Fuzzy Technologies for Modeling Social Capital in the Emergent
Economy
VIACHESLAV DZHEDZHULA
Department of Finances and Innovative
Management
Vinnytsia National Technical University
95, Khmelnytsky highway
UKRAINE
VIKTORIYA HUROCHKINA
Department of Economics, Entrepreneurship
and Economic Security, State Tax University,
Irpin, 31, Universytetska str.
UKRAINE
IRYNA YEPIFANOVA
Department of Finances and Innovative
Management
Vinnytsia National Technical University
95, Khmelnytsky highway
UKRAINE
ANATOLY TELNOV
Department of Marketing and Trade
Entrepreneurship, Khmelnytsky National
University, Khmelnytsky, 11, Instytutska str.
UKRAINE
Key-Words: - social capital, emergent, fuzzy logic, linguistic variable, digital environment, intellectual
measurement
Received: July 12, 2021. Revised: January 4, 2022. Accepted: March 3, 2022. Published: March 24, 2022.
1 Introduction
The system of social capital development in the
emergent economy focuses on social interaction in
professional activities. It requires adaptability and
flexibility, from banking to drawing. In the
paradigm of social capital development to non-
traditional and non-economic factors, should
include the following: digital, information, technical
and technological, environmental, energy and
resource, neuro-psychological and neuro-linguistic,
ethical, cultural, and religious, political and
institutional, etc. To the main properties of the
development system, social capital include natural
and developed elements. The natural ones are:
- potential for interaction or social resources
when employees achieve the results of the
enterprise;
- ability to accumulate - creating networks of
social ties;
- convertibility as an exchange on a non-
equivalent basis;
- ability to exchange and other resources in
quantitative terms;
- liquidity as an opportunity to exchange on an
equivalent basis;
- profitability as saving transaction costs of
cooperation or receiving social rent.
The developed elements of social capital include:
- corporate qualities, including the ability to
work as a team;
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
915
Volume 19, 2022
Abstract: Development of fuzzy mathematic model of identification of emergent state allows estimating the
intensity of occurrence of positive emergent in the course of development of social capital. The main factors
influencing the decision-making process regarding the emergent social capital have been determined. The
system of social capital development is considered. As a result of modeling, we have chosen the indicator Esc
- the level of emergence of social capital, which will assess the level of influence of drivers on the level of
development of social capital in the modern information society of the emergent economy. The results of the
study show that the indicator of the level of emergent social capital is formed on the basis of sources of
structural, cognitive, relational, intellectual dimensions and dynamic processes of development of the digital
environment, which promotes interaction and forms social network connections. Application of fuzzy logic in
mathematic models of identification of the emergent state allows to take into account the national characteristics
of the object of study and traditional and non-economic factors, at the same time, focuses on social interaction
in the professional activities of the society.
- focus on new knowledge and self-development;
- adaptive and communicative abilities
(emotional and adaptive intelligence);
- observance of moral norms and rules of
conduct;
- acquired general and special (professional,
subject) competencies that form an integral
competence.
In Social philosophy is a phenomenon of the
ideology of the information society, which is based
on information anthropology and axiology,
information ethics, culture, consciousness and
digital culture. The information society lives in an
age of ideas and creative leadership. Co-creation,
self-organization and self-development of actors is a
driver in the world VUCA (volatility, uncertainty,
complexity and ambiguity) unstable, uncertain,
complex and ambiguous. Delay in the development
of social capital occurs in the absence of
imagination of the subjects and a state of
uncertainty, everything else is only indirect factors
of influence.
2 Literature Review
Stimulating the self-development of subjects begins
with the specific qualitative characteristics of the
system of social capital development, which should
include preflection (evaluation and adaptation of
one's own behavior to an effective result) and the
level of adaptive intelligence of subjects (economic
agents) in unpredictable operating conditions (speed
of adaptation, communication, speed of recovery
“resilience”).
R. Putnam, who argued that “social capital is
associated with personal connection in social
networks, which is reliable and reciprocal” [1].
Social capital is based on social interaction, ie it is a
driver of social networks for productive work in
society. The convergence of the “social” part to the
term “capital” acquires a new meaning - intangible,
as we cannot touch it, consider, and therefore the
study of social capital requires non-standard
approaches. And such a characteristic of social
capital as the emergence of new qualities of a
system refers to emergent properties.
