the target
of political determinants.
When determining the geometric mean value of
those factors the normalized values of which are
equal to 0, there is a significant shift in the value of
the composite target towards 0. Then, you can use
Minkowski formula to eliminate this factor for such
values (4):
󰇛󰇜󰈅 
󰈅



(4)
where 󰇛󰇜 the composite target of
economic, social, political and digital capability and
cybersecurity dimensions;
 the weight of each determinant in the
formation of the composite target 
 . One
can conduct a canonical analysis, build a
standardized regression equation, or consider their
uniform influence on the formation of the target, to
determine them.
Building a four-pole barycentric model is
necessary to determine the balance of pairs of targets
and all four targets. It is carried out as a construction
of a quadrangle and determining its main features.
This process involves setting four points on the
coordinate area, the coordinates of which correspond
to composite targets. It is reasonable to build a
standard model and the actual data model to
understand how balanced the country's development
is. It is a square, the vertex coordinates of which are
equal to the maximum value of the target, i.e., 1. It is
a point with coordinates (1; 1) to measure digital
capability and cybersecurity, for the social dimension
- (1; -1), economic - (-1; -1), political - (-1; 1). The
points are connected by lines that form the sides of
the square. Its centroid is at the intersection point of
its diagonals ("Center of Mass"), which coincides
with the starting point of the coordinate axes and has
coordinates (0; 0). The standard model was built
using GeoGebra software and is shown in Figure 1.
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Figure 1 Standard four-pole barycentric model of country’s balanced development
Source: Yarovenko (2021).
It is quite difficult for empirical data to build a
barycentric model in the form of a square. Under such
conditions, the country has the same economic,
social, political, and information security levels. In
practice, different quadrangles can be obtained for
different countries, with different side lengths and
angles. Therefore, it is also necessary to draw a circle
around the quadrangle. It is possible if the sum of its
opposite angles is . Otherwise, this fact will
indicate the imbalance between the pairs of
dimensions.
It is necessary to divide the quadrangle into two
triangles and calculate their side lengths as the length
of segments to find the degree of angles in a
quadrangle and check the possibility of constructing
a circle around it, by the following formula (5):
󰇛󰇜󰇛󰇜
(5)
where AB is the length of the segment between
two points A and B, which are the vertices of one of
the two triangles ABC;
󰇛󰇜 the coordinates of point A, which are
the values of the corresponding composite targets;
󰇛󰇜 the coordinates of point B, which are
the values of the corresponding composite targets.
There are other sides of the triangle ABC and the
sides of the second triangle, which together form a
quadrangle.
We calculate the cosines of each angle for each of
the two triangles by formula (6):


(6)
where a, b, c values of the lengths of the
three sides in the triangle.
The obtained values are converted into degrees
using special tables or calculators. In this article, the
calculations were performed using MS Excel
software, which uses the appropriate functions.
We sum the degrees of two angles at the base of
one triangle with degrees of the other angles to obtain
the values of the two opposite angles in the
quadrangle. First, we check whether the sum of the
four angles is . Then we check the balance of
two pairs of dimensions by determining the sum of
pairs of opposite angles in the quadrangle. If their
sums are equal to , we conclude that a circle can
be described around this quadrangle, i.e., the pairs of
dimensions are balanced.
The third component of the barycentric model
(balance of four targets) is identified through
defining the centroid of the quadrangle. It involves
the calculation of its coordinates by formulas (7) -
(8):
󰇛󰇛󰇜󰇛

 󰇜󰇜
(7)
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󰇛󰇛󰇜󰇛

 󰇜󰇜
(8)
where Ox and Oy coordinates of the point О, that
is the centroid quadrangle;
(xi; yi), (xi+1; yi+1) – the coordinates of the vertices
of the quadrangle, where the vertex with coordinates
(xn; yn) will coincide with the vertex with the
coordinates (x0; y0);
A – quadrangle area, calculated by formula:
󰇛

 󰇜
(9)
The balance of the four targets is determined by
obtaining the difference between the center of mass,
which corresponds to the data of a particular country,
and the center of mass of the standard model. Then,
we calculate this distance as the length of the segment
by formula (5). The closer the obtained value to 0, the
closer the center of mass of the country’s barycentric
model to the standard value, which indicates a
balanced development of the country based on its
four composite targets
The balance of four targets is determined by
obtaining the difference between the center of mass,
which corresponds to the data of a particular country,
and the center of mass of the standard model. Then,
we calculate this distance as the length of the segment
by formula (5). The closer the obtained value to 0, the
closer the center of mass of the country’s barycentric
model to the standard value, which indicates a
balanced development of the country based on its
four composite targets.
