The Future of Behavioral Economics: AI Tools in the Digital Space

The monograph was prepared based on the materials of the scientifi c project «Artificial Intelligence Tools in Managing the Behavior of Economic Agents in the Digital Space» according to the Grant of the National Academy of Sciences (NAS) of Ukraine to research
laboratories/groups of young scientists of NAS of Ukraine for conducting research in the priority directions of the development of science and technology in 2022—2023, as well as the planned research work of the Institute of Industrial Economics of NAS of Ukraine «Financial and economic stimulation of the development of smart industry».

The purpose of this research is to substantiate and develop conceptual provisions along with an array of economic and mathematical models, as well as re commendations for managing the economic agents’ behavior in the digital space using artifi cial intelligence tools. The main result is an array of economic and mathematical models and practical recommendations for increasing the opportunities and reducing the threats of using artifi cial intelligence tools, which form the scientifi c basis for managing the behavior of economic agents in the digital space. For government authorities and management, organizations and enterprises, as well as for researchers, teachers, postgraduate students, students, all those who are interested in the problems of behavioral and digital economics.

Abasov, M. F. (2021). Digitalism and the new economic agent. International Scientific Journal of Universities and Leadership, (12), 76—85. https://doi.org/10.31874/2520-6702-2021-12-2-76-87

Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The simple economics of artificial intelligence: Harvard Business Press.

Akerlof, G. A., & Kranton, R. E. (2000). Economics and Identity*. Quarterly Journal of Economics, 115(3), 715—753. https://doi.org/10.1162/003355300554881

Allais, M. (1953). Le comportement de l’homme rationnel devant le risque: Critique des postulats et axiomes de l’ecole americaine. Econometrica, 21(4), 503. https://doi.org/10.2307/1907921

Ariely, D. (2023). Misbelief: What Makes Rational People Believe Irrational Things. Heligo Books.

Arrow, K. J. (1973). Information and Economic Behavior. Defense Technical Information Center. https://doi.org/10.21236/ad0768446

Asimov, A. (1942). Runaround. Astounding Science Fiction, 29 (1), 94—103.

Atanasov, V. (2020). Digital Capitalism and Utopias of the Internet. AVANPOST-PRIM. https://commons.com.ua/file/uploads/digital_capitalism_sbornik.pdf

Bačík, R., Fedorko, R., Kakalejčík, L., & Pudło, P. (2015). The importance of Facebook Ads in terms of online promotion. Journal of applied economic sciences, 35, 677—683.

Bansal, M., Goyal, A., & Choudhary, A. (2022). A comparative analysis of K-Nearest Neighbour, Genetic, Support Vector Machine, Decision Tree, and Long Short Term Memory algorithms in machine learning. Decision Analytics Journal, 100071. https://doi.org/10.1016/j.dajour.2022.100071

Bean, R. (2018, February 5). How Big Data and AI are Driving Business Innovation in 2018. MIT Sloan Management Review. https://sloanreview.mit.edu/article/how-big-data-and-ai-are-driving-business-innovation-in-2018/

Becker, G. S. (1993). Nobel Lecture: The Economic Way of Looking at Behavior. Journal of Political Economy, 101(3), 385—409. https://doi.org/10.1086/261880

Belov, M. V., & Novikov, D. A. (2019). Network Active Systems: Models of Planning and Incentives. Automation and Remote Control, 80(12), 2229—2244. https://doi.org/10.1134/s0005117919120117

Berente, N., Gu, B., Recker, J., & Santhanam, R. (2021). Managing artificial intelligence. MIS Quarterly, 45, 1433—1450. https://doi.org/10.25300/MISQ/2021/16274

Bezghin, K., Ushkalyov, V., & Doronina, O. (2021). Reflective aspects of enterprise personnel development management. AD ALTA: Journal of Interdisc Iplinary Research, 11(2), 190—195.

Bezgin, K., Martiyanova, M., & Ushkalev, V. (2020). Peculiarities of innovation-oriented organisation: Behavioural paradigm. Entrepreneurship and Innovation, (11), 118—127.

Boddu, R.S.K., Santoki, A.A., Khurana, S., Koli, P.V., Rai, R., & Agrawal, A. (2022). An analysis to understand the role of machine learning, robotics and artificial intelligence in digital marketing. Materials Today: Proceedings, 56, 2288—2292.

Böhm-Bawerk, E. v., & Leonard, H. (1891). The Austrian Economists. The Annals of the American Academy of Political and Social Science, 1, 361–384. http://www.jstor.org/stable/1008674

Bortnikova, M., & Chirkova, Y. (2022). Artificial intelligence in management of foreign economic activity. Digital Economy and Economic Security, 2(02). https://doi.org/10.32782/dees.2-12

Bouakkaz, M., Ouinten, Y., Loudcher, S., & Strekalova, Y. (2017). Textual aggregation approaches in OLAP context: A survey. International Journal of Information Management, 37(6), 684—692. https://doi.org/10.1016/j.ijinfomgt.2017.06.005

Bowonder, B., & Miyake, T. (1992). Creating and sustaining competitiveness: Information management strategies of Nippon Steel Corporation. International Journal of Information Management, 12(1), 39—56. https://doi.org/10.1016/0268-4012(92)90051-q

Brock, J. K.-U., & von Wangenheim, F. (2019). Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California Management Review, 61(4), 110—134. https://doi.org/10.1177/1536504219865226

Bugera, O. (2021). Use of artificial intelligence for crime prevention. Scientific Notes of Vernadskyi National University. Series: legal sciences, 32 (71) N 6, 81—86. https://doi.org/10.32838/TNU-2707-0581/2021.6/13

Burk, D. L. (2020). Algorithmic legal metrics. Notre Dame L. Rev., 96, 1147—1204.

