=Paper=
{{Paper
|id=Vol-3048/paper000
|storemode=property
|title=Machine learning for prediction of emergent economy dynamics III
|pdfUrl=https://ceur-ws.org/Vol-3048/paper00.pdf
|volume=Vol-3048
|authors=Arnold E. Kiv,Vladimir N. Soloviev,Serhiy O. Semerikov,Hanna B. Danylchuk,Liubov O. Kibalnyk,Andriy V. Matviychuk,Andrii M. Striuk
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==Machine learning for prediction of emergent economy dynamics III==
https://ceur-ws.org/Vol-3048/paper00.pdf
Machine learning for prediction of emergent economy
dynamics
Arnold E. Kiv1 , Vladimir N. Soloviev2 , Serhiy O. Semerikov2,3,4,5 , Hanna B. Danylchuk6 ,
Liubov O. Kibalnyk6 , Andriy V. Matviychuk7 and Andrii M. Striuk3
1
Ben-Gurion University of the Negev, P.O.B. 653, Beer Sheva, 8410501, Israel
2
Kryvyi Rih State Pedagogical University, 54 Gagarin Ave., Kryvyi Rih, 50086, Ukraine
3
Kryvyi Rih National University, 11 Vitalii Matusevych Str., Kryvyi Rih, 50027, Ukraine
4
Institute of Information Technologies and Learning Tools of the NAES of Ukraine, 9 M. Berlynskoho Str., Kyiv, 04060,
Ukraine
5
University of Educational Management, 52A Sichovykh Striltsiv Str., Kyiv, 04053, Ukraine
6
The Bohdan Khmelnytsky National University of Cherkasy, 81 Shevchenko Blvd., Cherkasy, 18031, Ukraine
7
Kyiv National Economic University named after Vadym Hetman, 54/1 Peremogy Ave., Kyiv, 03680, Ukraine
Abstract
This is an introductory text to a collection of selected papers and revised from the M3E2 2021: 9th
International Conference on Monitoring, Modeling & Management of Emergent Economy, which held
in Odessa National University of Economics, Odessa, Ukraine, on the May 26-28, 2021. It consists of
introduction, conference review and some observations about the event and its future.
Keywords
dynamics of emergent markets in crisis and post-crisis period, econophysics, global challenges for
economic theory and practice in Europe, information systems and technologies in economics, innova-
tion models of economic development, modeling of hospitality sphere development, models of global
transformations, monitoring, modeling and forecasting in the banking sector, monitoring, modeling,
forecasting and preemption of crisis in socio-economic systems, risk management models in emergent
economy
M3E2-MLPEED 2021: The 9th International Conference on Monitoring, Modeling & Management of Emergent Economy,
May 26-28, 2021, Odessa, Ukraine
Envelope-Open kiv.arnold20@gmail.com (A. E. Kiv); vnsoloviev2016@gmail.com (V. N. Soloviev); semerikov@gmail.com
(S. O. Semerikov); abdanilchuk@gmail.com (H. B. Danylchuk); liubovkibalnyk@gmail.com (L. O. Kibalnyk);
editor@nfmte.com (A. V. Matviychuk); andrey.n.stryuk@gmail.com (A. M. Striuk)
GLOBE https://ieeexplore.ieee.org/author/38339185000 (A. E. Kiv); https://kdpu.edu.ua/personal/vmsoloviov.html
(V. N. Soloviev); https://kdpu.edu.ua/semerikov (S. O. Semerikov);
https://scholar.google.com.ua/citations?user=bfPE5scAAAAJ (H. B. Danylchuk);
https://scholar.google.com.ua/citations?user=tPw46YYAAAAJ (L. O. Kibalnyk);
https://kneu.edu.ua/en/depts9/k_ekon_matematychn_modeljuvannja/vykladachi_kmm/Matvijchuk.A.V/
(A. V. Matviychuk); http://mpz.knu.edu.ua/pro-kafedru/vikladachi/224-andrii-striuk (A. M. Striuk)
Orcid 0000-0002-0991-2343 (A. E. Kiv); 0000-0002-4945-202X (V. N. Soloviev); 0000-0003-0789-0272 (S. O. Semerikov);
0000-0002-9909-2165 (H. B. Danylchuk); 0000-0001-7659-5627 (L. O. Kibalnyk); 0000-0002-8911-5677
(A. V. Matviychuk); 0000-0001-9240-1976 (A. M. Striuk)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073
CEUR Workshop Proceedings (CEUR-WS.org)
i
1. Introduction
The development of human society, its various spheres of activity and functioning in recent
years is characterized by the emergence of new challenges and threats. Humanity is facing many
global problems of development of technology and the increasing scientific and technological
progress. In addition to the usual environmental and man-made disasters, financial crises, the
new ones appeared. The COVID-19 pandemic, for example. As a result, technologies and online
communication instruments began to develop at an increasing pace. The need to work and
study remotely has forced people to master new methods and tools of digital technology.
Due to the limited movement and transportation, as well as due to the reduction of produc-
tion and business closure, enterprises, regions, national economies and transnational capital
found themselves in a difficult situation. They experienced a decline in production and trade,
bankruptcy, reduced profitability, slower growth etc. This is just a small list of the effects of the
pandemic on the world economy.
The causes, mechanisms and consequences of such processes are of particular concern to
the scientific community, which is the first to try to understand the depth and importance of
these changes. This year’s theme of the International Conference on Monitoring, Modeling &
Management of Emergent Economy has especially relevant issues that experts of various fields
are trying to raise and solve in their works.
The authors’ attempt to find out the causes of the crisis and the possibility of using modern
ICT to solve existing problems or prevent economic, political and environmental threats, need to
be especially considered. The countries with emerging economies are particularly vulnerable to
new challenges, so participation in constructive scientific discourse is very important. Modern
challenges contribute to the search for new approaches to solving these problems.
In their research scientists focus on economic, financial security and sustainability of enter-
prises and regions; digitalization of all spheres of human life; modern methods of management
and marketing activities; development and analysis of the financial market and cryptocurrency
market; modeling and forecasting of international economic activity of various business entities;
especially relevant methods of machine learning and fuzzy logic; solving the problems of various
sectors of the economy of Ukraine and other countries, especially countries with emerging
economies.
The subject of the works included in the proceedings it necessary to search for a new scientific
paradigm in a constantly changing environment. After all, new challenges and threats are a
certain stimulus for the development of scientific thought. We expect that the research of the
participants of this conference will be useful for scientists, teachers, students and representatives
of the business community.
