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ІННОВАЦІЙНІ МОЖЛИВОСТІ ВИКОРИСТАННЯ HR-МЕНЕДЖМЕНТУ У ВИЩІЙ ШКОЛІ В ПОРІВНЯННІ З ЄС
Get PDFThe article is devoted to the current conditions of highereducation development, where human capital management has become a key factor inenhancing the competitiveness of universities. HR management in higher education encompasses awide range of functions, from recruitment and staff onboarding to the development of professionalcompetencies, motivation, performance evaluation, and the formation of corporate culture.Efficient HR management in higher education becomes a crucial factor in enhancing educationquality, developing faculty professional competencies, and increasing the competitiveness ofuniversities. It is particularly important to explore modern HR opportunities and innovativeapproaches by comparing the Ukrainian experience with EU practices in order to adapt effectivepersonnel management models in domestic higher education institutions.The study identifies the main innovative HR management practices in higher education, includingHR analytics and Big Data for evaluating faculty performance, digital platforms for staff learningand development, gamification, and remote management. Their impact on university managementefficiency, motivation of academic and administrative personnel, productivity improvement, and theformation of a modern university image as an attractive employer is substantiated.Innovative approaches to HR management are an important factor for the successfultransformation of higher education institutions into a digital and competitive educationalenvironment. They enhance the adaptability of institutions to changes in the labor market andacademic requirements, ensure the development of human resources, and facilitate the integration ofUkrainian universities into the European Higher Education Area.Keywords: HR management, higher education, digitalization, innovations, digital transformation,HR analytics, employee motivation.
References1. Kozhushko R. (2020). Human capital management in higher education institutions.Management. Vol. 1, No. 31, рр. 49-56. (In Ukrainian)2. Adias, J. (2025). Human Resources Management Strategies in Higher Education Institutions:Addressing Workforce Challenges and Enhancing Performance. European Journal of Business andManagement, Vol. 17, No 6, рр 77-86.3. Biriuchenko, S. Yu., Ostapchuk, T. P., & Orlova, K. Ye. (2023). Professional ethics in HRmanagement. Economics, Management and Administration, Vol. 2, No. 104, рр. 51–57. (inUkrainian)4. Orel, Yu. L., & Smahliuk, A. A. (2023). HR management in Ukrainian business: challengesof digitalization. Academic Visions, No. 19. (in Ukrainian)5. Korolenko O., Kutova N. (2023). HR management of the enterprise: challenges and realitiesof today. Economy and Society. (53). С. 1-6. (in Ukrainian).6. Soroka, A. M., & Zasanskyi, V. V. (2024). Integration of HR management and timemanagement in the personnel management system of higher education institutions. ScientificCollection of NASOA, (4) С. 86-94. (in Ukrainian).Стаття присвячена сучасним умовам розвитку вищої освіти де управління людськимкапіталом стає ключовим фактором підвищення конкурентоспроможності університетів.HR-менеджмент у вищій школі охоплює широкий спектр функцій: від добору та адаптаціїперсоналу до розвитку професійних компетенцій, мотивації, оцінювання ефективності таформування корпоративної культури.Основні результати дослідження: виокремлено ключові інноваційні практики HRменеджменту у вищій школі, серед яких HR-аналітика та Big Data для оцінюванняефективності викладачів, цифрові платформи для навчання та розвитку персоналу,гейміфікація, віддалене управління; обґрунтовано безпосередній та опосередкований впливінноваційних практики HR-менеджменту на ефективність управління та мотиваціївикладацького та адміністративного персоналу, підвищення продуктивності праці таформування сучасного іміджу університету як привабливого роботодавця.Ключові слова: HR-менеджмент, вища школа, цифровізація, інновації, цифроватрансформація, HR-аналітика, мотивація персоналу.