Buttenheim, A., Moffitt, R. & Beatty, A. (Eds). (2023). Behavioral Economics: Policy Impact and Future Directions. The National Academies Press. https://doi.org/10.17226/26874

Cabinet of Ministers of Ukraine. (2020). On approval of the concept of artificial intelligence development in Ukraine. https://zakon.rada.gov.ua/laws/show/1556-2020-р#Text

Cabinet of Ministers of Ukraine. (2021). On approval of the action plan for the implementation of the concept of Artificial Intelligence development in Ukraine for 2021—2024. https://zakon.rada.gov.ua/laws/show/438-2021-р#Text

Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics — Theory and Methods, 3(1), 1—27. https://doi.org/10.1080/036109 27408827101

Campbell, C., & Ying, Y. (2011). Learning with Kernels. In: Learning with support vector machines, 45—64. Springer International Publishing. https://doi.org/10.1007/978-3-031-01552-6_3

Campbell, M., Hoane, A.J., & Hsu, F.-h. (2002). Deep blue. Artificial Intelligence, 134(1—2), 57—83. https://doi.org/10.1016/s0004-3702(01)00129-1

Cappelli, P., Tambe, P., & Yakubovich, V. (2018). Artificial intelligence in human resources management: Challenges and a path forward. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3263878

Casarosa, F. (2022). Cybersecurity certification of Artificial Intelligence: a missed opportunity to coordinate between the Artificial Intelligence Act and the Cybersecurity Act. International Cybersecurity Law Review, 3, 115—130. https://doi.org/10.1365/s43439-021-00043-6

Chkhartishvili, A.G., Gubanov, D.A., & Novikov, D.A. (2018). Models of Influence in Social Networks. In: Social Networks: Models of Information Influence, Control and Confrontation, 1—40. Springer International Publishing. https://doi.org/10.1007/978-3-030-05429-8_1

Christie, Z.S.-L., & Hunter, E. (2021). NATO review — an artificial intelligence strategy for NATO. NATO Review. https://www.nato.int/docu/review/articles/2021/10/25/an-artificial-intelligence-strategy-for-nato/index.html

Clark, N., & Juma, C. (2013). Long-Run Economics: An Evolutionary Approach to Economic Growth. Bloomsbury Publishing Plc.

Commons, J. R. (1931). Institutional economics. The American economic review, 40—41(2), 648—657. https://doi.org/10.3917/cep.040.0287

Council of Europe. (2018, June 21). Digital tools, spaces and places. Coyote Magazine. https://pjp-eu.coe.int/en/web/coyote-magazine/digital-tools-spaces-and-places#portlet_56_INSTANCE_jyqrnvVWf1Aw

Cuomo, M. T., & Foroudi, P. (2023). Digital transformation. In: Digital Transformation and Corporate Branding, 1—6. Routledge. https://doi.org/10.4324/9781003263784-1

Dasiv, A., Madikh, A., Okhten, A., & Turlakova, S. (2019). Economic and mathematical models and information and communication technologies of smart industry development: Monograph. National Academy of Sciences of Ukraine, Institute of Industrial Economics. https://iie.org.ua/wp-content/uploads/2020/04/2019-smart-promyslovist_napriamy-stanovlennia-problemy-i-rishennia_compressed-1.pdf

Daugherty, P. R., & Wilson, H. J. (2018). Human + machine: Reimagining Work in the Age of AI. Harvard Business Press.

de Marcellis-Warin, N., Marty, F., Thelisson, E., & Warin, T. (2022). Artificial intelligence and consumer manipulations: From consumer’s counter algorithms to firm’s self-regulation tools. AI and Ethics. https://doi.org/10.1007/s43681-022-00149-5

Denzin, N. K., Franks, D. D., & McCarthy, E. D. (1991). The sociology of emotions: Original essays and research papers. Contemporary Sociology, 20(1), 133. https://doi.org/ 10.2307/2072144

Diachuk, O. A., & Furtat, Y. O. (2020). The problem of reliability with the participation of a human operator in the decision-making process for the management of energy facilities. Mathematical and Computer Modelling. Series: Technical Sciences, (21), 61—75. https://doi.org/10.32626/2308-5916.2020-21.61-75

Dictionary C. I. E. (1995). Cambridge international dictionary english (Cambridge low price editions). Cambridge University Press.

Dodonov, O., Koval, O., Senchenko, V., & Shpuryk, V. (2019). An automated scenario generation system for analytical activities. egistration, storage and processing of data, 1(21), 11—22. http://nbuv.gov.ua/UJRN/rzod_2019_21_1_4

Dragan, O., & Pylypenko, M. (2021). Development of talent management in the enterprise’s personnel management system. Economy and society, 33. https://doi.org/10.32782/ 2524-0072/2021-33-52

Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data — evolution, challenges and research agenda. International Journal of Information Management, 48, 63—71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021

Dyer-Witheford, N., Kjøsen, A. M., & Steinhoff, J. (2019). Inhuman Power: Artificial Intelligence and the Future of Capitalism. Pluto Press. https://doi.org/10.2307/j.ctvj4sxc6

Echeberria, A. L. (2022). The impact of AI on business, economics and innovation. In: Artificial intelligence for business, 67—96. Springer International Publishing. https://doi.org/10.1007/978-3-030-88241-9_3

Efe, A. (2023). An assessment on the problems and possible solutions of artificial intelligence tools and techniques on execution, monitoring and reporting of impact investments. Girişimcilik İnovasyon ve Pazarlama Araştırmaları Dergisi. https://doi.org/10.31006/ gipad.1263598

Ershadi, M. M., & Seifi, A. (2020). An efficient Bayesian network for differential diagnosis using experts’ knowledge. International Journal of Intelligent Computing and Cybernetics, 13(1), 103—126. https://doi.org/10.1108/ijicc-10-2019-0112

ESCWA (2023). Economic agents. https://www.unescwa.org/sd-glossary/economic- agents

European Commission. (2021). Proposal for a Regulation laying down harmonised rules on artificial intelligence. https://digital-strategy.ec.europa.eu/en/library/proposal-regulation- laying-down-harmonised-rules-artificial-intelligence

Fast, N. J., & Schroeder, J. (2020). Power and decision making: New directions for research in the age of artificial intelligence. Current Opinion in Psychology, 33, 172—176. https://doi.org/10.1016/j.copsyc.2019.07.039

Forbes. (2023). AI in Business. https://www.forbes.com/advisor/business/software/ai-in-business/

Ford, N. (1989). From information- to knowledge-management: The role of rule induction and neural net machine learning techniques in knowledge generation. Journal of Studies in International Education, 15(4-5), 299—304. https://doi.org/10.1177/102831538 901500412

Furashev, V. (2012). Cyberspace and information space, cybersecurity and information security: Essence, definition, differences. Information and Law, (2), 162—169.

Galbraith, J.K. (2007). The New Industrial State. Princeton University Press.