1.1. M3E2 2021 at a glance
The Monitoring, Modeling & Management of Emergent Economy (M3E2, https://m3e2.
ccjournals.eu/2021/) is a peer-reviewed international conference focusing on research advances
and applications of nonlinear dynamics methods, econophysics and complex systems methodol-
ogy of emergent economy.
ii
The M3E2 Conference occupies contributions in all aspects of
Computational Finance, Economics, Risk Management, Statistical
Finance, Trading and Market Microstructure, (Deep) Machine
Learning technologies and tools, paradigms and models, relevant
to modern financial engineering and technological decisions in
the modern age. There is urgent general need for principled
changes in postclassic economy elicited by current models, tools,
services, networks and IT communication.
Figure 1: M3E2 2021 logo.
M3E2 2021 topics of interest since 2019 [1, 2]:
• Complex cyberphysical systems, synergy, econophysics, economy of agents
• Dynamics of emergent markets in crisis and post-crisis period
• Economic security
• Global challenges for economic theory and practice in Europe
• Information systems and technologies in economics
• Innovation models of economic development
• Machine learning for prediction of emergent economy dynamics
• Management of the state’s economic safety and economic safety of economic agents
• Methods and models of artificial intelligence in economic systems
• Modeling of hospitality sphere development
• Models of global transformations
• Monitoring, modeling and forecasting in the banking sector
• Monitoring, modeling, forecasting and preemption of crisis in socio-economic systems
• Optimal management of socio-economic processes
• Risk management models in emergent economy
This volume contains the selected and revised papers presented at M3E2 2021: 9th Interna-
tional Conference on Monitoring, Modeling & Management of Emergent Economy held on May
26-28, 2021 in Odessa, Ukraine.
There were 45 submissions. Each submission was reviewed by at least 3, and on the average
3.1, program committee members. 11 papers were accepted for this volume as regular papers.
1.2. M3E2 2021 reviewers
Dr. George Abuselidze, Professor of Economics and Busi-
ness, Department of Finance, Banking and Insurance, Ba-
tumi Shota Rustaveli State University, Batumi, Georgia.
George Abuselidze, from the Batumi Shota Rustaveli State
University (in 2001) and Ivane Javakhishvili Tbilisi State
University, Georgia, in 2005, and a Doctor of Economics
Sciences degree (Dr. habil.) from the National Academy of
Sciences of Georgia, in 2005. Since 2002, he has been work-
ing in the Finance and Banking at the Ivane Javakhishvili
Tbilisi State University, since 2006 - Batumi Shota Rustaveli
iii
State University where he is currently Head department of Finance, Banking and Insurance.
His research interests include Economics, Econometrics, Finance and Social Sciences (miscella-
neous). He has published a number of papers in international journals and volumes in book
series, is a member of editorial or/and review boards of Oeconomia Copernicana, Journal of
Financial Economic Policy, International Journal of Economics and Finance, journal of Science
and studies of accounting and finance: problems and perspectives, Management Studies and
etc. He also played instrumental role in different prestigious internal collaborative research
project with USA, Canada, Lithuania, Poland, Ukraine, Turkey and etc.
WWW: https://orcid.org/0000-0002-5834-1233
E-mail: george.abuselidze@bsu.edu.ge
Prof. Dr. Vitalina Babenko is Professor (Full) of Interna-
tional E-commerce and Hotel&Restaurant Business Depart-
ment, V. N. Karazin Kharkiv National University (Ukraine),
Dr. Sci. (habil.) in Economics, PhD in Technical Sciences.
Her sphere of scientific interests includes the manage-
ment of innovation processes, economic-mathematical mod-
elling, information systems and technologies. She has pub-
lished around 300 papers in peer-reviewed journals and in
the proceedings of conferences. She has taken part in more
than 100 conferences and workshops as a Chair, Keynote
Speaker, member of the Scientific Program Committee, an
Organizer and Session Chair. She is Editor-in-Chief of Jour-
nal of International Relations, Economics, Country Studies,
Tourism; International Journal of Economics and Manage-
ment Systems and member of editorial board of some sci-
entific journals. She is the Member of Doctoral Academic
Councils in Economics, Expert of the Ministry of Educa-
tion of Ukraine and Expert of Ukrainian Institute Scientific
Technical Information. Council many national and international informatics associations.
WWW: http://international-relations-tourism.karazin.
ua/Babenko
E-mail: vitalinababenko@karazin.ua
Dr. Oleksandr Chernyak was the Professor, Head of
Economic Cybernetics Department, Taras Shevchenko Na-
tional University of Kyiv
WWW: http://science.univ.
kiev.ua/en/researchgroups/
research.php?ELEMENT_ID=
2594
Dr. Hanna Danylchuk, Associate Professor of the De-
partment of Economics and Business Modeling, The Bohdan
iv
Khmelnytsky National University of Cherkasy, Cherkasy, Ukraine.
Hanna Danylchuk, born in 1969, received her PhD in
Economics (East European University of Economics and
Management) in 2015. Since 2006 she has been working
in the field of economic systems modeling at The Bohdan
Khmelnytsky National University of Cherkasy. Research
interests: modeling of crisis phenomena in financial mar-
kets. She has published a number of papers in international
journals.
E-mail: abdanilchuk@gmail.com
Dr. Irina Georgescu, Lecturer of Computational In-
telligence, Department of Informatics and Economic Cy-
bernetics, Bucharest University of Economics, Bucharest,
Romania.
Irina GEORGESCU holds a PhD in Economics from Turku
Centre for Computer Science, Turku, Finland. Currently
she is a lecturer at the Department of Economic Informatics
and Cybernetics, Bucharest Academy of Economic Studies.
Her research interests lie in the areas of fuzzy economics,
computational intelligence and econometrics. She is the
author of about 40 journal papers and 2 books published in
Springer Verlag.
E-mail: irina.georgescu@csie.ase.ro
Dr. Lidiya Guryanova, PhD, Doctor of Economics (Ha-
bilitation in Economics), Associate Professor, professor of
Economic Cybernetics Department, Simon Kuznets Kharkiv
National University of Economics.
