Expertise of Digital Reality as a Factor of Achieving Society Stability Under Stochastic Conditions (Uncertainty, Instability, Bifurcation)
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Abstract
Since we all live in a complex, interconnected, and interdependent world, in which the volumes of exponential information growth are increasing; since many leaders realize they are operating under conditions of stochasticity and uncertainty, the relevance of the analyzed problem remains extremely significant. The purpose of the article is to conceptualize the study of digital reality in matters of stochastic ambiguity based on system methodology and computer modeling. This conceptual and categorical apparatus aims to expose digital reality as a social phenomenon and a dynamic process. The principal approach to the research problem is a synergetic methodology that includes methods of consistency, structuredness, reasoning, and makes it credible to unveil the essence of the analysis of digital reality as a factor in achieving societal stability in circumstances of stochasticity, which is an integral process.
The article demonstrates that through the ability to predict, mistakes can be avoided, success can be achieved, and the prosperity of organizations can be multiplied. The article explains that the synergetic methodology, as a methodology of complexity, meets the conditions of globalization 4.0, Industry 4.0, technological progress 4.0, digital society, Enlightenment 2.0, and Agile management. It is for these complex requirements that a synergistic complexity methodology can be applied.
The materials presented in the article hold practical value for experts, scientists, and leaders. Implementation of this expertise will benefit society, the state, international partners, and future generations by promoting sustainable growth. The practical significance of the article lies in solving the problems of acquiring a conceptual framework for analyzing digital reality as a factor in achieving the efficiency and sustainability of society in circumstances of stochasticity. This approach enables the formulation of national, regional, local, and other indicators of sustainability and contributes to overcoming crises. All indicators mentioned can be manifested in absolute and relative dimensions, including indicators in the social sphere, such as health status, quality of life, social activity, demographics, and others.
DOI:
https://doi.org/10.61439/QEEE4158
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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Lorenz, E. N. (1963). Deterministic Nonperiodic Flow. Journal of the Atmospheric Sciences, 20(2), 130–141.
Lotman, J. (2009). Culture and explosion (M. Grishakova, Ed.; W. Clark, Trans.). De Gruyter Mouton.
Luhmann, N. (2013). Theory of Society (R. Barrett, Trans.; Vols. 1–2). Stanford University Press.
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Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.06.002
Misuraca, G., Baldry, D., & Centeno, C. (2012). Digital Europe 2030: Designing scenarios for ICT in future governance and policy making. Government Information Quarterly, 29, S121–S131. https://doi.org/10.1016/j.giq.2011.08.006
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Naisbitt, J. (2006). Mind set! Reset Your Thinking and See the Future. HarperBusiness.
Nikitenko, V. (2019a). The impact of digitalization on value orientations changes in the modern digital society. Humanities Studies, 2(79), 80–94. https://doi.org/10.26661/hst-2019-2-79-06
Nikitenko, V. (2019b). The matrix of creative-innovative potential of human as a factor of digital technologies, digital education and digital economy. Humanities Bulletin of Zaporizhzhe State Engineering Academy, 77, 133–143. http://dx.doi.org/10.26661/2072-1692-2019-77-10
Nikitenko, V. A. (2020). Evolyuciya koncepcii ustojchivogo razvitiya (v kontekste dokladov rimskogo kluba) [Evolution of the Concept of Sustainable Development (in the Context of the Reports of the Club of Rome)]. Journal of the Belarusian State University. Philosophy. Psychology, 2, 12–17.