Garcia-dias, R., Vieira, S., Lopez Pinaya, W. H., & Mechelli, A. (2019). Clustering analysis. In Machine Learning: Methods and Applications to Brain Disorders, 227—247. Else­vier. https://doi.org/10.1016/B978-0-12-815739-8.00013-4

Gartner. (2017). Gartner top 10 strategic technology trends for 2018. https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technology-trends-for-2018

Gartner. (2022). SAP SuccessFactors HXM Suite Enterprise IT Software Reviews. https:// www.gartner.com/reviews/market/cloud-hcm-suites-for-1000-employees/vendor/sap/product/sap-successfactors-hxm-suite/reviews?marketSeoName=cloud-hcm-suites-for-1000-employees&vendorSeoName=sap&productSeoName=sap-successfactors-hxm-suite

Google Ads Help. (2010, July 10). Putting machine learning into the hands of every advertiser. https://support.google.com/google-ads/answer/9065075?hl=en

Gottwald, S. (2006). Universes of Fuzzy Sets and Axiomatizations of Fuzzy Set Theory. Part II: Category Theoretic Approaches. Studia Logica, 84(1), 23—50. https://doi.org/10.1007/s11225-006-9001-1

Government portal. (2024). State in a Smartphone: More than 20 million Ukrainians use Diia. https://www.kmu.gov.ua/en/news/derzhava-u-smartfoni-diieiu-korystuietsia-ponad- 20-milioniv-ukraintsiv

Grand View Research. (2021). Human Resource Management Market Size, Share & Trends Analysis By Component, By Software, By Service, By Deployment, By Enterprise Size, By End-use, By Region, And Segment Forecasts, 2024—2030. https://www.grandviewresearch.com/industry-analysis/human-resource-management-hrm-market

Grinchenko, B. (1925). Dictionary of the Ukrainian language.

Gubanov, D. A., Novikov, D. A., & Chkhartishvili, A. G. (2011). Informational influence and informational control models in social networks. Automation and Remote Control, 72(7), 1557—1567. https://doi.org/10.1134/s0005117911070216

Gummadi, R., & Chen, K. (2023, June 23). Preference learning with automated feedback for cache eviction. Ars Machine Intelligence. Google Research. https://blog.research.google/2023/06/preference-learning-with-automated.html

Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 4(61), 5—14.

Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks.

Hartigan, J. A., & Wong, M. A. (1979). Algorithm AS 136: A K-Means Clustering Algorithm. Applied Statistics, 28(1), 100. https://doi.org/10.2307/2346830

Hazen, D., Horrell, J., & Merrill-Oldham, J. (1998). Selecting research collections for digitization. Proceedings of the Council on Library and Information Resources. https://www.clir.org/pubs/reports/hazen/pub74/

Helsi.me. (2024). About HELSI. https://helsi.me/about

Hermann, E. (2022). Leveraging artificial intelligence in marketing for social good — An ethical perspective. Journal of Business Ethics, 179(1), 43—61.

Higgs, H., Smith, A., & Cannan, E. (1904). An inquiry into the nature and causes of the wealth of nations. The Economic Journal, 14(56), 599. https://doi.org/10.2307/2221259

Hilbert, M., & Lopez, P. (2011). The world’s technological capacity to store, communicate, and compute information. Science, 332(6025), 60—65. https://doi.org/10.1126/science.1200970

Hirschman, E. C., Kahneman, D., Slovic, P., & Tversky, A. (1983). Judgement under Uncertainty: Heuristics and Biases. Journal of Marketing Research, 20(2), 217. https://doi.org/10.2307/3151689

Hodgson, G. M. (2003). The hidden persuaders: institutions and individuals in economic theory. Cambridge Journal of Economics, 27(2), 159—175. https://doi.org/10.1093/cje/27.2.159

Hodgson, G. M. (2013). The evolution of morality and the end of economic man. Journal of Evolutionary Economics, 24(1), 83—106. https://doi.org/10.1007/s00191-013-0306-8

Hoffman, S. (2017). Managing the state: Social credit, surveillance and the ccp’s plan for china. China Brief, Volume 17 (Issue: 11). https://www.refworld.org/docid/59bb92874.htm

Holá, J., Moravcová, M., Čegan, L., & Hlaváčková, E. (2022). Competency Manager as a Very Useful Competency Management Tool. IDIMT-2022 Digitalization of Society, Business and Management in a Pandemic, 313—322.

Horwitz, S. (2003). The Austrian Marginalists: Menger, Böhm-Bawerk, and Wieser. In: A Companion to the History of Economic Thought, 262—277. Blackwell Publishing Ltd. https://doi.org/10.1002/9780470999059.ch17

Hristov, K. (2017). Artificial Intelligence and the Copyright Dilemma. IDEA: The IP Law Review, 3(57), 431—454.

HR You. (2020). Аrtificial intelligence for determining aptitude for professions, level of skills and aptitude for entrepreneurship «AI HR». https://interactive-resume.in.ua/

Huang, M.-H., Rust, R., & Maksimovic, V. (2019). The feeling economy: Managing in the next generation of artificial intelligence (AI). California Management Review, 61(4), 43—65. https://doi.org/10.1177/0008125619863436

Hunt, E., Minsky, M., & Papert, S. (1971). Perceptrons. The American Journal of Psychology, 84(3), 445. https://doi.org/10.2307/1420478

Hutson, M. (2018). How researchers are teaching AI to learn like a child. Science, (24). https://www.sciencemag.org/news/2018/05/how-researchers-are-teaching-ai-learn-child

Iemets, O., Chernenko, O., Chilikina, T., & Оlkhovska, O. (2021). Overview of the prob­lems of combinatory optimization of determination of profitability of agricultural production and methods of their solution. Mathematical and Computer Modelling. Series: Physical and Mathematical Sciences, (22), 63—74. https://doi.org/10.32626/2308-5878.2021-22.63-74

Institute of Educational Analytics. (2020). Automated educational management complex. https://e-journal.iea.gov.ua

Ivashchenko, А., Pavlikovsky, А., & Sivokha, І. (2018). The concept of defence planning based on capability development: Problems of implementation. Collection of Scientific Papers of the Centre for Military and Strategic Studies Named After Ivan Chernyakhovsky, (1—59), 53—58. https://doi.org/10.33099/2304-2745/2017-1-59/53-58

Jain, A., & Sharma, A. (2020). Membership function formulation methods for fuzzy logic systems: A comprehensive review. Journal of Critical Reviews, 7(19), 8717—8733.

Jamieson, M. K., Govaart, G. H., & Pownall, M. (2023). Reflexivity in quantitative research: A rationale and beginner’s guide. Social and Personality Psychology Compass, 17(4), e12735. https://doi.org/10.1111/spc3.12735

Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577—586. https://doi.org/10.1016/j.bushor.2018.03.007

Kabachenko, D. (2017). Management decision-making under conditions of uncertainty and and risk. Economic Bulletin of the National Mining University, 2(58), 107—115.