Coordinator of the Master’s program “Assessment, anal-
ysis and forecasting of socio-economic processes” in the
specialty 8.18010024 “Applied Economics”, a member of the
Ukrainian Association of Economic Cybernetics, a reviewer
of the journals “Economics of Development” (Ukraine),
“Mathematical Problems in Engineering” (USA), Head of
Section, a member of the program, organizational and tech-
nical committees of international scientific-practical confer-
ence “Modern problems of modelling the socio-economic
systems” (Ukraine, Slovenia, Poland, the USA, Bulgaria), “Innovation and information technol-
ogy in the development of business and education” (Russian Federation, Ukraine, Germany,
Bulgaria, France), scientific director of training of highly qualified personnel (specialty 08.00.11
– mathematical methods, models and information technology in the economy).
WWW: https://ek.hneu.edu.ua/en/professors/guryanova-l-s/
E-mail: guryanovalidiya@gmail.com
v
Dr. Alexey Hostryk, Odessa National Economic Univer-
sity, Ukraine.
WWW: https://orcid.org/0000-0002-5834-1233
E-mail: AlexeyGostrik@gmail.com
Dr. Pavlo Hryhoruk, Professor of Department of Auto-
mated Systems and Modeling in Economics of Khmelnytskyi
National University, Khmelnytskyi, Ukraine.
Pavlo Hryhoruk, received a Doctor of Economic Sciences
degree (Dr. habil.) from the Khmelnytskyi National Univer-
sity, in 2013. Since 1997, he has been working in the field of
economic and mathematical modeling at the Khmelnytskyi
National University, where he is currently Head of Depart-
ment of Automated Systems and Modeling in Economics.
Directions of studies are related to decision-making, mul-
tidimensional modeling of socio-economic systems, com-
prehensive assessment of economic phenomena latent char-
acteristics, financial security, sustainable development, in-
formation technologies in education. He has published a
number of papers in domestic and international journals,
monographs and volumes in book series. Since Decem-
ber 2020 he is Editor-in-Chief of Herald of Khmelnytskyi
National University. Economic Sciences.
E-mail: violete@ukr.net, hryhoruk@khnu.km.ua
Dr. Serhii Hushko, State University of Economics and
Technology, Ukraine.
WWW: https://www.duet.edu.ua/en/persons/12
E-mail: gushko77@gmail.com
Dr. Nila Khrushch, Professor, Head of Department of
Finance, Banking and Insurance of Khmelnytskyi National
University, Khmelnytskyi, Ukraine.
Nila Khrushch, received a Doctor of Economic Sciences
degree (Dr. habil.) from the Institute of Market Prob-
lems and Economic & Ecological Researched of National
Academy of Sciences of Ukraine, Odesa in 2007. Since 1993,
she has been working in the field of innovation-investment
and strategic management at the Khmelnytskyi National
University, where she is currently Head of Department of Finance, Banking and Insurance.
Area of studies includes financial and economic research and modeling of business entities
activity, financial security, sustainable development, strategic and financial management. She
has published a number of papers in domestic and international journals, monographs and
vi
volumes in book series, is a member of editorial board of Herald of Khmelnytskyi National
University. Economic Sciences.
E-mail: nila.ukr@gmail.com, khrushch@khnu.km.ua
Dr. Liubov Kibalnyk, Head and Professor of Depart-
ment of Economics and Business Modelling, Cherkasy Bo-
hdan Khmelnytsky National University, Cherkasy, Ukraine.
Liubov Kibalnyk, born in 1969, received a Candidate
of Economic Sciences degree (Dr. phil.) from the Taras
Shevchenko National University of Kyiv, Ukraine, in 2002,
and a Doctor of Economic Sciences degree (Dr. habil.) from
the Institute of International Relations of Taras Shevchenko
National University of Kyiv, in 2015. Since 1994, she has
been working in the field of economics, international eco-
nomic relations and modeling at the Cherkasy Bohdan
Khmelnytsky National University, where he is currently
Head of Department.
She specialized in the field of modeling economic pro-
cesses in the global environment. She is the author of more
than 150 scientific and methodological works published in
international and national editions.
WWW: http://econom-law.cdu.edu.ua/?page_id=804
E-mail: liubovkibalnyk@gmail.com
Dr. Arnold Kiv, Ben-Gurion University of the Negev,
Israel.
Arnold Kiv received the D. Sc. (Dr. Hab.) degree in
solid state physics from Tartu Institute of Physics, Tartu,
Estonia, in 1978. From 1964 to 1982, he was a Senior
Researcher and a Head of the Laboratory of Radiation
Effects, Institute of Nuclear Physics, Academy of Sciences,
Tashkent, Uzbekistan. From 1983 to 1998, he was a Head
of the Department of Theoretical Physics, South-Ukrainian
National Pedagogical University, Odessa, Ukraine. In
1997, he was an Invited Professor, Western Ontario
University, Canada. From 1999 to the present, he is a
Professor-Researcher in the Department of Materials
Engineering, Ben-Gurion University of the Negev, Israel. In
1996 and 2011 he was co-Director of NATO Advanced research Workshops and an Editor of
two NATO Series books. He has about 200 publications, three monographs and three Invention
Certificates in the field of radiation effects in solid state electronics. His research interests
include mechanisms of formation of radiation defects in solids, interaction of fast particles with
materials, radiation methods in microelectronics, including computer simulation, analytical
calculations and experimental studies.
vii
PhD of Public Administration, Oksana Kovtun, asso-
ciate professor, Department of Public Administration and
Project Management, State Higher Educational Institution
“University of Educational Management”, Kyiv, Ukraine.
Oksana Kovtun, born in 1971, received a Candidate of
Public Administration degree (Dr. phil.) from the Council
for the Study of Productive Forces of Ukraine at the National
Academy of Sciences of Ukraine, Ukraine, in 2010. Since
2000, she has been working in the field of public finance
research, household financial behavior and mechanisms for
their activation in Classic Private University (Zaporizhzhia).
I am currently an associate professor at the Department
of Public Administration and Project Management, State
Higher Educational Institution «University of Educational
Management». Shies research interests: modeling of finan-
cial markets, study of structural changes in the economy,
innovations in the financial sector. She has published a
number of papers in international journals and workshops.
WWW: http://umo.edu.ua/institutes/imp/
struktura-institutu/kaf-upravl-proekt/sklad/
kovtun-oksana-anatolijivna
E-mail: kovtun.oa71@gmail.com
Dr. Hanna Kucherova, Professor of economy, Depart-
ment of Economy, Classic Private University, Zaporizhzhia,
Ukraine.