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Scandizzo, P. L., & Ferrarese, C. (2015). Social accounting matrix: A new estimation methodology. Journal of Policy Modeling, 37(1), 14–34. https://doi.org/10.1016/j.jpolmod.2015.01.007
Sullivan, C. (2018). Digital identity – From emergent legal concept to new reality. Computer Law & Security Review, 34(4), 723–731. https://doi.org/10.1016/j.clsr.2018.05.015
Tabesh, P., Mousavidin, E., & Hasani, S. (2019). Implementing big data strategies: A managerial perspective. Business Horizons, 62(3), 347–358. https://doi.org/10.1016/j.bushor.2019.02.001
Terziyan, V., Gryshko, S., & Golovianko, M. (2018). Patented intelligence: Cloning human decision models for Industry 4.0. Journal of Manufacturing Systems, 48, 204–217. https://doi.org/10.1016/j.jmsy.2018.04.019
Tiwari, S., Wee, H., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & Industrial Engineering, 115, 319–330. https://doi.org/10.1016/j.cie.2017.11.017
Torrecilla, J. L., & Romo, J. (2018). Data learning from big data. Statistics & Probability Letters, 136, 15–19. https://doi.org/10.1016/j.spl.2018.02.038
Varela, F., Maturana, H. R., & Uribe, R. (1974). Autopoiesis: The organization of living systems, its characterization and a model. Biosystems, 5(4), 187–196. https://doi.org/10.1016/0303-2647(74)90031-8
Von Bertalanffy, L. (1950). An Outline of General System Theory. The British Journal for the Philosophy of Science, 1(2), 134–165. https://doi.org/10.1093/bjps/i.2.134
Von Weizsäcker, E. U., & Wijkman, A. (2017). Come On!: Capitalism, Short-termism, Population and the Destruction of the Planet. Springer.
Voronkova, V. G. (2019, November 13). Formuvannya Koncepciyi Ekspertnogo Menedzhmentu, yak Vimoga Cifrovizaciyi Suspilstva [Formation of the concept of expert management as a requirement for the digitalization of society] [Materials of round table]. Round table "Modern problems and prospects of economic, commodity and construction expertise" (pp. 89-91), Ukraine, Zaporizhzhia.
Wallerstein, I. M. (1998). Utopistics, Or, Historical Choices of the Twenty-first Century. The New Press.
Wilkin, C., Ferreira, A., Rotaru, K., & Gaerlan, L. R. (2020). Big data prioritization in SCM decision-making: Its role and performance implications. International Journal of Accounting Information Systems, 38, 100470. https://doi.org/10.1016/j.accinf.2020.100470
Zheng, D., Yu, L., & Wang, L. (2019). A techno-economic-risk decision-making methodology for large-scale building energy efficiency retrofit using Monte Carlo simulation. Energy, 189, 116169. https://doi.org/10.1016/j.energy.2019.116169
Al‐Badi, A. H., Tarhini, A., & Khan, A. I. (2018). Exploring big data governance frameworks. Procedia Computer Science, 141, 271–277. https://doi.org/10.1016/j.procs.2018.10.181
Aron, R. (1968). Progress and Disillusion: the dialectics of modern Society. Pall Mall Press.
Bell, D. (1973). The Coming of Post-Industrial Society: A Venture in Social Forecasting. Basic Books.
Blevins, B. (2018). Teaching Digital Literacy Composing concepts: Focusing on the layers of augmented reality in an era of changing technology. Computers and Composition, 50, 21–38. https://doi.org/10.1016/j.compcom.2018.07.003
Bodin, J. (2017). Jean Bodin (J. Franklin, Ed.). Routledge.
Brzezinski, Z. (2010). Out of Control: Global Turmoil on the Eve of the 21st Century. Simon and Schuster. (Original work published 1993)
Caesarius, L. M., & Hohenthal, J. (2018). Searching for big data. Scandinavian Journal of Management, 34(2), 129–140. https://doi.org/10.1016/j.scaman.2017.12.002
Cai, T., Wang, S., & Xu, Q. (2015). Monte Carlo optimization for site selection of new chemical plants. Journal of Environmental Management, 163, 28–38. https://doi.org/10.1016/j.jenvman.2015.08.002
Castells, M. (2007). Communication, power and counter-power in the network society. International Journal of Communication, 1(1), 29. https://robertoigarza.files.wordpress.com/2009/07/art-after-mobile-phones-what-case-china-zhao-2007.pdf
Chen, S., & You, F. (2019). Data Analytics and Machine learning for smart process Manufacturing: Recent advances and perspectives in the Big Data Era. Engineering, 5(6), 1010–1016. https://doi.org/10.1016/j.eng.2019.01.019
Chopra, S. S., & Khanna, V. (2015). Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience. Physica A: Statistical Mechanics and Its Applications, 436, 865–877. https://doi.org/10.1016/j.physa.2015.05.091
Dávila, X., & Maturana, H. (2019). Historia de nuestro vivir cotidiano [History of our daily life]. Paidos Chile.