Kahneman, D. (2003). Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review, 93(5), 1449—1475. https://doi.org/10.1257/00028280 3322655392

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263. https://doi.org/10.2307/1914185

Kao, J.-H., Chan, T.-C., Lai, F., Lin, B.-C., Sun, W.-Z., & Chang, K.-W. et al. (2017). Spatial analysis and data mining techniques for identifying risk factors of Out-of-Hospital Cardiac Arrest. International Journal of Information Management, 37(1), 1528—1538. https://doi.org/10.1016/j.ijinfomgt.2016.04.008

Kaparulina, I. (2013). The essence and criteria for identifying an economic object. Problems of Economics, (3), 247—253. http://nbuv.gov.ua/UJRN/Pekon_2013_3_35

Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15—25. https://doi.org/10.1016/j.bushor.2018.08.004

Karmaza, O., & Kusherets, D. (2023). Artificial intelligence in the civil process: Prospects for use. Ukrainian Journal of Civil Engineering and Architecture, 3(15). https://doi.org/10.30525/978-9934-26-033-9-14

Kaski, S. (2011). Self-Organizing Maps. In: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning, 886—888.

Khrupovych, S. Ye., & Borysova, T. M. (2021). Using artificial intelligence in marketing analysis of unstructured data. Marketing and digital technology, 5(1), 17—26 [in Ukrainian].

Khrupovych, S. Ye., Okrepkyi, R. B., & Dudar, V. T. (2022). Using artificial intelligence to model the consumer portrait in digital marketing. Galician Economic Herald, 74(1), 163—170. [in Ukrainian].

Kirsch, G. (1997). Neue Politische Ökonomie. Werner, Ddf.

Kjosen, A. M., Dyer-Witheford, N., & Steinhoff, J. (2019). Inhuman power: Artificial intelligence and the future of capitalism. Pluto Press. https://doi.org/10.2307/j.ctvj4sxc6

Kleiner, G., Rybachuk, M., & Ushakov, D. (2023). Behavioral Model of Interaction Between Economic Agents and the Institutional Environment. In: Communications in Compu­ter and Information Science, 48—62. Springer Nature Switzerland. https://doi.org/10.1007/ 978-3-031-33728-4_4

Kofman, A. (1982). Introduction into the Theory of Fuzzy Sets. Radio and connection, 432.

Kohonen, T. (2001). Self-Organizing Maps. Springer—Verlag.

Kohonen, T. (2008). Data management by self-organizing maps. In: J.M. Zurada, G.G. Yen, & J. Wang (Eds.).

Kohonen, T. (2013). Essentials of the self-organizing map. Neural Networks, 37, 52—65. https://doi.org/10.1016/j.neunet.2012.09.018

Kondratieff, N. D. (1925). The Static and the Dynamic View of Economics. The Quarterly Journal of Economics, 39(4), 575. https://doi.org/10.2307/1883266

Kopalle, P.K., Gangwar, M., Kaplan, A., Ramachandran, D., Reinartz, W., & Rind­fleisch, A. (2022). Examining artificial intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. International Journal of Research in Marketing, 39(2), 522—540.

Korepanov, V.O., Chkhartishvili, A.G., & Shumov, V.V. (2022). Game-theoretic and reflexive combat models. Computer Research and Modeling, 14(1), 179—203. https://doi.org/10.20537/2076-7633-2022-14-1-179-203

Korsunova, K.Y. (2022). The impact of artificial intelligence on international digital marketing. Bulletin of the Volodymyr Dahl East Ukrainian National University, 4 (274), 25—30. [in Ukrainian].

Kotler, P. (Ed.). (2009). Marketing management. Prentice Hall Financial Times.

Kriegel, U. (2014). Sources of Intentionality. Oxford University Press, Incorporated.

Kushlyk-Divulska, O., & Kushlyk, B. (2014). Fundamentals of decision-making theory. NTUU «KPI».

Lefebvre, V. (2001). Algebra of conscience. Springer Science & Business Media.

Lefebvre, V. (2015). Conflicting Structures. Leaf & Oaks Publishers.

Li, D. (2023). AI-Threatened Jobs Are Mostly Held by Women, Study Shows. Bloom­berg. https://www.bloomberg.com/news/articles/2023-05-26/ai-threatened-jobs-are-mostly-held-by-women-study-shows

Li, H. (2019). Special section introduction: Artificial intelligence and advertising. Journal of Advertising, 48(4), 333—337. https://doi.org/10.1080/00913367.2019.1654947

Lighthill, J. (1973). Artificial intelligence: A general survey. Artificial Intelligence: A Paper Symposium. UK: Science Research Council, 34.

Lohvinenko, B. (2022a). Building the relationship of economic agents in the digital space at the Enterprise. In: Proceedings of the ХХX international scientific and practical conference, 11—15. https://isg-konf.com/wp-content/uploads/2022/08/The-newest-problems-of-science-and-ways-to-solve-them.pdf

Lohvinenko, B. (2022b). Managing the behavior of economic agents at enterprises with artificial intelligence tools. Economy of Industry, 4(100), 78—92. https://doi.org/10. 15407/econindustry2022.04.078

Lohvinenko, B. (2022c). The genesis of the concept of artificial intelligence in the context of management behaviour of economic agents. In: Multidisciplinary academic notes. Theory, methodology and practice, 233—235. https://isg-konf.com/wp-content/uploads/ 2022/05/Multidisciplinary-academic-notes.-Theory-methodology-and-practice.pdf

Lohvinenko, B. (2023). The impact of artificial intelligence tools in the management of human resource behavior on the results of decision-making by economic agents in the digital space. In: The EU Cohesion policy and healthy national development: Management and promotion in Ukraine, 617—624. Ed. by N. Letunovska, L. Saher, A. Rosokhata. Szczecin, Poland: Centre of Sociological Research.

Maedche, A., Legner, C., Benlian, A., Berger, B., Gimpel, H., & Hess, T. et al. (2019). AI-Based digital assistants. Business & Information Systems Engineering, 61(4), 535—544. https://doi.org/10.1007/s12599-019-00600-8

Management, I. R. (2017). Artificial intelligence: Concepts, methodologies, tools, and applications. IGI Global.

Markoff, J. (1992). Technology; A celebration of isaac asimov. NY: New York Times, 3, 8. https://www.nytimes.com/1992/04/12/business/technology-a-celebration-of-isaac-asimov.html

Mashliy, G., Mosiy, O., & Pelcher, M. (2018). Research on the management aspects of artificial intelligence. Galician Economic Herald of Ternopil National Technical University, 2(57), 80—89.

Matviychuk, А. (2011). Artificial intelligence in economics: Neural networks, fuzzy logic. KNEU.

Matviychuk, A., Dyuryadin, V., & Egorova, T. (2010). Intellectual modelling technologies in the information and analytical system of the state tax service. Alerta.

McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1955). A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence. http://jmc.stanford.edu/articles/dartmouth/dartmouth.pdf

McClelland, D. (2001). Chapter 27: Where Do We Stand on Assessing Competencies? Counterpoints, 166 (Competence in the learning society), 479—489. https://www.jstor.org/stable/42977810

McIntyre, R., & Smith, D. (1989). Theory of intentionality. Center for Advanced Research in Phenomenology.