Firms with high social capital systematically
outperform their peers during periods of economic
distress [2]. Social capital hedging firms against
systematic shocks by mitigating employee-related
litigation risk.
In [3] the value appropriation involving startups
and examines the relationship between founder
social capital and value obtained by startups in R&D
alliance agreements are considered.
The formation of digital culture, ethics, tolerance
and virtual patience in the period of formation of the
information society are also specific qualitative
indicators of the effectiveness of the system of
social capital development.
The theoretical essence of the concept of
“resilience” is interpreted as resilience,
replenishment of personal resources, the ability of
the subject to cope relatively well with difficult
situations, the potential for recovery, return to
previous physical and psychological states
associated with psychological stress and trauma. As
noted by N. Gusak and V. Chernobrovkina “in
Ukraine the use of the concept of resilience
approach began in 2017, due to the psychological
trauma of society due to hostilities in the country”
[4].
The convergence of elements of economic and
socio-emotional dimensions of the theory of social
exchange and the strength of their impact on
people's participation in joint economic activities
has led totransition from the economy of attention to
the economy of participation, in which the
achievement of ecommunication and the
development of social skills through the effects of
involvement.
Horizon 2020, one of the parts of the European
Union's research project, focuses on participatory or
shared economics: “Ps2Share Participation, Privacy,
and Power in the Sharing Economy” [5]. The main
goal is to identify the key challenges of the sharing
economy and to improve European digital services
by making recommendations to European
institutions. The initial phase of this research project
includes a set of three literature reviews on the state
of research on three main topics related to the
sharing economy: participation, privacy and power.
The formation of an economy of participation or
sharing is a specific quantitative indicator of the
effectiveness of the system of social capital
development in the country.
The experience of stimulating creative thinking
in the system of social capital development has
shown results in the application of practice-oriented
approachproblem-based learning (PBL, Project
Based Learning). As Ulger K. notes, “PBL had a
significant impact on creative thinking, but a
tendency to think critically to a lesser extent. One of
the possible reasons for this result is the use of non-
programmatic problem-solving process for the
development of creative thinking [6]. That is, such
an approach based on problem-based learning is the
basis for building relationships of non-core
problem-solving processes, maintaining uncertainty
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
916
Volume 19, 2022
and enhancing creative thinking, but will not affect
the emergence of critical thinking.
Creating a knowledge management system that
will ensure high competitiveness of enterprises and
organizations and their innovative growth in the
concept of innovative progress is a specific
quantitative indicator of the effectiveness of social
capital development. According to Ilyashenko S. M.
and the team of authors “organizational and
economic mechanism of knowledge management
will determine the priority areas of knowledge
production on global (industry, market) trends and
existing potential, choose effective ways to apply
these areas by creating and implementing
(commercializing) product, technology,
management and other innovations” [7].
Thus, the above characteristics of quantitative
and qualitative systemic effects (synergistic and
emergent) are achieved through the interaction of
agents. As for the emergent effects, they have a
dualistic nature, which has the characteristics of
achieving multi-vector results of activities or a
double trajectory of functioning with different
results in one plane - ambiguous activity. In modern
economics it is called ambidexterity or
ambidexterity.
Ambidextria (from Latin ambo - both + dextri -
right), Ambidexterity, ambidexterity (translated
from English. ambidexterity -ambiguity, ambiguity)
at the level of the economic system should be
considered as the ability to synchronously conduct
different processes while maintaining a balance of
interests and using the inherent capabilities of the
components of the system.
Hughes M. exploring organizational
ambidexterity combines the art of management at
the level of organizational structure and design,
while at the individual level in terms of people's
skills, leadership and work in general. However, he
notes that "we realize that we may not need to do
everything ourselves" [8] and highlights six basic
recurring elements of organizational ambidexterity
that we must appreciate if we want to understand
this phenomenon and interpret it correctly, namely:
otimeliness and punctuality, survival of the
organization, compromise and balance, load
management, greatness and importance,
synchronicity and agility.