Hanna Kucherova, born in 1983, received a Candidate of
Economical Sciences degree from the Classic Private Univer-
sity, in 2011, and a Doctor of Economical Sciences degree (Dr.
habil.) from the Classic Private University, in 2017. Since
2008, she has been working in the field of pricing, economy,
tax, economy behavior at the Classic Private University
of Ukraine, where he is currently professor Chair of Eco-
nomics. Her research interests include modeling the coun-
try’s business climate, behavior of socio-economic agents,
tax consciousness and information transparency.
WWW: https://scholar.google.ru/citations?user=
FhBOVExn1foC
E-mail: kucherovahanna@gmail.com
Dr. Serhii Lehenchuk, head of the department of man-
agement information systems and accounting, Zhytomyr
Polytechnic State University, Zhytomyr, Ukraine.
viii
Serhii Lehenchuk, born in 1981, received a Candidate of Economic Sciences degree (Dr.
phil.) from the National Agrarian University, Kyiv, Ukraine, in 2006, and a Doctor of Economic
Sciences degree (Dr. habil.) from the Zhytomyr State Technological University, in 2011. Since
2004, he has been working in the field of accounting and information systems at the Zhytomyr
Polytechnic State University. His research interests include general accounting theory, positive
accounting theory and accounting choice, intangible assets accounting, corporate and integrated
reporting. He has published a number of papers in international and Ukrainian journals, is a
member of editorial boards of “Economics, Management and Administration”, “Problems of
Theory and Methodology of Accounting, Control and Analysis”, “Socio-Economic Research
Bulletin”, “Public Policy and Accounting”.
WWW: https://ztu.edu.ua/ua/structure/faculties/fbso/bok.php
E-mail: legenchyk2014@gmail.com
Dr. Nataliia Maksyshko, Doctor of Economic Sciences,
Professor, Head of Department of Economic Cybernetics,
Professor, Zaporizhzhia National University, Zaporizhzhia,
Ukraine.
Nataliia Maksyshko, received a Candidate in Physics and
Mathematics Sciences degree (Dr. phil.) from the V.M.
Glushkov Institute of Cybernetics of National Academy
of Sciences of Ukraine, in 1990 (Mathematical modeling
and computational methods), and a Doctor of Economics
Sciences degree (Dr. habil.) (Economic and mathemati-
cal modeling) from the Kyiv National Economic University
named after Vadym Hetman, in 2010. Since 1983, she has
been working in the field of economic and mathematical
modeling at the Zaporizhzhia National University, where
she is currently Head of Department of Economic Cyber-
netics. Her research interests include economic and math-
ematical modeling of complex economic systems, economic
dynamics, discrete optimization, information technology in
economics and education. She has published a number of papers in international journals and
volumes in book series, is a member of editorial board of Bulletin of Zaporizhzhia National
University. Economic sciences.
E-mail: maxishko@ukr.net
Dr. Andriy Matviychuk, Professor of Economic and
Mathematical Modeling, Kyiv National Economic University
named after Vadym Hetman, Kyiv, Ukraine.
Andriy Matviychuk, born in 1978, became a Candidate
of Science in Economics (PhD) by specialty Economic and
Mathematical Modelling at the Technological University of
Podillia (Khmelnitskiy) in 2003, and a Doctor of Economics
(DSc) with a degree in Mathematical Methods, Models and
ix
Information Technologies in Economics at the Kyiv National Economic University named after
Vadym Hetman in 2008.
Since 1990 he has been working in the field of AI & ML at the Kyiv National Economic Univer-
sity named after Vadym Hetman, where he is currently professor of Economic and Mathematical
Modeling Department, director of Institute of Modeling and Informational Technologies in
Economics and CEO at KNEU Science Park. His research interests cover the field of mathemat-
ical modeling of complex systems, primarily using tools of neural networks and fuzzy logic.
He is a Chief Editor of scientific and analytical journal Neuro-Fuzzy Modeling Techniques in
Economics and a member of editorial boards of a number of scientific journals.
WWW: https://kneu.edu.ua/ua/depts9/k_ekon_matematychn_modeljuvannja/vykladachi_
kmm/Matvijchuk.A.V/
E-mail: editor@nfmte.com
Dr. Inese Mavlutova, Professor (Full) at Department of
Economics and Finance, BA School of Business and Finance,
Latvia.
E-mail: inese.mavlutova@ba.lv
Dr. Iveta Mietule, Rector of Rezekne Academy of Tech-
nologies, Latvia, Professor of Economics.
Iveta Mietule was born in 1972 in Latvia. Received her
PhD in Economics from University of Latvia in 2009. Mem-
ber of the Association of University Professors of Latvia,
professor of Rezekne Academy of Technologies, member of
the Senate of RTA, expert of the Latvian Council of Science
in the field of Economic and Management Sciences. Author
of more than 50 publications, 3 monographs. Participant
and contributor of more than 15 projects and programmes,
included FRONTEX, ERDF, ESF, INTERREG, ERASMUS and
the Latvian National Research Programme. International
experience of organizing and participating in more than 50
events (conferences, lectures, seminars etc.).
WWW: https://orcid.org/0000-0001-7662-9866
E-mail: iveta.mietule@rta.lv, mietule@inbox.lv
Dr. Dariusz Pawliszczy, Mayor of Gromadka, Poland.
E-mail: pawliszczy@interia.pl
Dr. Oleg Pursky, Professor of Computer Science and
Information Systems, Head of Department of Computer
Science and Information Systems, Kyiv National University
of Trade and Economics, Kyiv, Ukraine.
Oleg Pursky, born in 1967, received a Candidate of Sci-
ences in Physics and Mathematics degree (Dr. phil.) from
x
the Institute for Low Temperature Physics and Engineering of the National Academy of Sciences
of Ukraine, in 2001, and a Doctor of Sciences in Physics and Mathematics degree (Dr. habil.)
from the Taras Shevchenko National University of Kyiv, Ukraine, in 2010.
His research interests include informational systems de-
velopment, computer simulation and modeling of socio-
economic systems. He has published a number of papers
in international journals, monographs and volumes in book
series, is a member of editorial board of International Jour-
nal of Economic Theory and Application, reviewer of sci-
entific journals International Journal of Modern Physics
(B) and Heat Transfer and certified Data Science&Machine
Learning specialist. He is a member of Scientific Council
section of Ukrainian Ministry of Education and Science on
the specialty “Informatics and Cybernetics”. Currently, he
is working as a Head of Department of Computer Science
and Information Systems, Kyiv National University of Trade
and Economics.