McKinsey & Company. (2023). The state of AI in 2023: Generative AI’s breakout year. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai-in-2023-generative-ais-breakout-year#research.

Meta. (2020, June 11). Good Questions, Real Answers: How Does Facebook Use Ma­chi­ne Learning to Deliver Ads? https://www.facebook.com/business/news/good-questions-real-answers-how-does-facebook-use-machine-learning-to-deliver-ads

Metcalf, L., Askay, D. A., & Rosenberg, L. B. (2019). Keeping humans in the loop: Pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61(4), 84—109. https://doi.org/10.1177/0008125619862256

Meza, J., Terán, L., & Tomalá, M. (2019). A fuzzy-based discounts recommender system for public tax payment. In: Applying fuzzy logic for the digital economy and society, 47—72. Springer International Publishing. https://doi.org/10.1007/978-3-030-03368-2_3

Miller, S. (2018). AI: Augmentation, more so than automation. Asian Management Insights, 5(1), 1—20.

Ministry of Digital Transformation of Ukraine. (2023). Regulation of artificial intelligence in Ukraine: presenting a roadmap. https://thedigital.gov.ua/news/regulyuvannya-shtuchnogo-intelektu-v-ukraini-prezentuemo-dorozhnyu-kartu

Ministry of Education and Science of Ukraine. (2021). Education Management Information System. https://mon.gov.ua/osvita-2/tsifrova-transformatsiya-osviti-i-nauki/avtomatizovaniy-informatsiyniy-kompleks-osvitnogo-menedzhmentu

Minsky, M., & Papert, S. (1988). Perceptrons: An introduction to computational geometry. Cambridge. MA: MIT Press.

Mints, A., & Kamyshnykova, E. (2021). Fuzzy methods of stakeholder prioritisation in the context of stakeholder management. International Journal of Learning and Change, 13(4/5), 372. https://doi.org/10.1504/ijlc.2021.116673

Mints, A., Schumann, A., & Kamyshnykova, E. (2020). Stakeholders’ rank of reflexion diagnostics in a corporate social responsibility system. Economic Annals-Xxi, (1-2)(181), 92—104.

Misra, J., & Saha, I. (2010). Artificial neural networks in hardware: A survey of two decades of progress. Neurocomputing, 74(1-3), 239—255. https://doi.org/10.1016/j.neucom.2010.03.021

Morgenstern, O. (1976). The collaboration between Oskar Morgenstern and John von Neumann on the theory of games. Journal of Economic Literature, 3(14), 805—816.

Morris, R.G. M. (1999). D.O. Hebb: The organization of behavior. Wiley: New York, 1949. Brain Research Bulletin, 50(5—6), 437. https://doi.org/10.1016/s0361-9230(99) 00182-3

Mueller, B. (2021). The Artificial Intelligence Act: A Quick Explainer. Data Innovation. https://datainnovation.org/2021/05/the-artificial-intelligence-act-a-quick-explainer/

NATO. (2023). Summary of NATO’s Quantum Technologies Strategy. https://www.nato. int/cps/en/natohq/official_texts_221777.htm

Neisser, U., Boodoo, G., Bouchard, T.J., Boykin, A.W., Brody, N., Ceci, S.J., Hal­pern, D.F., Loehlin, J.C., Perloff, R., Sternberg, R.J., & Urbina, S. (1996). Intelligence: Knowns and unknowns. American Psychologist, 51(2), 77—101. https://doi.org/10.1037/0003-06 6x.51.2.77

Newell, A., Shaw, J., & Simon, H. (1958). Report on a general problem solving program. In IFIP Congress.

North, D. (2003). The Role of Institutions in Economic Development. UNECE, ECE Discussion Papers Series.

North, D. C. (1990). Institutions, Institutional Change and Economic Performance. Cambridge University Press.

North, O. (1990). Institutions, economic theory, and economic performance. In: Institutions, Institutional Change and Economic Performance, 107—117. Cambridge University Press. https://doi.org/10.1017/cbo9780511808678.014

Novikov, D. (2001). Management of Active Systems: Stability or Efficiency. Systems Science, 2(26), 85—93.

Novikov, D.A. (2014). Reflexion and Control: Mathematical Models. Taylor & Francis Group.

OECD. (2019). Recommendation of the Council on Artificial Intelligence, OECD/LEGAL/ 0449. https://oecd.ai/en/assets/files/OECD-LEGAL-0449-en.pdf

Ogiela, L., & Ogiela, M.R. (2014). Cognitive systems for intelligent business information management in cognitive economy. International Journal of Information Management, 34(6), 751—760. https://doi.org/10.1016/j.ijinfomgt.2014.08.001

Onowu, N. (2023). The rise of AI and Its implications for gender dynamics: Revelio Labs’ 2023 Workforce Study — ToTalent. ToTalent. https://totalent.eu/ai-and-gender-revelio-labs-2023-study/

Oplachko, I., Malchyk, M., & Popko, O. (2019). Organizational support of the crisis management mechanism of the industrial enterprises activity on the basis of reflexive approach. Annales Universitatis Mariae Curie-Skłodowska, sectio H — Oeconomia, 53(1), 49. https://doi.org/10.17951/h.2019.53.1.49-58

Osvita.ua. (2024). Online — external assessment tests. https://zno.osvita.ua

Oxford Insights. (2022). Government AI readiness index 2022. https://static1.square space.com/static/58b2e92c1e5b6c828058484e/t/639b495cc6b59c620c3ecde5/16711212 99433/Government_AI_Readiness_2022_FV.pdf

Panetta, K. (2018). Gartner Top 10 Strategic Technology Trends for 2018. Retrieved from https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technologytrends-for-2018/

Pchelyansky, D., & Voinova, S. (2019). Artificial intelligence: Prospects and trends of development. Automation of Technological and Business Processes, 11(3), 59—64. https://doi.org/10.15673/atbp.v11i3.1500

Petrushyna, T. (2009). Economic behaviour. Encyclopaedia of modern Ukraine. Institute of Encyclopaedic Studies of the National Academy of Sciences of Ukraine. https://esu.com.ua/article-18782.

Phillips-Wren, G., & Lakhmi, J. (2006). Artificial intelligence for decision making. Knowledge-Based Intelligent Information and Engineering Systems, Vol. 4252.

Piegat, A. (2001). Fuzzy Modeling and Control (Studies in Fuzziness and Soft Computing). Physica-Verlag Heidelberg.

