Machine learning for prediction of emergent economy dynamics

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 introduction, conference review and some observations about the event and its future. 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, innovation 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 M3E2-MLPEED 2021: The 9th International Conference on Monitoring, Modeling & Management of Emergent Economy, 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); (A. V. Matviychuk); http://mpz.knu.edu.ua/pro-kafedru/vikladachi/224-andrii-striuk (A. M. Striuk) 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

Keywords

• economy

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CEUR Workshop Proceedings htp:/ceur-ws.org IS N1613-073

CEUR Workshop Proceedings (CEUR-WS.org)

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 production and business closure, enterprises, regions, national economies and transnational capital found themselves in a dificult situation. They experienced a decline in production and trade, bankruptcy, reduced profitability, slower growth etc. This is just a small list of the efects 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 enterprises 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 methodology of emergent economy.

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.

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 International 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, Batumi 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 working in the Finance and Banking at the Ivane Javakhishvili Tbilisi State University, since 2006 - Batumi Shota Rustaveli State University where he is currently Head department of Finance, Banking and Insurance. His research interests include Economics, Econometrics, Finance and Social Sciences (miscellaneous). 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 diferent prestigious internal collaborative research project with USA, Canada, Lithuania, Poland, Ukraine, Turkey and etc.

WWW: https://orcid.org/0000-0002-5834-1233 E-mail: [e-mail]

Prof. Dr. Vitalina Babenko is Professor (Full) of Interna

tional E-commerce and Hotel&Restaurant Business Department, V. N. Karazin Kharkiv National University (Ukraine), Dr. Sci. (habil.) in Economics, PhD in Technical Sciences.

Her sphere of scientific interests includes the management of innovation processes, economic-mathematical modelling, information systems and technologies. She has published 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 Journal of International Relations, Economics, Country Studies, Tourism; International Journal of Economics and Management Systems and member of editorial board of some scientific journals. She is the Member of Doctoral Academic Councils in Economics, Expert of the Ministry of Education 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: [e-mail]

Dr. Oleksandr Chernyak was the Professor, Head of

Economic Cybernetics Department, Taras Shevchenko National 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 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 markets. She has published a number of papers in international journals.

E-mail: [e-mail]

Dr. Irina Georgescu, Lecturer of Computational In

telligence, Department of Informatics and Economic Cybernetics, 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: [e-mail]

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, analysis 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 technical committees of international scientific-practical conference “Modern problems of modelling the socio-economic systems” (Ukraine, Slovenia, Poland, the USA, Bulgaria), “Innovation and information technology 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: [e-mail]

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 University, 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 Department of Automated Systems and Modeling in Economics. Directions of studies are related to decision-making, multidimensional modeling of socio-economic systems, comprehensive assessment of economic phenomena latent characteristics, financial security, sustainable development, information technologies in education. He has published a number of papers in domestic and international journals, monographs and volumes in book series. Since December 2020 he is Editor-in-Chief of Herald of Khmelnytskyi National University. Economic Sciences.

E-mail: [e-mail], [e-mail]

Dr. Serhii Hushko, State University of Economics and

Technology, Ukraine.

WWW: https://www.duet.edu.ua/en/persons/12 E-mail: [e-mail]

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 Problems 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 volumes in book series, is a member of editorial board of Herald of Khmelnytskyi National University. Economic Sciences.

E-mail: [e-mail], [e-mail]

Dr. Liubov Kibalnyk, Head and Professor of Depart

ment of Economics and Business Modelling, Cherkasy Bohdan 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 economic 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 processes 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: [e-mail]

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 Efects, 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 efects 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.

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 financial 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: [e-mail]

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 University, 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 Economics. Her research interests include modeling the country’s business climate, behavior of socio-economic agents, tax consciousness and information transparency.

WWW: https://scholar.google.ru/citations?user= FhBOVExn1foC

E-mail: [e-mail]

Dr. Serhii Lehenchuk, head of the department of man

agement information systems and accounting, Zhytomyr Polytechnic State University, Zhytomyr, Ukraine.

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: [e-mail]

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 mathematical 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 Cybernetics. Her research interests include economic and mathematical 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: [e-mail]

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 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 University 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 mathematical 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: [e-mail]

Dr. Inese Mavlutova, Professor (Full) at Department of

Economics and Finance, BA School of Business and Finance, Latvia.

E-mail: [e-mail]

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. Member 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: [e-mail], [e-mail]

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 Sciences in Physics and Mathematics degree (Dr. phil.) from 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 development, computer simulation and modeling of socioeconomic 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 Journal of Economic Theory and Application, reviewer of scientific 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: [e-mail]

Dr. Sultan Ramazanov, Kyiv National Economic Uni

versity named after Vadym Hetman, Ukraine.

Born 12/13/1949. Mathematician, cybernetic, environmental economist; design specialist and development of integrated management information systems complex ecological-economic objects with elements of artificial intelligence. Professor, Doctor of Engineering, Doctor of Economics Science, Honored Worker of Science and Technology of Ukraine. Honored Worker of Education of Ukraine.

Excellence in education of Ukraine. Professor of the Department ”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 International 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 at PUET (Poltava) and KNEU (Kyiv).

E-mail: [e-mail], [e-mail]

Dr. Serhiy Semerikov, Professor of Computer Science

and Educational technology, Kryvyi Rih State Pedagogical University, Ukraine.