WWW: https://knute.edu.ua/blog/read/?pid=12695&uk
E-mail: Pursky_O@ukr.net
Dr. Sultan Ramazanov, Kyiv National Economic Uni-
versity named after Vadym Hetman, Ukraine.
Born 12/13/1949. Mathematician, cybernetic, envi-
ronmental economist; design specialist and development
of integrated management information systems complex
ecological-economic objects with elements of artificial in-
telligence. Professor, Doctor of Engineering, Doctor of Eco-
nomics Science, Honored Worker of Science and Technol-
ogy of Ukraine. Honored Worker of Education of Ukraine.
Excellence in education of Ukraine. Professor of the De-
partment ”Information systems in the economy” of Kyiv
National Economic University named after Vadym Hetman.
Professor Emeritus of East Ukrainian National University
named after V. Dahl and Poltava University of Economics
and Trade. Prepared 1 DSc and 14 PhDs (7 scientific fields).
He is the author of 495 scientific and methodological works,
including 41 monographs and 14 textbooks. Expert of the
Ministry of Education and Science of Ukraine (“Informatics
and Cybernetics”). Academician of Academies: International Academy of Informatics, The In-
ternational Academy of Environmental Sciences and Life Safety, The Academy of Technological
Sciences of Ukraine, the Academy of Economic Sciences of Ukraine, Transport Academy of
Ukraine. Total work experience in Ukrainian universities - 47 years (since 1973). 28 years – head
of the department and at the same time 13 years – dean of the faculty (EUNU named after V.
Dahl, Luhansk and Severodonetsk) ([)from 1973 to 2014). Since 2014 - Professor of Departments
xi
at PUET (Poltava) and KNEU (Kyiv).
E-mail: sramazanov@i.ua, sultan.ramazanov@kneu.edu.ua
Dr. Serhiy Semerikov, Professor of Computer Science
and Educational technology, Kryvyi Rih State Pedagogical
University, Ukraine.
Serhiy Semerikov is professor of Department of Com-
puter Science and Applied Mathematics at Kryvyi Rih State
Pedagogical University. He got both PhD and DSc in edu-
cation (informatics) from the National Pedagogical Drago-
manov University in 2001 and 2009, respectively. The main
directions of Dr. Semerikov’ research is methods of learning
and educational technology.
WWW: https://kdpu.edu.ua/semerikov/
E-mail: semerikov@gmail.com
Dr. Nadiia Shmygol, Professor of Management Depart-
ment, National University “Zaporizhzhia Polytechnic”, Za-
porizhzhia, Ukraine.
Nadiia Shmygol, born in Pavlodar city in Kazakhstan
1972. In 2005 defended a thesis and obtained a diploma of
Candidate of Sciences (comparable to the academic degree
of Doctor of Philosophy, Ph.D.) Economics in Economic
and Mathematical Modeling. In 2013 defended a thesis
and obtained a diploma of Doctor of Sciences in Economy
and Management of enterprises. Certificate of professor
of Accounting and Audit Department (2014). Author of
over 200 scientific and practical publications in the field of
economics and management.
Sphere of scientific interests: management accounting,
CSR, sustainable development, circular economy, sustain-
able marketing, resource-efficient production, decision-
making methods, environmental management.
WWW: https://zp.edu.ua/nadiya-mikolayivna-shmigol
E-mail: nadezdashm@gmail.com
Dr. Kateryna Shymanska, Head of the Department, De-
partment of Digital Economy and International Economic
Relations, Zhytomyr Polytechnic State University, Zhyto-
myr, Ukraine.
Kateryna Shymanska, born in 1985, received a Candidate
of Economic Sciences degree (Dr. phil.) from the Zhytomyr
State Technological University, Ukraine, in 2010, and a Doc-
tor of Economic Sciences degree (Dr. habil.) from the Vasyl’
xii
Stus Donetsk National University, in 2019. Since 2014, she has been working in the field of
international economic relations at the Zhytomyr Polytechnic State University, where she is
currently Head of the Department of Digital Economy and International Economic Relations.
Her research interests include international migration consequences and regulation, but also
international trade and the challenges of the digital economy. She has published a number of
papers on the specified problems.
WWW: https://ztu.edu.ua/ua/structure/faculties/fbso/kme.php
E-mail: kv.shymanska@gmail.com
Vladimir N. Soloviev received the D. Sc. (Dr. Hab.)
degree in solid state physics from Institute of Physics of
the National Academy of Sciences of Ukraine, in 1993.
From 1992 to 2000 and from 2016 to the present head of
the Department of Informatics and Applied Mathematics
of Kryvyi Rih State Pedagogical University. In the period
from 2000 to 2016, he carry out research on critical and
crisis phenomena in the financial markets at various
universities in Kyiv, Cherkasy and Kryvyi Rih. He has
about 300 publications in the field of solid state physics,
complex systems and quantitative methods of constructing
precursors of crisis phenomena in systems of different
nature.
Dr. Victoria Solovieva, Associate Professor, Head of
Department, State University of Economics and Technology,
Ukraine.
She graduated from the Faculty of Physics and Mathemat-
ics of the Kryvyi Rih Pedagogical Institute. She has a Ph.D.,
specializing in Economic and Mathematical Modeling. He
has about 130 publications in the field of complex systems
and quantitative methods for constructing precursors of
crisis phenomena in systems of various nature.
E-mail: vikasolovieva2027@gmail.com
Dr. Galyna Velykoivanenko, Head of the Economic
and Mathematical Modeling Department, Kyiv National
Economic University named after Vadym Hetman, Ukraine.
E-mail: ivanenko@kneu.edu.ua
Dr. Eugene Yakub, Professor of Economic Information
and Computer Technology, Department of Economic Cy-
bernetics and Information Technology, Odessa National
Economic University, Odessa, Ukraine.
xiii
Eugene Yakub, born in 1946, received a Candidate of Tech-
nical Sciences degree (Dr.Phil.) from the Odessa Technolog-
ical Institute of Refrigeration, USSR, in 1973, and a Doctor
of Physical and Mathematical Sciences degree (Dr. habil.)
from the Institute of High Temperatures of the Academy of
Sciences of USSR, in 1990. Since 1977, he has been working
in the field of mathematical and computer modelling at the
Odessa National Economic University, where he is currently
head of Department of Economic Cybernetics and Informa-
tion Technology. His research interests include modelling
and computer simulation of various complex natural and
economic systems. He has published a number of papers in
international journals and monographs, is a member of several Academic Councils.