Pivnyak, B., Busygin, B., Divizinyuk, M., Azaenko, O., Korotenko, H., & Korotenko, L. (2010). Explanatory dictionary of computer science. Department of Computer Systems Software. http://ir.nmu.org.ua/handle/123456789/1957

Proskurnina, N. V., & Dobroskok, Y. B. (2019). Artificial intelligence in the marketing activities of trade enterprises. Economic development and the legacy of Semen Kuznets: materials of the International scientific and practical conference, (30—31 May 2019, Kharkiv: KhNUE named after Semen Kuznets), 254—255. [in Ukrainian].

Proskurnina, N. (2020). Artificial intelligence in marketing activities. Foreign Trade: Economics, Finance, Law, (4), 129—140. http://irbis-nbuv.gov.ua/cgi-bin/irbis_nbuv/cgiirbis_64.exe?C21COM=2&I21DBN=UJRN&P21DBN=UJRN&IMAGE_FILE_DOWNLOAD=1&Image_file_name=PDF/uazt_2020_4_11.pdf

Puntoni, S., Reczek, R.W., Giesler, M., & Botti, S. (2020). Consumers and artificial intelligence: An experiential perspective. Journal of Marketing, 85(1), 131—151. https://doi.org/10.1177/0022242920953847

Raevneva, O. (2006). Management of enterprise development: methodology, mechanisms, models. INZHEK Publishing House.

Ragini, J.R., Anand, P.M.R., & Bhaskar, V. (2018). Big data analytics for disaster response and recovery through sentiment analysis. International Journal of Information Management, 42, 13—24. https://doi.org/10.1016/j.ijinfomgt.2018.05.004

Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation-augmentation paradox. Academy of Management Review, 46(1), 192—210. https://doi.org/10.5465/amr.2018.0072

Ramírez-Noriega, A., Juárez-Ramírez, R., & Martínez-Ramírez, Y. (2017). Evaluation mo­du­le based on bayesian networks to intelligent tutoring systems. Internatio­nal Journal of In­formation Management, 37(1), 1488—1498. https://doi.org/10.1016/j.ijinfomgt.2016.05.007

Rathore, B. (2023). Digital Transformation 4.0: Integration of Artificial Intelligence & Metaverse in Marketing. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 12(1), 42—48.

Raven, J. (1977). Education, values and society: The objectives of education and the nature and development of competence. Lewis.

Raven, J., & Stephenson, J. (2001). Competence in the Learning Society. Peter Lang Publishing.

Rekik, R., Kallel, I., Casillas, J., & Alimi, A. M. (2018). Assessing web sites quality: A systematic literature review by text and association rules mining. International Journal of Information Management, 38(1), 201—216. https://doi.org/10.1016/j.ijinfomgt.2017.06.007

Reznikov, R. (2024). Practical recommendation of using generative ai in business. Herald of Khmelnytskyi National University. Economic sciences, 328(2), 378—384.

Reznikov R., & Turlakova S. (2024а). Data science methods and models in modern economy. Economic Scope, 191, 104—113. https://doi.org/10.32782/2224-6282/191-19

Reznikov R., & Turlakova S. (2024b). Importance of Machine Learning and Data Science in Modern Business. Efficient economy, 5. http://doi.org/10.32702/2307-2105.2024.5.13

Reznikov R., & Turlakova S. (2024с). The crucial role of ІТ service companies in driving the modern economy. Collection of Scientific Papers «Scientific Notes», 35 (2), 251—269. https://doi.org/10.33111/vz_kneu.35.24.02.18.124.130

Reznikov, R., & Turlakova, S. (2024d). The driver of industry 4.0 development: the key role of IT-service companies. Herald of Khmelnytskyi National University. Economic sciences, 330(3), 26—35.

Robert, K., & Ola, L. (2021). Reflexive sensegiving: An open-ended process of influencing the sensemaking of others during organizational change. European Management Journal, 39(4), 476—486. https://doi.org/10.1016/j.emj.2020.10.007

Sancho-Royo, A., & Verdegay, J. L. (1999). Methods for the Construction of Membership Functions. International Journal of Intelligent Systems, 14(12), 1213—1230. https://doi.org/10.1002/(sici)1098-111x(199912)14:12%3C1213::aid-int3%3E3.0.co;2-5

Searle, J.R. (1983). Intentionality, an essay in the philosophy of mind. Cambridge University Press.

Searle, J.R. (2001). Rationality in action. MIT Press.

Sharavara, O. (2017). Klaus schwab’s «fourth industrial revolution»: Worldview gui­de­lines. Actual Problems of Philosophy and Sociology: Scientific and Practical Journal. Na­tional University «Odesa Law Academy, (15), 156—158.

Shevchenko, A., Bilokobylskyi, О., & Vakulenko, M. (2022). On the draft strategy for the development of artificial intelligence in ukraine for 2022—2030. Artificial Intelligence, 1. https://www.slyusar.kiev.ua/AI_2022-1-1_ua.pdf

Shevchenko., A. (Eds). (2023). Strategy for Artificial Intelligence Development in Uk­rai­ne. IAIP.

Shrestha, Y.R., Ben-Menahem, S.M., & von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66—83. https://doi.org/10.1177/0008125619862257

Shumanov, M., Cooper, H., & Ewing, M. (2021). Using AI predicted personality to enhance advertising effectiveness. European Journal of Marketing.

Shumilo, Y. (2022a). Opportunities and advantages of using artifi cial intelligence tools in digital marketing activities. Commercialization of innovations: protection of intellectual capital, marketing and innovations. Edited by Candidate of Economic Sciences, Associate Professor L. Sager, Candidate of Economic Sciences, Associate Professor L. Sigida. Sumy: Sumy State University.

Shumilo, Y.M. (2022b). Possibilities and advantages of using artificial intelligence tools in digital marketing activities. In: Commercialization of Innovations: Protection of Intellectual Capital, Marketing, and Innovations. Ed. Saher, L.Yu., Syhyda, L.O., 141—150. Sumy: Sumy State University. [in Ukrainian].

Shumilo, Y.M. (2022с). Artificial intelligence tools for managing the behavior of economic agents in marketing activities. Bulletin of V.N. Karazin Kharkiv National University. Series: International Relations. Economics. Country Studies. Tourism, 15, 60—68. https://doi.org/10.15407/scin13.05.019

Shumilo, Y.M. (2022d). Conceptual provisions of the mechanism of reflexive management of consumer behaviour in the marketing activities of enterprises. Economics of Industry, 1 (97), 103—117. [in Ukrainian].

Shumilo, Y.M. (2023). Reflective management of the behaviour of marketing spe­cia­lists using artificial intelligence tools. In book: Actual problems of system analysis and modelling of management processes. Ed. V. Ponomarenko, L. Guryanova, J. Peliova, E. Nizhynsky. Bratislava-Kharkiv, HSE — HNUE named after S. Kuznets, 307—320. [in Ukrainian].

Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., & van den Driessche, G. et al. (2016). Mastering the game of Go with deep neural networks and tree search. Nature, 529(7587), 484—489. https://doi.org/10.1038/nature16961

Simon, H. (1993). Altruism and economics. American Economic Review, 83(2), 156—161. https://EconPapers.repec.org/RePEc:aea:aecrev:v:83:y:1993:i:2:p:156-61

Simon, H.A. (1955). A Behavioral Model of Rational Choice. The Quarterly Journal of Economics, 69(1), 99. https://doi.org/10.2307/1884852

Simon, H.A. (1966). Theories of decision-making in economics and behavioural scien­ce. In: Surveys of economic theory, 1—28. Palgrave Macmillan UK. https://doi.org/10.1007/978-1-349-00210-8_1

Simon, H.A. (1978). Rational decision making in business organizations. The American Economic Review, 69, 493—513. https://api.semanticscholar.org/CorpusID:652610

Simon, H.A. (1993). Homo rationalis. Die Vernunft im menschlichen Leben. Campus- Verlag.

Smith, V.L., & Wilson, B.J. (2019). Humanomics: Moral Sentiments and the Wealth of Nations for the Twenty-First Century. Cambridge University Press.

Spencer, L.M., Spencer, S.M., & Jr, S.L.M. (2008). Competence at Work: Models for Superior Performance. Wiley & Sons, Incorporated, John.

Srinivasan, D. (2020). Why Google dominates advertising markets. Stanford Technology Law Review, 24, 55.

Standage, T. (2023, November 6). Tom Standage’s ten trends to watch in 2024. The Economist. https://www.economist.com/the-world-ahead/2023/11/06/tom-standages-ten- trends-to-watch-in-2024

Stanley-Lockman, Z., & Christie, А.H. (2021). NATO’s Artificial Intelligence Strategy. NATO Review. https://www.nato.int/docu/review/uk/articles/2021/10/25/strategya-shchodo-shtuchnogo-rozumu-dlya-nato/index.html

Stasiuk, O., Baranov, V., Baranov, G., & Frolova, O. (2005). Differential transforms for computer modelling of control system. a textbook for students of higher educational institutions. KUETTE.

Steinhoff J. (2021). Automation and Autonomy. Labour, Capital and Machines in the Artificial Intelligence Industry. Palgrave Macmillan Cham. https://doi.org/10.1007/978-3-030-71689-9

Stempel, J., Bartz, D., & Raymond, N. (2024). Meta’s Instagram linked to depression, anxiety, insomnia in kids  — US states’ lawsuit. Reuters. https://www.reuters.com/legal/dozens-us-states-sue-meta-platforms-harming-mental-health-young-people-2023-10-24/

Subbotin, S., Oliynyk, A., & Oliynyk, O. (2009). On-iterative, evolutionary and multi-agent methods for synthesis of fuzzy and neural network models. ZNTU.

Suchetha, M., Madhumitha, R., Sorna Meena, M. & Sruthi, R. (2021). Sequential Convolutional Neural Networks for classification of cognitive tasks from EEG signals. Applied Soft Computing, 111, 107664. https://doi.org/10.1016/j.asoc.2021.107664

Sunstein, C. R., & Thaler, R. H. (2008). Nudge: Improving decisions about health, wealth, and happiness. Yale University Press.

Sunstein, C. R., & Thaler, R. H. (2009). Nudge: Improving decisions about health, wealth and happiness. Penguin Books, Limited.

Suthaharan, S. (2016). Science of information. In: Machine learning models and algorithms for big data classification, 1—13. Springer US. https://doi.org/10.1007/978-1-4899-7641-3_1

Tadeusiewicz, R., Ogiela, L., & Ogiela, M. R. (2008). The automatic understanding approach to systems analysis and design. International Journal of Information Management, 28(1), 38—48. https://doi.org/10.1016/j.ijinfomgt.2007.03.005

Tarasov, A., & Turlakova, S. (2018). Mathematical modelling of advanced mechanical engineering technologies for smart enterprises: Overview of approaches and implementation paths. Industrial Economics, 3(83), 57—75.

Tchaikovska, V., & Guba, R. (2022). European Parliament approves plan to regulate artificial intelligence. DW. https://www.dw.com/uk/evroparlament-shvaliv-plan-reguluvanna-stucnogo-intelektu/a-65912171

Terna, P. (1992). Artificial economic agents. In: S. K. Rogers (Eds.). Aerospace sensing. SPIE. https://doi.org/10.1117/12.139977

Tkachenko, T. (2023). Dopamine: the hormone of happiness, where it is found. Pharmacist Practitioner. https://fp.com.ua/foto/dolomin-molecula [in Ukrainian].

Thaler, R. H. (2015). Misbehaving: The story of behavioral economics. Norton & Company, Incorporated, W. W.

Thaler, R. H. (2018). Nudge, not sludge. Science, 361(6401), 431. https://doi.org/10.1126/ science.aau9241

Thaler, R. H., & Ganser, L. J. (2015). Misbehaving: The Making of Behavioral Economics. Audible Studios on Brilliance Audio.

The Economist. (2023, November 13). The Word Ahead 2024. Future-gazing analysis, predictions and speculation. https://www.economist.com/topics/the-world-ahead-2024

Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, 49, 433—460.

Turlakova, S. (2011). The role of awareness of decision-making subjects in the process of manifestation of herd behavior in economic systems. Culture of the peoples of the Black Sea region, 205, 222—224.

Turlakova, S. (2019). Information and communication technologies for the development of smart production: Scientific and analytical report. Economy of Industry, 1(85), 101—122. https://doi.org/10.15407/economindustry2019.01.101

Turlakova, S. (2020a). Reflexive management of herd behavior at enterprises: concept, models and methods. National Academy of Sciences of Ukraine, Institute of Industrial Economics. https://iie.org.ua/wp-content/uploads/2020/04/mono_turlakova_2020_compressed.pdf

Turlakova, S. (2020b). Influence of agents’ competence on reflexive processes of herd behavior manifestation at enterprises. Investitsii: praktika ta dosvid, 5(6), 38—46.

Turlakova, S.S. (2022a). Conceptual provisions for managing the behaviour of economic agents in the digital space using artificial intelligence tools. Economics and entrepreneurship, 49, 40—54. 10.33111/EE.2022.49

Turlakova, S.S. (2022b). Modeling the values of reflexive characteristics of agents within the management of herd behavior at the enterprises. Neuro-Fuzzy Modeling Techniques in Economics, 11, 48—71. http://doi.org/10.33111/nfmte.2022.048

Turlakova, S. (2023a). Reflexive management of the behavior of economic agents in the digital space using artificial intelligence tools. In: Actual problems of system analysis and modelling of management processes, 268—283.