Перелік посилань1. Kozhushko R. (2020). Human capital management in higher education institutions.Management. Vol. 1, No. 31, рр. 49-56. (In Ukrainian)2. Adias, J. (2025). Human Resources Management Strategies in Higher Education Institutions:Addressing Workforce Challenges and Enhancing Performance. European Journal of Business andManagement, Vol. 17, No 6, рр 77-86.3. Biriuchenko, S. Yu., Ostapchuk, T. P., & Orlova, K. Ye. (2023). Professional ethics in HRmanagement. Economics, Management and Administration, Vol. 2, No. 104, рр. 51–57. (inUkrainian)4. Orel, Yu. L., & Smahliuk, A. A. (2023). HR management in Ukrainian business: challengesof digitalization. Academic Visions, No. 19. (in Ukrainian)5. Korolenko O., Kutova N. (2023). HR management of the enterprise: challenges and realitiesof today. Economy and Society. (53). С. 1-6. (in Ukrainian).6. Soroka, A. M., & Zasanskyi, V. V. (2024). Integration of HR management and timemanagement in the personnel management system of higher education institutions. ScientificCollection of NASOA, (4) С. 86-94. (in Ukrainian)
СУЧАСНІ ТРАНСФОРМАЦІЇ ЗОВНІШНЬОЕКОНОМІЧНОЇ ДІЯЛЬНОСТІ В УМОВАХ ГЛОБАЛЬНОЇ НЕСТАБІЛЬНОСТІ
No full textThe article examines modern transformations of foreign economic activity of enterprises in thecontext of global economic and geopolitical instability. The impact of crisis phenomena, armedconflicts, sanctions policy, disruption of international logistics chains and deglobalization processeson the mechanisms of foreign economic operations is analyzed. The key challenges faced by foreigneconomic entities are identified, in particular, the growth of trade risks, the instability of currencymarkets, the transformation of the export and import structure. The need for a strategic rethinking ofapproaches to managing foreign economic activity is substantiated, taking into account therequirements of flexibility, market diversification and digitalization of international businessprocesses. Directions for increasing the efficiency of foreign economic activity are proposed bydeveloping logistical sustainability, integrating digital tools and improving the risk managementsystem.Keywords: foreign economic activity, global instability, international trade, logistics,digitalization , risks.
References1. Kozik, V. V. (2022). Zovnishnoekonomichna diialnist pidpryiemstv: teoriia ta praktyka[Foreign Economic Activity of Enterprises: Theory and Practice]. Kyiv: Znannia.2. Porter, M. E. (2020). The Competitive Advantage of Nations. New York, NY: Free Press.3. World Trade Organization. (2023). World Trade Report. Geneva: WTO. Available on the WTOOfficial Website. https://www.wto.org/english/res_e/booksp_e/wtr23_e/wtr23_e.pdf4. United Nations Conference on Trade and Development. (2024). Global Trade Update. NewYork; Geneva: UNCTAD. Available via the UNCTAD Data Portal.https://unctad.org/publication/global-trade-update-july-20245. International Monetary Fund. (2025). World economic outlook: Policy pivot, globaluncertainties. www.imf.org https://www.imf.org/en/publications/weo6. Krugman, P. R., Obstfeld, M., & Melitz, M. J. (2024). International economics: Theory andpolicy (12th global ed.).. DOI: https://doi.org/10.36348/sjef.2025.v09i11.0037. Organisation for Economic Co-operation and Development. (2025). OECD economic outlook,volume 2025 issue 2. OECD https://www.oecd.org/en/publications/oecd-economic-outlook-volume2025-issue-2_9f653ca1-en.html8. United Nations Conference on Trade and Development. (2025). Trade and developmentforesights 2025: Under pressure – Uncertainty reshapes global economic prospects. United Nations.unctad https://unctad.org/system/files/official-document/tdr2025_en.pdfУ статті досліджено сучасні трансформаціїзовнішньоекономічної діяльності підприємств в умовах глобальної економічної тагеополітичної нестабільності. Проаналізовано вплив кризових явищ, збройних конфліктів,санкційної політики, порушення міжнародних логістичних ланцюгів і процесів деглобалізаціїна механізми здійснення зовнішньоекономічних операцій. Визначено ключові виклики, зякими стикаються суб’єкти зовнішньоекономічної діяльності, зокрема зростанняторговельних ризиків, нестабільність валютних ринків, трансформацію структури експорту таімпорту. Обґрунтовано необхідність стратегічного переосмислення підходів до управліннязовнішньоекономічною діяльністю з урахуванням вимог гнучкості, диверсифікації ринків іцифровізації міжнародних бізнес-процесів. Запропоновано напрями підвищення ефективностіЗЕД шляхом розвитку логістичної стійкості, інтеграції цифрових інструментів і вдосконаленнясистеми ризик-менеджменту.Ключові слова: зовнішньоекономічна діяльність, глобальна нестабільність, міжнароднаторгівля, логістика, цифровізація, ризики.