WWW: http://oneu.edu.ua/ru/yakub-yevgen-solomonovich
E-mail: yakub@oneu.edu.ua
Oleh Yatsiuk, Department of Economics and Manage-
ment Theory, Ivano-Frankivsk National Technical Univer-
sity of Oil and Gas, Ivano-Frankivsk, Ukraine.
Oleh Yatsiuk, born in 1978, received a Master degree in
Economics from the Ivano-Frankivsk National Technical
University of Oil and Gas, in 2000. Since 2001, he has been
working in the field of enterprise’ financial sanation at the
Ivano-Frankivsk National Technical University of Oil and
Gas. His research interests include finances of the enter-
prise, anti-crisis management and HR management. He has
more than 200 published scientific and educational works,
including monographs, textbooks, papers in domestic and
international journals.
WWW: https://nung.edu.ua/person/
yacyuk-oleg-stepanovich-0
E-mail: olegstya@gmail.com
Dr. Nataliia Zachosova, Professor of Management and
Economic Security Department, Bohdan Khmelnytsky Na-
tional University of Cherkasy, Cherkasy, Ukraine.
Nataliia Zachosova, born in 1986, received a Candidate
of Economic Sciences degree (Dr. phil.) in 2011, and a Doc-
tor of Economic Sciences degree (Dr. habil.) in 2017. In
2018 she received the Scholarship of the Cabinet of Minis-
ters of Ukraine for Young Scientists (and in 2020 she got it
once again) and in 2019 ‒ the Nominal Scholarship of the
Verkhovna Rada of Ukraine for the Most Talented Young
Scientists. Since 2014, she has been working in the field of
xiv
financial and economic security management at the Bohdan Khmelnytsky National University
of Cherkasy, where she is currently Professor and the Chairman of the Council of Young Sci-
entists. Her research interests include security oriented management, strategic and personnel
management. She has published a number of papers in international journals and volumes in
book series, is a member of editorial boards of Bulletin of the Cherkasy Bohdan Khmelnytsky
National University, Series “Economic Sciences”.
WWW: https://orcid.org/0000-0001-8469-3681
E-mail: natazachosova@gmail.com
Dr. Pavel Zakharchenko, Professor of Economic Cyber-
netics, Head of Department of Economic Cybernetics and Fi-
nances, Berdyansk State Pedagogical University, Berdyansk,
Ukraine.
Pavel Zakharchenko, born in 1957, received a Candidate
of Technical Sciences (Dr. phil.) from the Kharkov Insti-
tute of Radio Electronics, USSR, in 1982, and a Doctor of
Economical Sciences degree (Dr. habil.) from the Kiev Na-
tional Economic University of Ukraine, in 2010. Since 2000,
he has been working in the field of finance and economic
cybernetics at the Berdyansk State Pedagogical University,
where he is currently Head of Department of Economic
Cybernetics and Finances. His research interests include
health economics models, chaos and catastrophe theory. He
has published a number of articles in international journals
and volumes in book series, and is a member of the editorial
board of scientific journals.
WWW: https://bdpu.org.ua/en/faculties/gef/
structure-gef/kaf-fin/composition-kaf-fin/zaharchenko/
E-mail: pvzz1957@gmail.com
2. Articles overview
The aim of the article “Innovative behavior of bitcoin market agents during COVID-19: re-
currence analysis” [3] by Hanna Yu. Kucherova, Vita O. Los, Dmytro V. Ocheretin, Olha V.
Bilska and Evgenia V. Makazan (figure 2) is to study the series of the dynamics of the price
of bitcoin and the frequency of online requests for bitcoin as an indicator of the behavior of
agents of the digital economy using the methods of qualitative recurrent analysis. The types of
constructed time series plots of the price of bitcoin and the frequency of requests for bitcoin are
defined as drift with a superimposed linearly gradually increasing sequence, which indicates
the unpredictability of the behavior of digital economy agents with a gradual stabilization in
new quality trend. The scientific novelty of the research results lies in the proven connection
between the series of bitcoin price dynamics and the frequency of online requests for bitcoin,
xv
tracking changes in the behavior of digital economy agents before and after the introduction of
quarantine restrictions. The procedure for conducting a qualitative recurrence analysis of the
series of dynamics is generalized, which takes into account the specifics of the formation of the
frequency of online requests for bitcoin, the price and the behavioral aspect of its formation.
The practical value lies in defining the characterization of the behavior model of digital economy
agents under conditions of quarantine restrictions. The behavior of digital economy agents in
the context of COVID-19 requires further research, in particular, using cross-recurrent analysis
methods.
This article highlights further research by the authors, begun in [4, 5, 6, 7, 8, 9, 10].
Figure 2: Presentation of paper [3].
The article “Comparative analysis of the stock quotes dynamics for IT and the entertainment
industry companies based on the characteristics of memory depth” [11] by Nataliia K. Maksyshko
and Oksana V. Vasylieva (figure 3) is devoted to the study and comparative analysis of the stock
quotes dynamics for the world’s leading companies in the IT sector and the entertainment
industry. Today, these areas are developing the fastest and most powerful, which attracts
the attention of investors around the world. This is due to the rapid development of digital
communication technologies, the growth of intellectualization and individualization of goods
and services, and so on. These spheres have strong development potential, but the question to
how their companies’ stock quotes respond to the impact of such a natural but crisis phenomenon
as the COVID-19 pandemic remains open. Based on the nonlinear paradigm of the financial
markets dynamics, the paper considers and conducts a comprehensive fractal analysis of the
quotations dynamics for six leading companies (Apple Inc., Tesla Inc., Alphabet Inc., The Walt
Disney Company, Sony Corporation, Netflix) in this area before and during the COVID-19
pandemic. As a result of the application of the rescaled range analysis (R/S analysis), the
presence of the persistence property and long-term memory in the stock quotes dynamics for
all companies and its absence in their time series of profitability was confirmed. The application
xvi
of the method of sequential R/S analysis made it possible to construct fuzzy sets of memory
depths for the considered time series and to deepen the analysis of the dynamics due to the
quantitative characteristics calculated on their basis. Taking into account the characteristics
of memory depth in the dynamics of quotations made it possible to conduct a comparative
analysis of the dynamics, both under the influence of the natural crisis situation and in terms of
investing in different terms. The peculiarities of the delayed profitability dynamics of quotations
for each of the companies are also taken into consideration and compared. The developed
recommendations can be used in investment activities in the stock market.