Turlakova S.S. (2023b). Modeling the behavior of economic agents in the digital space. Modeling and forecasting of economic processes: Coll. of proceedings of the XVIІ Internat. scient.-pract. conf., Kyiv, Decem. 7, 2023. Kyiv: Igor Sikorsky Kyiv Polytechnic Institute, PH «Politekhnika».

Turlakova, S., & Lohvinenko, B. (2023). Artificial intelligence tools for managing the behavior economic agents at micro level. Neuro-Fuzzy Modeling Techniques in Economics, 12, 3—30. https://doi.org/10.33111/nfmte.2023.003

Turlakova, S., Shumilo, Y., & Lohvinenko, B. (2021). Systems analysis models in the economic processes management. М. Ponomarenko, T. Klebanova & L. Guryanova, Eds. HSE — KhNUE named after S. Kuznets. https://mpsesm.org/downloads/mono/mono-2021.pdf

Tversky, A., & Kahneman, D. (1982). Judgment under uncertainty: Heuristics and biases. In: Judgment under Uncertainty, 3—20. Cambridge University Press. https://doi.org/10.1017/cbo9780511809477.002

Tzung-Pei, H., & Jyh-Bin, Ch. (1999). Finding relevant attributes and membership fun­ctions. Fuzzy Sets and Systems, 103(3), 389—404. https://doi.org/10.1016/s0165-0114(97)00187-5

Unated Nations. (2023). Final Report — Governing AI for Humanity. https://www.un. org/ai-advisory-body

Vapnik, V. N., & Chervonenkis, A. Y. (1971). On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability & Its Applications, 16(2), 264—280. https://doi.org/10.1137/1116025

Vartanova, O., & Rovnyagin, O. (2022). Revitalisation of the concept of economic behaviour and irrationality of its subjects in decision-making. Tavrian Scientific Bulletin. Series: Economics, (13), 9—15. https://doi.org/10.32782/2708-0366/2022.13.1

Veale, M., & Zuiderveen Borgesius, F. (2021). Demystifying the Draft EU Artificial Intelligence Act — Analysing the good, the bad, and the unclear elements of the proposed approach. Computer Law Review International, 22(4), 97—112. https://doi.org/10.9785/cri-2021-220402

Verkhovin, V. (1994). Economic behavior as a subject of sociological analysis. Sociological studies, 10, 120—125.

Virendra, S. (1991). Education, concept and management. Sar Publishers.

Vishnevsky, V., Viyetska, O., Viyetskyi, O., Vorgach, O., Harkushenko, O., & Dasiv, A. et al. (2019). Smart industry: Directions of development, problems and solutions. National Academy of Sciences of Ukraine, Institute of Industrial Economics. https://iie.org.ua/wp-content/uploads/2020/04/2019-smart-promyslovist_napriamy-stanovlennia-problemy-i-rishennia_compressed-1.pdf

Volchik, V., & Zotova, T. (2010). Economic behavior in the context of the evolution of institutions. TeRRa economicus, 8(4), 62—67.

von Neumann, J., & Morgenstern, O. (1945). Theory of Games and Economic Beha­vior. The Journal of Philosophy, 42(20), 550. https://doi.org/10.2307/2019327

Wang, Y., Jin, W., & Derr, T. (2022). Graph neural networks: Self-supervised learning. In: Graph neural networks: Foundations, frontiers, and applications, 391—420. Springer Singapore. https://doi.org/10.1007/978-981-16-6054-2_18

Watanabe, S., Amano, S., Takarabe, T., Nakamori, T., Oda, H., & Taira, M. et al. (1989). Application of expert system to blast furnace operation. IFAC Proceedings Volumes, 22(11), 255—260. https://doi.org/10.1016/s1474-6670(17)53118-3

Watson, R. (2022). The virtual economy of the metaverse: Computer vision and deep learning algorithms, customer engagement tools, and behavioral predictive analytics. Linguistic and Philosophical Investigations, 21, 41. https://doi.org/10.22381/lpi2120223

Weizenbaum, J. (1966). ELIZA — a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36—45. https://doi.org/10.1145/365153.365168

Wormell, I. (1984). Cognitive aspects in natural language and free-text searching. Social Science Information Studies, 4(2—3), 131—141. https://doi.org/10.1016/0143-6236(84)90071-1

Yawalkar, V. V. (2019). A study of artificial intelligence and its role in human resource management. International Journal of Research and Analytical Reviews, 6(1), 20—24. https://www.ijrar.org/papers/IJRAR19UP004.pdf

Zadeh, L. (1965). Fuzzy sets. Information and Control, 8(3), 338—353.

Zadeh, L.A. (2008). Is there a need for fuzzy logic? Information Sciences, 178(13), 2751—2779. https://doi.org/10.1016/j.ins.2008.02.012

Zenkin, A., Kovalev, O., & Ovcharenko, H. (2016). Processes in complex enterprise management systems. Printing Technology and Techniques, 3(53), 81—87. https://doi.org/10.20535/2077-7264.3(53).2016.82429

Zhang, T., Ramakrishnan, R., & Livny, M. (1996). BIRCH: an efficient data clustering method for very large databases. In: Proceedings of the 1996 ACM SIGMOD international conference on Management. http://doi.acm.org/10.1145/233269.233324

Zhao, Y., Tang, L. C. M., Darlington, M. J., Austin, S. A., & Culley, S. J. (2008). High va­lue information in engineering organisations. International Journal of Information Mana­gement, 28(4), 246—258. https://doi.org/10.1016/j.ijinfomgt.2007.09.007

Zuboff, S. (2015). Big Other: Surveillance Capitalism and the Prospects of an Information Civilization. Journal of Information Technology 30, 75—89. https://doi:10.1057/jit.2015.5

Zuboff, S. (2019). Age of surveillance capitalism: The fight for a human future at the new frontier of power. PublicAffairs.

Zvarikova, K., Machova, V., & Nica, E. (2022). Cognitive artificial intelligence algorithms, movement and behavior tracking tools, and customer identification technology in the metaverse commerce. Review of Contemporary Philosophy, (21), 171—187.

Zvarikova, K., Michalikova, K., & Rowland, M. (2022). Retail data measurement tools, cognitive artificial intelligence algorithms, and metaverse live shopping analytics in immersive hyper-connected virtual spaces. Linguistic and Philosophical Investigations, 21, 9—24. https://doi.org/10.22381/lpi2120221