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
Dufva, T., & Dufva, M. (2019). Grasping the future of the digital society. Futures, 107, 17–28. https://doi.org/10.1016/j.futures.2018.11.001
Fang, L., Cheng, J., & Su, F. (2019). Interconnectedness and systemic risk: A comparative study based on systemically important regions. Pacific-Basin Finance Journal, 54, 147–158. https://doi.org/10.1016/j.pacfin.2019.02.007
Fukuyama, F. (2003). Our posthuman future: Consequences of the Biotechnology Revolution. Frofile Books.
Giddens, A. (1990). The consequences of modernity. Polity.
Holford, W. D. (2019). The future of human creative knowledge work within the digital economy. Futures, 105, 143–154. https://doi.org/10.1016/j.futures.2018.10.002
Gandomi, A. H., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
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
Karagiannidis, I., & Wilford, D. S. (2015). Modeling fund and portfolio risk: A bi‐modal approach to analyzing risk in turbulent markets. Review of Financial Economics, 25(1), 19–26. https://doi.org/10.1016/j.rfe.2015.02.005
Khalaf, L., & Saunders, C. J. (2017). Monte Carlo forecast evaluation with persistent data. International Journal of Forecasting, 33(1), 1–10. https://doi.org/10.1016/j.ijforecast.2016.06.004
Kyrychenko, M. (2019). The impact of digital technologies on the development of human and social capital in a digitalized society. Humanities Studies, 1(78), 108–129.
Kurt, R. (2019). Industry 4.0 in terms of industrial relations and its impacts on labour life. Procedia Computer Science, 158, 590–601. https://doi.org/10.1016/j.procs.2019.09.093
Lechner, S., Jacometti, J., McBean, G., & Mitchison, N. (2016). Resilience in a complex world – Avoiding cross-sector collapse. International Journal of Disaster Risk Reduction, 19, 84–91. https://doi.org/10.1016/j.ijdrr.2016.08.006
Lepskiy, M. (2020, March 17). What will be our future: forecast of Zaporizhzhia academician. Inform.zp. https://www.inform.zp.ua/ru/2020/03/18/90199_kakim-budet-nashe-budushhee-prognoz-zaporozhskogo-akademika/
Lien, D. (2017). Business Finance and Enterprise Management in the Era of Big Data: An introduction. The North American Journal of Economics and Finance. https://doi.org/10.1016/j.najef.2016.10.002
Lorenz, E. N. (1963). Deterministic Nonperiodic Flow. Journal of the Atmospheric Sciences, 20(2), 130–141.
Lotman, J. (2009). Culture and explosion (M. Grishakova, Ed.; W. Clark, Trans.). De Gruyter Mouton.
Luhmann, N. (2013). Theory of Society (R. Barrett, Trans.; Vols. 1–2). Stanford University Press.
Mandelbrot, B. B. (1983). The Fractal Geometry of Nature. Times Books.
Meadows, D. H., Meadows, D. L., & Randers, J. (2004). Limits to growth the 30-year update. Earthscan.
Mergel, I., Edelmann, N., & Haug, N. (2019). Defining digital transformation: Results from expert interviews. Government Information Quarterly, 36(4), 101385. https://doi.org/10.1016/j.giq.2019.06.002
Misuraca, G., Baldry, D., & Centeno, C. (2012). Digital Europe 2030: Designing scenarios for ICT in future governance and policy making. Government Information Quarterly, 29, S121–S131. https://doi.org/10.1016/j.giq.2011.08.006
Morin, É. (1992). The concept of system and the paradigm of complexity. In M. Maruyama (Ed.), Context and Complexity (pp. 125–138). https://doi.org/10.1007/978-1-4612-2768-7_6
Naisbitt, J. (2006). Mind set! Reset Your Thinking and See the Future. HarperBusiness.
Nikitenko, V. (2019a). The impact of digitalization on value orientations changes in the modern digital society. Humanities Studies, 2(79), 80–94. https://doi.org/10.26661/hst-2019-2-79-06
Nikitenko, V. (2019b). The matrix of creative-innovative potential of human as a factor of digital technologies, digital education and digital economy. Humanities Bulletin of Zaporizhzhe State Engineering Academy, 77, 133–143. http://dx.doi.org/10.26661/2072-1692-2019-77-10
Nikitenko, V. A. (2020). Evolyuciya koncepcii ustojchivogo razvitiya (v kontekste dokladov rimskogo kluba) [Evolution of the Concept of Sustainable Development (in the Context of the Reports of the Club of Rome)]. Journal of the Belarusian State University. Philosophy. Psychology, 2, 12–17.