4. Results
Authors took the data of selected determinants for
127 countries for 2018 for the study and calculations
from the sources of such organizations as The World
Bank, The International Monetary Fund, The World
Economic Forum, the independent Swedish
foundation “Gapminder”, the global nonprofit “The
Social Progress Imperative”. This period was chosen
because most determinants do not have actual values
after it, especially indicators of measuring digital
capability and cybersecurity. We will group countries
by economic development according to the
classification of the International Monetary Fund, to
analyze the results. Thus, they are divided into
developed, developing and least developed. We will
also single out among them a group of countries that
are considered to be newly industrial due to their high
rates of technological development, which acts as a
driver of their economic development. These include
Argentina, Brazil, Mexico, India, Malaysia,
Thailand, Chile, Indonesia, Turkey, China, Iran, the
Philippines (Corporate Finance Institute, September
10, 2021), and promising industrial countries from
the Group of Eleven (Nigeria, Egypt, Pakistan,
Bangladesh, Vietnam) (O’Neill et al., September 10,
2021). All calculations were performed using MS
Excel software.
4.1. Analysis of the results of the composite
targets
Figure 2 presents the results of the calculated
composite targets of economic, social, political and
digital capability and cybersecurity for twenty
developed countries or countries with a high
economic level, the list of which was determined
following the International Monetary Fund
(September 10, 2021). The top ten countries have the
highest total value of targets, the second ten - the
lowest among the group of developed countries.
A comparison of the composite targets with the
standard level (Figure 1) shows that for most
developed countries, their values go to 1 but do not
reach it. In practice, it is impossible for any country,
so the closer the calculated values go to it, the higher
the level of this dimension in the country. One should
note that Switzerland demonstrates the best result. It
has the highest total value of economic, social,
political, and digital capability and cybersecurity
dimensions (3.735).
Such countries as Denmark, Finland, Norway, the
Netherlands, Singapore, Sweden, New Zealand,
Australia, and Canada are among the top ten
countries with the highest values of composite
targets. It indicates a relatively high level of their
development. Portugal, Lithuania, Israel, Malta,
Italy, Slovenia, Latvia, Slovakia, Cyprus, and Greece
show the lowest values among the analyzed group of
developed countries. The social dimension
demonstrates the highest level of development,
indicating the effective social policy of these
countries’ governments in relation to their
population. The political and digital development and
cybersecurity dimensions for most countries prevail
over the economic target values.
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
19
Volume 3, 2023
Figure 2 The values of composite targets of economic, social, political and digital capability and cybersecurity
dimensions for developed countries
Source: own calculations
It proves that the economic potential of these
countries has given impetus to accelerate the
development of other targets, which will further
contribute to stronger economic growth in these
countries.
Figure 3 presents the calculated values of
composite targets of economic, social, political, and
digital capability and cybersecurity dimensions for
developing countries according to the list of the
International Monetary Fund (September 10, 2021).
Ten countries with the highest values and ten with the
lowest values were issued. Poland, the United Arab
Emirates, Mauritius, Uruguay, Croatia, Hungary,
Qatar, Bulgaria, Costa Rica and Romania are leading
countries. The least developed countries are
Kyrgyzstan, Bolivia, Kenya, Algeria, Nicaragua,
Honduras, Suriname, Côte d’Ivoire, Tajikistan and
Cameroon.