Serhiy Semerikov is professor of Department of Computer Science and Applied Mathematics at Kryvyi Rih State Pedagogical University. He got both PhD and DSc in education (informatics) from the National Pedagogical Dragomanov 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: [e-mail]

Dr. Kateryna Shymanska, Head of the Department, De

partment of Digital Economy and International Economic Relations, Zhytomyr Polytechnic State University, Zhytomyr, 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 Doctor of Economic Sciences degree (Dr. habil.) from the Vasyl’ 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: [e-mail]

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 diferent nature.

Dr. Victoria Solovieva, Associate Professor, Head of

Department, State University of Economics and Technology, Ukraine.

She graduated from the Faculty of Physics and Mathematics 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: [e-mail]

Dr. Galyna Velykoivanenko, Head of the Economic

and Mathematical Modeling Department, Kyiv National Economic University named after Vadym Hetman, Ukraine.

E-mail: [e-mail]

Dr. Eugene Yakub, Professor of Economic Information

and Computer Technology, Department of Economic Cybernetics and Information Technology, Odessa National Economic University, Odessa, Ukraine.

Eugene Yakub, born in 1946, received a Candidate of Tech

nical Sciences degree (Dr.Phil.) from the Odessa Technological 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 Information 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: [e-mail]

Oleh Yatsiuk, Department of Economics and Manage

ment Theory, Ivano-Frankivsk National Technical University 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 enterprise, 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: [e-mail]

Dr. Nataliia Zachosova, Professor of Management and

Economic Security Department, Bohdan Khmelnytsky National University of Cherkasy, Cherkasy, Ukraine.

Nataliia Zachosova, born in 1986, received a Candidate of Economic Sciences degree (Dr. phil.) in 2011, and a Doctor of Economic Sciences degree (Dr. habil.) in 2017. In 2018 she received the Scholarship of the Cabinet of Ministers 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 ifnancial 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 Scientists. 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: [e-mail]

Dr. Pavel Zakharchenko, Professor of Economic Cyber

netics, Head of Department of Economic Cybernetics and Finances, Berdyansk State Pedagogical University, Berdyansk, Ukraine.

Pavel Zakharchenko, born in 1957, received a Candidate of Technical Sciences (Dr. phil.) from the Kharkov Institute of Radio Electronics, USSR, in 1982, and a Doctor of Economical Sciences degree (Dr. habil.) from the Kiev National 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: [e-mail]

2. Articles overview

The aim of the article “Innovative behavior of bitcoin market agents during COVID-19: recurrence 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, 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 ].

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 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 diferent 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 ].

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.

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 ].

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 diferent 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.

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 coeficients (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.

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 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, dificult 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 efective 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 socioeconomic development” [ 57 ], Oleg I. Pursky, Tetiana V. Dubovyk, Iryna O. Buchatska, Iryna

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 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 efect of the inconsistency in the level of factor provision on the socioeconomic development of the -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 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 eficiency for the studied cases has been performed. The economic eficiency 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 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 participation 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 eforts 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 staf 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. [62] H. Danylchuk, L. Kibalnyk, O. Kovtun, A. Kiv, O. Pursky, G. Berezhna, Modelling of cryptocurrency market using fractal and entropy analysis in COVID-19, CEUR Workshop Proceedings 2713 (2020) 352–371. [63] H. Danylchuk, O. Kovtun, L. Kibalnyk, O. Sysoiev, Monitoring and modelling of cryptocurrency trend resistance by recurrent and R/S-analysis, E3S Web of Conferences 166 (2020) 13030. doi:10.1051/e3sconf/202016613030. [64] O. Kovtun, A. Opalenko, O. Ivanylova, Assessment of the economy structural changes based on the consistency, CEUR Workshop Proceedings 2422 (2019) 27–37. [65] L. O. Kondratenko, H. T. Samoylenko, A. E. Kiv, A. V. Selivanova, O. I. Pursky, T. O.

Filimonova, I. O. Buchatska, Computer simulation of processes that influence adolescent learning motivation, CEUR Workshop Proceedings 2879 (2020) 495–506. [66] O. Pursky, A. Selivanova, T. Dubovyk, T. Herasymchuk, Software implementation of e-trade business process management information system, CEUR Workshop Proceedings 2546 (2019) 171–181. [67] O. Pursky, T. Dubovyk, I. Moroz, I. Buchatska, A. Savchuk, The price competition simulation at the blended trading market, CEUR Workshop Proceedings 2422 (2019) 15–26. [68] O. Pursky, T. Dubovyk, I. Gamova, I. Buchatska, Computation algorithm for integral indicator of socio-economic development, CEUR Workshop Proceedings 2393 (2019) 919–934. [69] O. I. Pursky, T. V. Dubovyk, V. O. Babenko, V. F. Gamaliy, R. A. Rasulov, R. P. Romanenko, Computational method for studying the thermal conductivity of molecular crystals in the course of condensed matter physics, Journal of Physics: Conference Series 1840 (2021) 012015. doi:10.1088/1742-6596/1840/1/012015. [70] R. V. Ivanov, Y. V. Sherstennikov, V. M. Porokhnya, T. V. Grynko, Modelling the logistics system of an enterprise producing two type of goods, CEUR Workshop Proceedings (2021).

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