Oleksenko, R. I. (2013). Globalni problemi filosofiyi vid Antichnosti do sogodennya v diskursi rinkovih transformacij [Global problems of philosophy in Antiquity up to the present day in the discourse of market transformations] [Materials of conference]. Prydniprovsky Social and Humanitarian Readings: in 6 Parts. Part 2: Materials of the Dnipropetrovsk Session of the II All-Ukrainian Scientific-practical Conference with International Participation (pp. 148-151), Dnipropetrovsk, Ukraine.
Ouyang, M. (2014). Review on modeling and simulation of interdependent critical infrastructure systems. Reliability Engineering & System Safety, 121, 43–60. https://doi.org/10.1016/j.ress.2013.06.040
Ranerup, A., & Henriksen, H. (2019). Value positions viewed through the lens of automated decision-making: The case of social services. Government Information Quarterly, 36(4), 101377. https://doi.org/10.1016/j.giq.2019.05.004
Roukny, T., Battiston, S., & Stiglitz, J. E. (2018). Interconnectedness as a source of uncertainty in systemic risk. Journal of Financial Stability, 35, 93–106. https://doi.org/10.1016/j.jfs.2016.12.003
Secchi, P. (2018). On the role of statistics in the era of big data: A call for a debate. Statistics & Probability Letters, 136, 10–14. https://doi.org/10.1016/j.spl.2018.02.041
Scandizzo, P. L., & Ferrarese, C. (2015). Social accounting matrix: A new estimation methodology. Journal of Policy Modeling, 37(1), 14–34. https://doi.org/10.1016/j.jpolmod.2015.01.007
Sullivan, C. (2018). Digital identity – From emergent legal concept to new reality. Computer Law & Security Review, 34(4), 723–731. https://doi.org/10.1016/j.clsr.2018.05.015
Tabesh, P., Mousavidin, E., & Hasani, S. (2019). Implementing big data strategies: A managerial perspective. Business Horizons, 62(3), 347–358. https://doi.org/10.1016/j.bushor.2019.02.001
Terziyan, V., Gryshko, S., & Golovianko, M. (2018). Patented intelligence: Cloning human decision models for Industry 4.0. Journal of Manufacturing Systems, 48, 204–217. https://doi.org/10.1016/j.jmsy.2018.04.019
Tiwari, S., Wee, H., & Daryanto, Y. (2018). Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Computers & Industrial Engineering, 115, 319–330. https://doi.org/10.1016/j.cie.2017.11.017
Torrecilla, J. L., & Romo, J. (2018). Data learning from big data. Statistics & Probability Letters, 136, 15–19. https://doi.org/10.1016/j.spl.2018.02.038
Varela, F., Maturana, H. R., & Uribe, R. (1974). Autopoiesis: The organization of living systems, its characterization and a model. Biosystems, 5(4), 187–196. https://doi.org/10.1016/0303-2647(74)90031-8
Von Bertalanffy, L. (1950). An Outline of General System Theory. The British Journal for the Philosophy of Science, 1(2), 134–165. https://doi.org/10.1093/bjps/i.2.134
Von Weizsäcker, E. U., & Wijkman, A. (2017). Come On!: Capitalism, Short-termism, Population and the Destruction of the Planet. Springer.
Voronkova, V. G. (2019, November 13). Formuvannya Koncepciyi Ekspertnogo Menedzhmentu, yak Vimoga Cifrovizaciyi Suspilstva [Formation of the concept of expert management as a requirement for the digitalization of society] [Materials of round table]. Round table "Modern problems and prospects of economic, commodity and construction expertise" (pp. 89-91), Ukraine, Zaporizhzhia.
Wallerstein, I. M. (1998). Utopistics, Or, Historical Choices of the Twenty-first Century. The New Press.
Wilkin, C., Ferreira, A., Rotaru, K., & Gaerlan, L. R. (2020). Big data prioritization in SCM decision-making: Its role and performance implications. International Journal of Accounting Information Systems, 38, 100470. https://doi.org/10.1016/j.accinf.2020.100470
Zheng, D., Yu, L., & Wang, L. (2019). A techno-economic-risk decision-making methodology for large-scale building energy efficiency retrofit using Monte Carlo simulation. Energy, 189, 116169. https://doi.org/10.1016/j.energy.2019.116169