Under conditions of emergence ambidextric
properties in the economic system (or in the agent at
the micro-level), there is an effect of resistance to
the operating environment. A feature of the strategic
strength of the economic system is the timely
identification of resistance and activation of
adaptive capacity and resilience to
eliminate/mitigate negative factors. In [9] the
mathematical model has been developed to support
intellectual decision-making on the optimal balance
of financial security for the innovative activities of
industrial enterprises in the face of a shortage of
financial resources, is presented as a set of fuzzy
logical equations. In [10] proposed scientific and
methodological approach for estimating emergent
properties, based on the modeling of processes
according to the theory of fuzzy logic, where the
information base became the dynamic changes in
the functioning of mechanical engineering
enterprises, the system of organizational and
organizational acceptance technological.
3 Methodology
Emergence, as an emerging phenomenon,
characterizes the set of properties of the system
that is a consequence of unpredictable
bifurcation in a dynamic environment.
environment and quantitative and qualitative
new properties that were not inherent in both
the sum of the components of the system as a
whole and its individual elements [11].
Social capital arises due to the convergence
of its constituent elements and is an emergent
effect with different scenarios of strategic
development (dualistic attractor and
ambidexterity). The system of social capital
development is shown at fig. 1.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
917
Volume 19, 2022
Fig. 1: The system of social capital development
The immanence of the nature of the development
of a scenario depends on the potential of the
economic system and the factors of influence at the
time of bifurcation.
For developing a mathematical model based on
fuzzy technologies for modeling the measurement of
social capital in the emergent economy on the
example of social capital of Ukraine groups of
measurement of influencing factors are selected,
which are classified according to various features
and divided into five subgroups: structural,
cognitive, relational, intellectual, digital. Typically,
such indicators are qualitative and quantitative.
Scientific and methodological approach to
assessing the level of influence of drivers of social
capital development in the emergent economic
system using the theory of fuzzy logic is to measure
the level of emergence of social capital in a certain
range. As a result of modeling, we have chosen the
indicator Esc - the level of emergence of social
capital, which will assess the level of influence of
drivers on the level of development of social capital
in the modern information society of the emergent
economy (fig. 2).
4 Results and Discussion
Linguistic variable (LV), which corresponds to
the indicator of the level of emergence of social
capital in the emerging economy Esc can be
represented as a ratio:
Esc =(X, Y, Z, W, Q), (1)
where Esc- indicator of the level of emergent
social capital;
X is a linguistic variable that describes the
influence of sources of structural dimension;
Y - linguistic variable that describes the impact
of cognitive dimensions that affect social capital;
Z is a linguistic variable that describes the
influence of the relational dimension, which affects
the formation of relationships,
W- linguistic variable that describes the impact
of the intellectual dimension, which characterizes
the level of development of social capital in the
economy of emergent influence,
Q - linguistic variable that describes the impact
of the level of development of the digital
environment.
Resource provision
En
vir
on
me
nt
Inc
rea
sin
g
the
lev
el
of
wel
far
e
of
the
pop
ulat
ion
Socio-
psychological
environment
Institutional
environment
Social
norms and
rules
Civil society
institutions
Trust
and its
level
Socio-cultural
(education,
science, art)
State and
legal
institutions
Human capital
Social networks or social
connections
Property of the
collective public good
Synergy,
emergence
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
918
Volume 19, 2022
Fig. 2: Tree of hierarchical connection of formation and development social capital
The linguistic variable describing the emergent
structural dimension can be expanded as follows:
X = (x1, x2, x3), (2)
where x1 - linguistic variable s “architecture of
structure" (the ratio of women to men);
x2 - linguistic variable "level of trust";
x3 - linguistic variable "social well-being and
public mood";
The linguistic variable describing the emergent
cognitive dimension can be expanded as follows:
Y = (y1, y2, y3), (3)
where y1 - LV "psychological distress";
y2 - LV "anomie (lack of norms)";
y3 - LV "values";
The linguistic variable describing the emergent
dimensions of relational dimension can be expanded
as follows:
Z = (z1, z2, z3), (4)
where z1 is LV “index of national distance”;
z2 - LV “index of state subjectivity of Ukraine”;
z3 - LV "index of social tension";
The linguistic variable describing the
emergencies of the intellectual dimension can be
expanded as follows:
W = (w1, w2, w3), (5)
where w1 - linguistic variable "adaptive
intelligence";
w2 - linguistic variable "emotional
intelligence";
w3 - LV “ integral index of social well-
being”;
The linguistic variable that describes the
emergence of the digital environment can be
deployed as follows:
Q = (q1, q2, q3), (6)
where Q1 - LV "digital infrastructure";
Q2 - LV "digital ethics and trust";
Q3 - LV "online services";
Table 1 shows the universal sets of variations of
factor values, units of measurement, and linguistic
terms for evaluation by experts.