This article highlights further research by the authors, begun in [12, 13, 14].
Figure 3: Presentation of paper [11].
Cryptocurrencies refer to a type of digital asset that uses distributed ledger, or blockchain
technology to enable a secure transaction. Like other financial assets, they show signs of complex
systems built from a large number of nonlinearly interacting constituents, which exhibits
collective behavior and, due to an exchange of energy or information with the environment,
can easily modify its internal structure and patterns of activity. The article “Econophysics of
cryptocurrency crashes: a systematic review” [15] by Andrii O. Bielinskyi (figure 4), Oleksandr
A. Serdyuk, Serhiy O. Semerikov and Vladimir N. Soloviev review the econophysics analysis
methods and models adopted in or invented for financial time series and their subtle properties,
which are applicable to time series in other disciplines. Quantitative measures of complexity
have been proposed, classified, and adapted to the cryptocurrency market. Their behavior in
the face of critical events and known cryptocurrency market crashes has been analyzed. It has
been shown that most of these measures behave characteristically in the periods preceding the
critical event. Therefore, it is possible to build indicators-precursors of crisis phenomena in the
cryptocurrency market.
xvii
This article highlights further research by the authors, begun in [16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33].
Figure 4: Presentation of paper [15].
The focus of the article “Irreversibility of financial time series: a case of crisis” [34] by Andrii
O. Bielinskyi, Serhii V. Hushko (figure 5), Andriy V. Matviychuk, Oleksandr A. Serdyuk, Serhiy O.
Semerikov and Vladimir N. Soloviev to measure the varying irreversibility of stock markets. A
fundamental idea of this study is that financial systems are complex and nonlinear systems that
are presented to be non-Gaussian fractal and chaotic. Their complexity and different aspects of
nonlinear properties, such as time irreversibility, vary over time and for a long-range of scales.
Therefore, this work presents approaches to measure the complexity and irreversibility of the
time series. To the presented methods authors include Guzik’s index, Porta’s index, Costa’s
index, based on complex networks measures, Multiscale time irreversibility index and based on
permutation patterns measures. This study presents that the corresponding measures can be
used as indicators or indicator-precursors of crisis states in stock markets.
This article highlights further research by the authors, begun in [35, 36, 37].
The article “Big Data based marketing forecasting” [38] by Sergey M. Ivanov and Mykola M.
Ivanov (figure 6) discusses the use of big data as a tool to increase data transfer speed while
providing access to multidimensional data in the process of forecasting product sales in the
market. In this paper discusses modern big data tools that use the MapReduce model. The big
data presented in this article is a single, centralized source of information across your entire
domain. In the paper also proposes the structure of a marketing analytics system that includes
many databases in which transactions are processed in real time. For marketing forecasting
of multidimensional data in Matlab, a neural network is considered and built. For training
and building a network, it is proposed to construct a matrix of input data for presentation in a
neural network and a matrix of target data that determine the output statistical information.
xviii
Figure 5: Presentation of paper [34].
Input and output data in the neural network is presented in the form of a 5x10 matrix, which
represents static information about 10 products for five days of the week. The application of
the Levenberg-Marquardt algorithm for training a neural network is considered. The results
of the neural network training process in Matlab are also presented. The obtained forecasting
results are given, which allows us to conclude about the advantages of a neural network in
multivariate forecasting in real time.
This article highlights further research by the authors, begun in [39, 40, 41].
The article “Fuzzy model for complex risk assessment of an enterprise investment project” [42]
by Inna I. Chaikovska, Pavlo M. Hryhoruk and Maksym Yu. Chaikovskyi (figure 7) proposes
an economic-mathematical model for determining a comprehensive risk assessment of the
investment project of the enterprise which are based on the approaches of A. Nedosekin. The
model is built using fuzzy logic and takes into account the probability of occurrence of each of
the identified risks and the level of impact of each of them on the project. The probability of
risk is set by experts in the form of points and converted into linguistic terms, and the level of
influence of each of them on the project – the ratio of benefits and is determined using Fishburne
scales. The proposed Project Risk Model consists of the following stages: formation of initial
data using expert opinions; construction of a hierarchical project risk tree; determination of
weight coefficients (Fishburne weights) of project risks; selection and description of membership
function and linguistic variables; conversion of input data provided by experts from a score scale
into linguistic terms; recognition of qualitative input data on a linguistic scale; determination
of a complex indicator of investment project risks; interpretation of a complex indicator. The
developed model allows managing the risks of the project to maximize the probability of its
successful implementation, to compare alternative projects and choose less risky, to minimize
the level of unforeseen costs of the project.
xix
Figure 6: Presentation of paper [38].
This article highlights further research by the authors, begun in [43, 44, 45, 46].
The article “Modeling structural changes in the regional economic development of Ukraine
during the COVID-19 pandemic” [47] by Pavlo M. Hryhoruk (figure 8), Nila A. Khrushch and
Svitlana S. Grygoruk investigates the issues of evaluating structural changes in the regions’
economic development based on the comprehensive index assessment technology. The impact
of the COVID-19 pandemic on regional development and changes in the regional structure is
considered. The authors propose the use of block convolution to design a comprehensive index
based on a set of metric initial indicators that characterize the regions’ economic development.
Grouping the set of initial indicators is carried out based on the method of an extreme grouping
of parameters and the method of principal components. A weighted linear additive convolution
was used to develop partial composite indices and an economic development comprehensive
index. The practical approbation was carried out for the regions of Ukraine according to the data
of 9 months of 2019 and the same period of 2020. To establish the regions’ structure, authors
used the division of the comprehensive index values into intervals and further distributing
regions into classes according to the level of economic development. There is a general decrease
in the value of the integrated indicator in 2020, caused by the impact of the COVID-19 pandemic.
However, no significant changes in the structure of the regions were detected, which indicates
an equally negative impact of the pandemic for all regions of Ukraine.
This article highlights further research by the authors, begun in [48].