Figure 3 The value of composite targets for economic, social, political, digital capability and cybersecurity
dimensions for developing countries
Source: own calculations
0
0,2
0,4
0,6
0,8
1
Switzerland Denmark
Norway
Finland
Netherlands
Singapore
Sweden
New Zealand
Australia
Canada
Portugal
Lithuania
Israel
Malta
Italy
Slovenia
Latvia
Slovakia
Cyprus
Greece
Target of Political Determinants Target of Social Determinants
Target of Economic Determinants Target of Digital Capability and Cybersecurity
Standard Value
0
0,2
0,4
0,6
0,8
1
Poland
United Arab Emirates
Mauritius
Uruguay
Croatia
Hungary
Qatar
Bulgaria
Costa Rica
Romania
Kyrgyzstan
Bolivia
Kenya
Algeria
Nicaragua
Honduras
Suriname
Côte d'Ivoire
Tajikistan
Cameroon
Target of Political Determinants Target of Social Determinants
Target of Economic Determinants Target of Digital Capability and Cybersecurity
Standard Value
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
20
Volume 3, 2023
Compared to the data obtained for developed
countries, a significant imbalance arises between the
social dimension and the cybersecurity, economic
and political dimensions. The differences are quite
significant. For example, for Poland the social
dimension target is 0.8357, digital capability and
cybersecurity - 0.7773, economic - 0.6533, political -
0.6410, and for Algeria - respectively 0.6542, 0.3486,
0.1365, 0.3002. The development of the economic
and political spheres is quite critical for developing
countries. It is due either to the unstable political
situation in them (for example, Ukraine, Honduras,
Guatemala), or the ineffectiveness of the government
and its political laws and decisions. The economic
development instability of such countries is a direct
consequence of the crisis in their political sphere,
which leads to a slowdown in their development as a
whole. In other words, it is important for developing
countries, first of all, to strengthen the political
dimension by transforming legislation, combating
corruption, making more effective decisions by the
government aimed at economic development and
reform, etc. The calculated results of composite
targets for the newly industrialized countries are
presented in Figure 4.
Figure 4 The values of composite targets of economic, social, political and digital capability and cybersecurity
dimensions for newly industrialized countries
Source: Yarovenko (2021)
There is also an imbalance in the development of
newly industrialized countries (Figure 4), with the
same direction of development in the social,
economic, and political dimensions and the digital
capability and cybersecurity dimensions. However,
in contrast to the values of the composite targets
presented in Figure 3, most of these countries, except
Chile, Argentina, and Brazil, are characterized by a
more uniform development of selected areas, which
does not contain abnormal differences. Malaysia,
Chile, Thailand, Turkey, and Argentina have the
highest targets. Iran, Bangladesh, Pakistan, and
Nigeria have the worst results. Since the represented
countries are considered to have already passed
certain stages of socio-economic development and
achieved success or have all the chances for an
industrial leap, we can say that for most of them,
namely Turkey, Thailand, Argentina, Nigeria,
Pakistan, Chile, Brazil, Bangladesh, Mexico and
Iran, attention should be paid to the political and
economic dimensions to ensure the social sphere
development and the digital capability sphere.
Figure 5 shows the composite targets of
economic, social, political and digital capability and
cybersecurity dimensions for the least developed
countries, the list of which is defined by the United
Nations (September 10, 2021). Ten countries with the
highest and lowest values of indicators were
distinguished among their group of countries. Almost
all countries except Botswana and Bhutan have low
values of the four targets (Figure 5). At the same
time, you can see the uneven development of all
dimensions, mainly economic. The obtained results
0
0,2
0,4
0,6
0,8
1
Malaysia
Chile
Thailand
Turkey
Argentina
Mexico
China
South Africa
Indonesia
Brazil
Philippines
Vietnam
India
Egypt
Iran
Bangladesh
Pakistan
Nigeria
Target of Political Determinants Target of Social Determinants
Target of Economic Determinants Target of Digital Capability and Cybersecurity
Standard Value
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
21
Volume 3, 2023
prove the existence of actual problems of economic,
social, political nature and insufficient level of
information technology development, which needs
help from global and international organizations.
Figure 5 The values of composite targets for economic, social, political, digital capability and cybersecurity
dimensions for the least developed countries
Source: own calculations
4.2. Analysis of the results of the target pairs
balance
The degree of angles of quadrangle for 127
countries was determined and their pairs were formed
to analyze the balance of target pairs. They were
selected based on the following considerations.
Today, the greatest impetus in the economy is
provided by the development of information
technology, transforming it into digital technology.