A similar situation with the membership
functions of the variable Esc. The number of
membership functions for this variable corresponds
to the number of linguistic terms - 5; function
definition range [0… 10]. Other membership
functions are built into the program in a similar way
using the built-in Fuzzy logic designer packages.
The mathematical model of identification of the
emergent state of social capital is presented in the
form of a set of fuzzy logical equations, which are
Esc
Esc L
Esc bA
Esc M
Esc aA
X
Z
X2
X1
X3
Y3
Y2
Z2
Z1
Z3
Y1
W3
Y
W
Q 3
W2
Esc H
Q
W1
Q 2
Q 1
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
919
Volume 19, 2022
formed on the basis of information from knowledge
bases.
Mathematical model of intelligent decision
support with the definition of the dimension of
social capital in the emergent economy is
represented by a set of fuzzy logical equations based
on information obtained from the knowledge base.
A fragment of the mathematical model is presented
below:
µgi (x1) µd (x2) µla (x3) µl (y1) µp (y2) µabs
(y3) µl (z1) µd (z2) µh (z3) µd (w1) µl (w2)
µzvr (w3) µgsg (q1) µritcrit (q2) µl (q3) µgi (x1) µd
(x2) µl (x3) µu (y1) µh (y2) µabs (y3) µl (z1)
µd (z2) µh (z3) µd (w1) µl (w2) µhap (w3)
µgsg (q1) µritcrit (q2) µbsabs (q3)µgi (x1) µd (x2)
µha (x3) µu (y1) µp (y2) µVapor (y3) µl (z1) µd
(z2) µh (z3) µd (w1) µl (w2) µzvr (w3) µgsg (q1)
µqa (q2) µbsabs (q3)µgi (x1) µd (x2) µl (x3) µu
(y1) µp (y2) µabs (y3) µza (z1) µChad (z2) µh
(z3) µd (w1) µl (w2) µzvr (w3) µgsg (q1)
µ ritcrit (q2) µl (q3)µgi (x1) µd (x2) µl (x3) µu
(y1) µp (y2) µabs (y3) za (z1) µd (z2) µh (z3)
µd (w1) µl (w2) µzvr (w3) µh (q1) µqa (q2)
µbsabs (q3) = µH (Esc);
(7)
Using a knowledge base and a set of fuzzy
logical equations allows you to perform process
modeling measurement of social capital in the
emergent economy. For the processing of fuzzy
information, phasing and dephasification it is
necessary to use specialized software packages that
allow obtaining the predicted data automatically
without manual calculations. One such complex is
the Matlab mathematical package. Formed
mathematical model in the mathematical package
Simulink Matlab (Fig. 3).
This model allows us to determine the value of
social capital in the emergent economy. The
calculation is performed as follows: the values of
the input variables obtained by experts or calculated
analytically are entered into the blocks of constants
at the input of the model. The integration units
supply an input signal to the input port of the fuzzy
Fi model. Then the program performs calculations
and the signal is fed to the display unit in the form
of a numerical value - the predicted value -indicator
of the level of emergence of social capital in the
emerging economy.
The window of the virtual oscilloscope with the
value of the simulation result for 2018 is shown in
Figure 4.