The article “The use of genetic algorithms for multicriteria optimization of the oil and gas
xx
Figure 7: Presentation of paper [42].
enterprises financial stability” [49] by Marta V. Shkvaryliuk, Liliana T. Horal, Inesa M. Khvostina,
Natalia I. Yashcheritsyna and Vira I. Shiyko (figure 9) considers the problem of optimizing the
financial condition of oil and gas companies. The offered methods of optimization of a financial
condition by scientists from different countries are investigated. It is determined that the
financial condition of the enterprise depends on the effectiveness of the risk management
system of enterprises. It is proved that the enterprises of the oil and gas complex need to
develop a system for risk management to ensure the appropriate financial condition. The
financial condition is estimated according to the system of certain financial indicators, the
integrated indicator of financial condition assessment is constructed using the method of
taxonomy. According to the results of the calculation of the integrated indicator, it is concluded
that this indicator does not have a stable trend. On the basis of the conducted researches it is
offered to carry out optimization of an integral indicator of a financial condition with use of
genetic algorithm in the Matlab environment. Based on the obtained results, recommendations
of the management of the researched enterprises on increase of management efficiency are
given.
This article highlights further research by the authors, begun in [50, 51, 52, 53, 54, 55].
The article “Fuzzy modelling of the country’s migration attractiveness” [56] by Hanna B.
Danylchuk, Liubov O. Kibalnyk (figure 10), Oksana A. Kovtun, Oleg I. Pursky and Zenon Sta-
xxi
Figure 8: Presentation of paper [47].
chowiak deals with the analysis the current state of migration in the context of globalization and
identifies the most important corridors for the labour movement. The main donor countries of
migrants are developing countries, with low socio-economic indicators, difficult environmental
conditions and high levels of poverty. According to forecasts, the most migratory flows will
take place in the countries of North America and in Europe, which is due to rising trends in
unemployment in the countries of the “third world” and the demand for cheap labour, changes
in the structure of the economies of developed countries, changes in labour market demand.
The main world regional corridors in 1990–2019 have been identified through statistical analysis.
And their growing and declining trends. The need to use economic and mathematical modelling
techniques to analyse and determine the migration attractiveness of recipient countries in an
uncertain environment has been substantiated. It has been shown that fuzzy logic tools are the
most effective in this case. Based on the results of the simulation using the Mamdani method,
the world’s attractiveness rating for migration is calculated, which with a “high” thermo leads
such countries as Italy, France, United Arab Emirates. The findings suggest that migrants are
attracted by countries with the lowest inflation rates, high and average GDP per capita and
average or low taxation levels.
This article highlights further research by the authors, begun in [58, 59, 60, 61, 62, 63, 64, 65,
66, 67, 68, 69].
In the article “Computational method determining integral risk indicators of regional socio-
economic development” [57], Oleg I. Pursky, Tetiana V. Dubovyk, Iryna O. Buchatska, Iryna
xxii
Figure 9: Presentation of paper [49].
Figure 10: Presentation of paper [56].
S. Lutsenko and Hanna B. Danylchuk (figure 11) present the computational method for risk
assessment of the socio-economic development of regions. An attempt has been made to develop
a method for the determination of integral risk indicators of socio-economic development based
on the joint use of the methods of factor analysis and expert evaluation. This approach has
xxiii
Figure 11: Hanna B. Danylchuk, Vita O. Los, Hanna Yu. Kucherova and Liubov O. Kibalnyk after
presentation of paper [57].
increased the reliability of the calculations and made it possible to analyze the influence of
socio-economic indicators on the risk level of socio-economic development. The integral risk
indicator shows the effect of the inconsistency in the level of factor provision on the socio-
economic development of the 𝑗-th region (district) in comparison with the general situation in
the country (regions). The closer the value of integral risk indicator is to 1, the higher the level
of risk in this region. Using Kyiv region districts as an example, the process of risk assessment
for regional socio-economic development has been considered. The results obtained in this
investigation demonstrate that the presented computational method solves the problem of
formalization of risk assessment for the socio-economic development of regions.
The article “Modelling the logistics system of an enterprise producing two type of goods”
[70] by Roman V. Ivanov (figure 12), Yuriy V. Sherstennikov, Vasyl M. Porokhnya and Tetyana
V. Grynko is devoted to solving the scientific problem of optimizing the retail trade in the
production and sale of two types of products, taking into account the change in potential
demand for products. The economic and mathematical model of the production activity of
the enterprise was developed taking into account logistics and market demand. The logistics
scheme takes into account all the main links of the logistics system, as well as the connections
between them. The considered scheme makes it possible to take into account the diversification
xxiv
Figure 12: Presentation of paper [70].
of products manufactured by the enterprise. The mathematical model is designed for discrete
time. A numerical optimization method has been developed for this mathematical model. The
optimal solutions for several cases are found and investigated. The dynamics of the main
characteristics of drugs was calculated for all considered cases. A comparative analysis of
economic efficiency for the studied cases has been performed. The economic efficiency of retail
network optimization is proved.
3. Conclusion and outlook
The vision of the M3E2 2021 is provides a premier interdisciplinary platform for researchers,
practitioners and educators to present and discuss the most recent innovations, trends, and
concerns as well as practical challenges encountered and solutions adopted in the fields of
emergent economy.
The conference has successfully performing forum to transferring and discussing research
result among the researcher, students, government, private sector or industries. Participants
and presenters from several countries such as Belarus, China, Czechia, Kazakhstan, Moldova,
Poland and Ukraine have attended the conference in-person and online to share their significant
xxv
Figure 13: Have a nice conference in Odessa, Ukraine!
contribution in research related to Monitoring, Modeling & Management of Emergent Economy.
We are thankful to all the authors who submitted papers and the delegates for their partici-
pation and their interest in M3E2 as a platform to share their ideas and innovation. Also, we
are also thankful to all the program committee members for providing continuous guidance
and efforts taken by peer reviewers contributed to improve the quality of papers provided
constructive critical comments, improvements and corrections to the authors are gratefully
appreciated for their contribution to the success of the conference. Moreover, we would like
to thank the developers and other professional staff of Not So Easy Science Education platform
(https://notso.easyscience.education), who made it possible for us to use the resources of this
excellent and comprehensive conference management system, from the call of papers and
inviting reviewers, to handling paper submissions, communicating with the authors etc.
We are looking forward to excellent presentations and fruitful discussions, which will broaden
our professional horizons. We hope all participants enjoy this conference and meet again in
more friendly, hilarious, and happiness of further M3E2 2022.
xxvi
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