On the other hand, the country’s economic
development stimulates scientific and technological
progress, the consequence of which is the IT-sphere
development in the country. These considerations
were also supported by calculating a linear
correlation coefficient between the four composite
targets values. It turned out that there is the closest
correlation between the integrated values of the
economic dimension and the dimension of digital
capability and cybersecurity (0.9144). This
relationship is also close between the pair of social
and political dimensions (0.8343). We visualize the
obtained calculations, which in percent show the ratio
of the sums of opposite angles of the quadrangle. It
enables us to conclude that the balance or imbalance
of the dimension pairs development - socio-political
and economic-digital (to reduce the name of digital
capability and cybersecurity dimension, we use
“informational”). It means that if the value goes to
50% (for a pair of social and political dimensions)
and 100% (for a pair of economic dimensions and
dimension of digital capability and cybersecurity),
the sum of the pair of angles is ; otherwise, it
will be either greater or less than . Thus, Figure
6 presents the results of calculations for developed
countries, where ten countries are with the highest
values, and ten is with the lowest values.
Analyzing the data in Figure 6, we can conclude
that countries like Italy, Japan, France, and Israel
have the most balanced pairs of targets because the
sums of pairs of opposite angles go up to .
When constructing their barycentric model, you
can draw a circle around their quadrangle. For Spain,
Singapore, Estonia, the United Kingdom, Germany
and the United States, the sum of the angles has a
slight deviation of , but for other countries, the
discrepancy is growing.
At the same time, it can be seen that the socio-
political dimension value is lower for the vast
majority of countries, which indicates the greater
importance of this pair for balanced development of
economically developed countries, as well as their
rapid growth compared to a pair of economic and
digital capability.
0
0,2
0,4
0,6
0,8
1
Botswana
Bhutan
Rwanda
Nepal
Senegal
Zambia
Uganda
Benin
Laos
Tanzania
Madagascar
Mali
Mozambique
Liberia
Haiti
Sierra Leone
Angola
Chad
Burundi
Congo
Target of Political Determinants Target of Social Determinants
Target of Economic Determinants Target of Digital Capability and Cybersecurity
Standard Value
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
22
Volume 3, 2023
Figure 6 Balancing composite target pairs of economic, social, political, and digital capability and cyber
security dimensions for developed countries
Source: own calculations
The results of calculating the sums of opposite
angles to build a barycentric model of developing
countries are presented in Figure 7, where ten
countries are with the highest values, and ten is with
the lowest values.
Figure 7 Balancing composite target pairs of economic, social, political, and digital capability and cyber
security dimensions for developing countries
Source: own calculations
We can see that Côte d’Ivoire, Bulgaria, Oman
and Romania have values close to . For other
countries, the discrepancy is growing, which
indicates that it is impossible to describe a circle
around the quadrangle of the model. The results show
that for some countries, the predominant pair is the
socio-political dimension. For Moldova, Georgia,
Kenya, Armenia, Qatar, the United Arab Emirates,
Ukraine, Bahrain, Kazakhstan, Saudi Arabia,
Azerbaijan and the Russian Federation (some of them
are not presented in Figure 7), the dimension of
economic development and digital capability and
cybersecurity prevails. Analysis of this pair of
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Italy
Japan
France
Israel
Spain
Singapore
Estonia
UK
Germany
USA
Lithuania
Sweden
Slovakia
Luxembourg
Norway
New Zealand
Malta
Slovenia
Cyprus
Iceland
Socio-political Dimension Economic and Digital Dimension
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Côte d'Ivoire
Bulgaria
Oman
Romania
Croatia
Colombia
Poland
Moldova
Hungary
Serbia
Ghana
El Salvador
Suriname
Ecuador
Trinidad and Tobago
Honduras
Guyana
Algeria
Bolivia
Namibia
Socio-political Dimension
Economic and Digital Dimension
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
23
Volume 3, 2023
dimensions for these countries showed that they have
the most powerful development in the IT, and
economic development lags far behind. Therefore, in
the case of these countries, an economic
breakthrough is possible due to the strong potential
of the IT sector.