Table 1. Influencing factors as linguistic variables
Designation and name of the
variable
Universal
set of variations
Linguistic terms for estimating the factor and its
limits
structural dimension factors (X)
x 1 - LV "architecture of
structure"
U(x1) = {0… 10}
(gap)
Gender inequality (gi), [0-5]: average (a), [5.1-7.5]
equal (e) [7.6-10]
x2 - LV "level of trust"
U(x2) = {0… 10}
(items)
Distrust (d), [0-3.9];
average confidence level (mt), [4-7.5]
trust (t) [7.51-10]
x3 - LV "social well-being
and public mood"
U(x3) = {0… 10}
(items)
Low (l), 0-1.5; below average (la), [1.6-2.5];
average (a), [2.6-5]; above average (ha), [5.1-7.5]
high (h) [7.6-10]
cognitive measurement factors (Y)
y1 - LV “Psychological
distress”
U(y1) = {0… 10}
(items)
Unsatisfactory (u), [0-2.4]; low (l), [2.5-4.4];
satisfactory (s), [4.5-6.99]; sufficient (suf), [7-8.5]
high (h) [8.4-10]
y2 - LV "anomie (lack of
norms)"
U(y2) = {0… 10}
(items)
Present (p), [10-8]; high (h), [6.01-7.99]
average (a), [4.5-6]; low (l), [2.5-4.49]
absent (abs) [0-2.4]
y3 - LV "values"
U(y3) = {0… 10}
(items)
Absent (abs), [0-3.99]; Partial (pair), [4-6.5]
Steel (const) [6.51-10]
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
920
Volume 19, 2022
factors relational measurement (Z)
z1 - LV «index of national
distance»
U(z1) = {0… 10}
(items)
Low (l), [8.6-10]; average (a), [5.6-8.5]
partial (pair), [3.6-5.5]; high (h), [2.01-3.5]
full [0-2]
z2 - LV «index of state
subjectivity of Ukraine»
U(z2) = {0… 10}
(items)
Destruction (d), [0-1.99]; vector changes (vc),
[2-3.5] device (ad), [3.6-5.5]; integration (i),
[5.6-7.5] transformation (t) [7,6-10]
z3 - LV "index of social
tension"
U(z3) = {0… 10}
(items)
High (h), [10-7.5]; average (a), [7.49-5.5]
below average (la), [4.99-3]; low (l) [0-2.99]
factors of intellectual measurement (W)
w1 - LV “Adaptive
Intelligence”
U(w1) = {0… 10}
(items)
Destruction (d), [0-2]; average (a), [2.1-3.5]
partial (pair), [3.6-5.5]; moderate (m), [5.6-7.5]
strong full (df) [7.6-10]
w2 - LV "emotional
intelligence"
U(w2) = {0… 10}
(items)
Low (l), [0-2]; average (a), [2.1-3.5]
partial (pair), [3.49-5.99]; high (h), [6-7.99]
full [8-10]
w3 - LV «integral index of
social well-being»
U(w3) = {0… 10}
(items)
Despair (ZVR), [0-2.8]; average (a), [2.9-4]
security (sec), [4.01-6.5]; happiness (hap) [6.6-10]
factors emerging in the digital environment (Q)
Q1 - LV "digital
infrastructure"
U(Q1) = {0… 10}
(items)
Significant gap (sg), [0-2]; low (l), [2.01-2.5]
average (a), [2.6-5]; developed (dev), [5.01-7.59]
high (h) [7.6-10]
Q2 - LV «digital ethics
and trust »
U(Q2) = {0… 10}
(items)
Critical, [0-2.59]; low (l), [2.6-3.5]
average (a), [3.51-6.5]; high (h) [6.51-10]
Q3 - LV "online services"
U(Q3) = {0… 10}
(items)
Absent (abs), [0-2.5]; low (l), [2.51-3.5]
average (a), [3.6-6.5]; developed (dev) [6,6-10]
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
921
Volume 19, 2022
Fig. 3: Fuzzy mathematical model of measuring social capital in the emergent economy
Table 2. Simulation results
Year
x1
x2
x3
y1
y2
y3
z1
z2
z3
w1
w2
w3
Q1
Q2
Q3
Soc
cap
Esc
2016
0.88
1.9
2.25
0.6
0.75
1.3
2.4
3
1.8
3.0
3.58
3.1
3.72
1.2
5.12
4.14
2.37
2017
0.93
1.8
2.42
0.6
0.8
1.4
3.5
3.15
2.0
2.8
2.11
3.3
3.80
1.4
5.24
4.30
2.39
2018
0.88
1.9
2.71
0.7
0.9
1.5
4.3
3.2
3.2
2.9
1.92
3.4
3.96
1.5
5.87
4.60
2.67
2019
0.88
2.6
3.47
1
1.2
1.8
5.3
4.0
3.5
3.0
2.14
4.0
4.36
1.4
5.69
5.33
2.89
2020
0.83
2.2
2.37
1.4
1.6
2.1
6
4.6
4.8
3.1
4.23
4.7
5.94
1.3
6.82
6.26
3.47
Fig. 4: The simulation results for 2018 are displayed in the virtual oscilloscope window
Development level social capital is in Ukraine in
2020 6.26 points on a scale from 0 to 10, which
compared to 2016 is 4.14 points more than 51.20%.
