Formation of a mechanism for developing the economic potential of enterprises in the context of digital transformation and post-war reconstruction of Ukraine's economy
DOI:
https://doi.org/10.65026/sg4v9a49Keywords:
economic potential of the enterprise, digital transformation, fuzzy-logic development mechanism, post-war recovery of Ukraine, SME resilience, multi-level strategic managementAbstract
The article substantiates a mechanism for the development of the economic potential of the enterprise under conditions of digital transformation and post-war recovery of Ukraine. The research clarifies the essence and structure of economic potential and interprets it as a dynamic combination of production, financial, human, innovation, digital and organizational components. An integrated system of indicators and a fuzzy-logic model are developed to diagnose the state of these components, identify structural imbalances and classify enterprises into development trajectories: active growth, adaptive development, compensatory stabilization or conservative survival. Particular attention is paid to the digital component as a cross-cutting factor that reinforces all elements of economic potential and increases resilience to war-related shocks. A multi-level mechanism is proposed that combines enterprise-level diagnostics and fuzzy modeling with meso- and macro-level instruments of digitalization and SME support policy, providing a practical toolkit for aligning internal development strategies with national post-war recovery priorities.
References
[1]. Awasthi, A., Chauhan, S. S., & Omrani, H. (2011). Application of fuzzy TOPSIS in evaluating sustainable transportation systems. Expert Systems with Applications, 38(10), 12270–12280. https://doi.org/10.1016/j.eswa.2011.04.005
[2]. Babenko, V., Chebanova, N., Ryzhikova, N., Rudenko, S., & Birchenko, N. (2018). Research into the process of multi-level management of enterprise production activities with taking risks into consideration. Eastern-European Journal of Enterprise Technologies, 3(4), 4–12.
[3]. Babenko, V., Nazarenko, O., Nazarenko, I., & Mandych, O. (2018). Aspects of program control over technological innovations with consideration of risks. Eastern-European Journal of Enterprise Technologies, 34(2), 6–14.
[4]. David, M. E., & David, F. R. (2009). The quantitative strategic planning matrix (QSPM) applied to retail computer store. Coastal Business Journal, 8(1), 42–52.
[5]. Dziedzic, M., Zadrozny, S., & Kacprzyk, J. (2013). Bipolar linguistic summaries: A novel fuzzy querying-driven approach. In Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting (pp. 1279–1284). IEEE.
[6]. Fang, H. H., Lee, H. S., Hwang, S. N., & Chung, C. C. (2013). A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach. Omega, 41(4), 731–734. https://doi.org/10.1016/j.omega.2012.09.003
[7]. Kofman, A. (1982). Introduction to the theory of fuzzy sets. Radio i Svyaz Publishing.
[8]. Levchenko, M. O. (2013). Methods and technologies of innovative product output on the market. Herald of Khmelnytskyi National University, 3(1), 39–42.
[9]. Liu, W. B., Zhang, D. Q., Meng, W., Li, X. X., & Xu, F. (2011). A study of DEA models without explicit inputs. Omega, 39(5), 472–480. https://doi.org/10.1016/j.omega.2010.10.004
[10]. Malyshev, N. G., Bershtein, L. S., & Bozhenyuk, A. V. (1991). Fuzzy models for expert systems in CAD. Energoatomizdat Publishing.
[11]. Melikhov, A. N., Bernstein, L. C., & Korovin, S. Ya. (1990). Fuzzy situational advisory systems. Nauka Publishing.
[12]. Mohammadizadeh, M. J., Karbassi, A. R., Nabi Bidhendi, G. R., & Abbaspour, M. (2016). Integrated environmental management model of air pollution control by hybrid model of DPSIR and FAHP. Global Journal of Environmental Science and Management, 2(4), 381–388. https://doi.org/10.22034/gjesm.2016.02.04.007
[13]. Orlovskiy, S. A. (1981). Decision-making problems with fuzzy source information (pp. 1–256). Almaty, Kazakhstan: Nauka Publishing.
[14]. Peneder, M. (2001). Entrepreneurial competition and industrial location (pp. 1–312). Cheltenham, UK: Edward Elgar Publishing.
[15]. Telnov, A. (2019). Modeling of the processes of increasing foreign economic potential of the microeconomic system. Journal of Applied Economics and Management, 8(2), 45–63.
[16]. Vasylkivskyi, D. M. (2012). Formation of strategic decisions on managing the process of improving the economic potential of the enterprise. Actual Problems of the Economy, 4(1), 162–167.
[17]. Yaremenko, O. F. (2016). Scientific approaches to the concept of the economic system and its development. Herald of Khmelnytskyi National University, 6(2), 111–116.
[18]. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to making approximate decisions. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
[19]. Zare, K., Mehri-Tekmeh, J., & Karimi, S. (2015). A SWOT framework for analyzing the electricity supply chain using an integrated AHP methodology combined with fuzzy-TOPSIS. International Strategic Management Review, 3(1–2), 66–80. https://doi.org/10.1016/j.ism.2015.09.001
[20]. Zaredar, N., Kheirkhah Zarkesh, M., Jozi, S. A., & Ghadirpour, A. (2010). Investigation of fuzzy as well as Boolean logics application in land evaluation: Case study TALEGHAN basin-Iran. In Proceedings of the International Conference on Environmental and Agriculture Engineering (pp. 354–357). IACSIT Press.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Vitalii Vyshniuk, Halyna Skyba (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles published in the International Journal of Economics and Society (IJES) are licensed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and the source are properly credited.