The calculated sums of opposite angles for the
newly industrialized countries are presented in Figure
8, where it can be seen that only the model of the
Philippines and India have values of the sums of
opposite angles of a quadrangle, which are
approximately equal to . Other countries have
unbalanced pairs of dimensions, and some are
characterized by the prevalence of economic-digital
dimension (India, Indonesia, Mexico, Egypt,
Vietnam, Malaysia, Pakistan, Iran, China, Thailand,
Turkey, Nigeria), for others - socially -political
(South Africa, Argentina, Bangladesh, Brazil, Chile).
The analysis of individual indicators showed that
China, India, Egypt have a strong development of the
IT industry and cybersecurity. Mexico and Malaysia
have the same level of economic development and
IT. Brazil, Chile and Argentina have the destabilizing
political target, which is a consequence of the
political instability of these countries. It means that
the group of newly industrialized countries has
different directions of development that must be
considered by the government for development
strategy.
Figure 8 Balancing composite target pairs of economic, social, political and digital capability and cyber
security dimensions for newly industrialized countries
Source: Yarovenko (2021)
Figure 9 demonstrates the values of the sums of
opposite angles for the least developed countries,
where ten countries are with the highest values, and
ten is with the lowest values. Only for Cambodia, the
values of the sums of opposite angles of a quadrangle
are , and for Ethiopia these values are close.
Other countries have imbalance of dimension pairs,
and the vast majority of them are characterized by the
prevalence of socio-political dimension and
economic-digital imbalance. It is vice versa for Chad,
Mali and Burundi. Although the values of their
targets are low, some countries have a balanced
development of targets for dimension pairs.
For example, Bhutan (0.5400 - social target,
0.6322 - political, 0.3800 - economic, 0.3356 - digital
capability and cybersecurity), which has the same
socio-political and economic-digital development,
but there is a significant difference between these
pairs, which indicates the insufficient potential of the
economic and digital sphere. Other countries in this
group may have other development scenarios where
only one of the targets will dominate due to their
historical, cultural, political and other features of
existence and development.
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Philippines
India
Indonesia
Mexico
Egypt
Vietnam
South Africa
Malaysia
Pakistan
Iran
China
Bangladesh
Brazil
Chile
Thailand
Turkey
Argentina
Nigeria
Socio-political Dimension Economic and Digital Dimension
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
24
Volume 3, 2023
Figure 9 Balancing composite targets of economic, social, political and digital capability and cybersecurity
dimensions for the least developed countries
Source: own calculations
4.3. Analysis of the results regarding the
balance of the four targets
The calculated distances between the centers of
mass for all countries, which represent the deviation
of the actual values of their centers of mass from the
standard, are presented in Figure 10.
Figure 10 The level of countries’ development balance based on the deviation of the centers of mass in their
barycentric models
Source: own calculations
Thus, New Zealand (0.0106), Mali (0.0196),
Burundi (0.0214), Switzerland (0.0236), Sweden
(0.0272), Singapore (0.0312), Mauritius (0.0340),
Canada (0.0350), Mauritania (0.0357) are the most
balanced countries. It means that the developed,
developing, and the least developed states are the
most balanced countries. This factor proves that
regardless of the values of targets, the balance level
of their pairs, any country can have an effective
combination of four targets. For example, Mali has
low target values, but their combination is balanced,
which in the future can serve as a driver for their more
rapid and dynamic development. Paraguay (0.1860),
Algeria (0.1946), Brazil (0.1990), Kazakhstan
(0.1998), Azerbaijan (0.2063), Bahrain (0.2093), Iran
(0.2113), Ukraine (0.2269), the Russian Federation
(0.2467), and Saudi Arabia (0.2542) were the least
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Cambodia
Ethiopia
Uganda
Rwanda
Chad
Laos
Nepal
Mali
Myanmar
Tanzania
Senegal
Madagascar
Mauritania
Bhutan
Malawi
Zambia
Haiti
Congo
Angola
Sierra Leone
Socio-political Dimension Economic and Digital Dimension
DESIGN, CONSTRUCTION, MAINTENANCE
DOI: 10.37394/232022.2023.3.3
Tetyana Vasilyeva, Hanna Yarovenko,
Svitlana Bestuzheva, Nataliia Frolova,
Tetiana Smirnova, Nadiia Shylovtseva
E-ISSN: 2732-9984
25
Volume 3, 2023