With such data, the level of emergent state of social
capital in 2020 is 3.47 points on a similar scale, ie
the state of emergence is 55.43% in 2020,
respectively, according to the dynamic changes in the
level of social capital development over the years, it
should be noted that the state of emergence is:
54.22% in 2019, 58.04% in 2018, 55.58% in 2017,
57.24% in 2016
5 Conclusion
Developed fuzzy mathematic model of
identification of emergent state allows estimating
the intensity of occurrence of positive emergent in
the course of development of social capital. The
study of the system of social capital
development in the emergent economy on the
example of Ukraine showed that the indicator of
the level of emergent social capital is formed on the
basis of sources of structural, cognitive, relational,
intellectual dimensions and dynamic processes of
development of the digital environment, which
promotes interaction and forms social network
connections. Application of fuzzy logic in
mathematic models of identification of the emergent
state allows to take into account the national
characteristics of the object of study and-traditional
and non-economic factors, at the same time, focuses
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
922
Volume 19, 2022
on social interaction in the professional activities of
the society.
References:
[1] Putnam R. D, Leonardi R., Nanetti R. J.
(2001) Creation of democracy. Traditions
of creating public activity in modern Italy.
K .: Fundamentals.
[2] Franco Fiordelisi, Giuseppe Galloppo,
Gabriele Lattanzio (2021) Where does
corporate social capital matter the most?
Evidence From the COVID-19 crisis.
Finance Research Letters,
https://doi.org/10.1016/j.frl.2021.102538
[3] Ramakrishna Devarakonda, Jeffrey J.
Reuer, Harsha Tadikonda (2022) Founder
social capital and value appropriation in
R&D alliance agreements. Research Policy
51, 104474.
https://doi.org/10.1016/j.respol.2022.10447
4.
[4] Gusak, N., Chernobrovkina, V., (2017).
Psychosocial support in emergencies:
resilience approach: teaching method.
manual. Nat. University "Kyiv-Mohyla
Academy". Kyiv: NaUKMA
[5] Horizon 2020. Ps2Share Participation,
Privacy, and Power in the Sharing
Economy.
URL:https://cordis.europa.eu/project/id/732
117
[6] Ulger K. (2018) The effect of problem-
based learning on the creative thinking and
critical thinking disposition of students in
visual arts education. Interdisciplinary
Journal of Problem-Based Learning, 12 (1).
URL: https://doi.org/10.7771/1541-
5015.1649
[7] Illiashenko, SM, Shipulina, Yu. S.,
Illiashenko NS, Komarnicka, G. A. (2017).
Knowledge management in the system of
organization's innovative development.
Marketing and Management of
Innovations, (1), 231–241.
https://doi.org/10.21272/mmi.2017.1-21.
[8] Hughes, M. (2018). Organizational
ambidexterity and firm performance:
burning research questions for marketing
scholars. Journal of Marketing
Management.
https://doi.org/10.1080/0267257X.2018.14
41175
[9] Voynarenko M., Dzhedzhula V.,
Yepifanova, I. (2016) Modelling the
process of making decisions on sources of
financing of innovation activity. Economic
AnnalsXXI, 160(7-8), рр. 126-129
[10] Voynarenko M., Hurochkina V.,
Dzhedzhula V., Yepifanova I. Yu.,
Menchynska О. (2021) Applying Fuzzy
Logic to Modeling Economic Emergence
WSEAS Transactions on Business and
Economics, Volume 18, pp. 424-434.
[11] Gurochkina V. V. (2020) Financial and
integration mechanisms of industrial
enterprises development in emergent
economy: author's ref. dis ... Dr. Econ.
Sciences: 08.00.04 / VV Gurochkina,
Khmelnitsky. nat. un-t. Khmelnytsky:
KhNU, 2020.
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
Vіacheslav Dzhedzhula has implemented model
design, data analysis, implementation of
modelling, methodology.
Hurochkina Viktoriya was responsible for
conceptualization, formal analysis,
methodology.
Iryna Yepifanova was the author of the idea,
structuring the factors, was responsible for
methodology
Anatoly Telnov was responsible for
conceptualization, methodology.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.80
Viacheslav Dzhedzhula,
Viktoriya Hurochkina,
Iryna Yepifanova, Anatoly Telnov
E-ISSN: 2224-2899
923
Volume 19, 2022