Перелік посилань1. Kozik, V. V. (2022). Zovnishnoekonomichna diialnist pidpryiemstv: teoriia ta praktyka[Foreign Economic Activity of Enterprises: Theory and Practice]. Kyiv: Znannia.2. Porter, M. E. (2020). The Competitive Advantage of Nations. New York, NY: Free Press.3. World Trade Organization. (2023). World Trade Report. Geneva: WTO. Available on the WTOOfficial Website. https://www.wto.org/english/res_e/booksp_e/wtr23_e/wtr23_e.pdf4. United Nations Conference on Trade and Development. (2024). Global Trade Update. NewYork; Geneva: UNCTAD. Available via the UNCTAD Data Portal.https://unctad.org/publication/global-trade-update-july-20245. International Monetary Fund. (2025). World economic outlook: Policy pivot, globaluncertainties. www.imf.org https://www.imf.org/en/publications/weo6. Krugman, P. R., Obstfeld, M., & Melitz, M. J. (2024). International economics: Theory andpolicy (12th global ed.).. DOI: https://doi.org/10.36348/sjef.2025.v09i11.0037. Organisation for Economic Co-operation and Development. (2025). OECD economic outlook,volume 2025 issue 2. OECD https://www.oecd.org/en/publications/oecd-economic-outlook-volume2025-issue-2_9f653ca1-en.html8. United Nations Conference on Trade and Development. (2025). Trade and developmentforesights 2025: Under pressure – Uncertainty reshapes global economic prospects. United Nations.unctad https://unctad.org/system/files/official-document/tdr2025_en.pd
ОБЛІК В РЕАЛЬНОМУ ЧАСІ: ЗМІНА АКЦЕНТІВ З КОНТРОЛЬНОЇ НА ІНФОРМАЦІЙНУ ФУНКЦІЮ
Get PDFIn the contemporary landscape of the economy's digital transformation, a noticeable decline inthe effectiveness of traditional accounting as a source of reliable and up-to-date information forinformed management decisions has been observed. Conventional accounting, which predominantlyfocuses on its control function and the retrospective recording of transactions, often fails to providethe timely information essential for agile operational management. This deficiency frequently leads to the duplication of functions and the fragmentation of information flows across an organization.The solution to this pressing problem lies in the transition to real-time accounting. Thisinnovative approach significantly enhances the timeliness and relevance of accounting information,thereby making it invaluable for enterprise management in making critical decisions. Such aparadigm shift simultaneously strengthens the function of prompt informational support formanagement and other stakeholders, all while diligently preserving the fundamental control functionof accounting. The advancement of real-time accounting directly aligns with the strategic objectivesof Ukraine's economy, which include reducing the administrative burden on businesses, ensuring thetransparency of economic processes, fostering the development of digital infrastructure, andfacilitating integration into the European economic space. This approach is fully consistent with theEuropean Real-Time Economy (RTE) model, which is already being successfully implemented in theBaltic region countries as a powerful tool to support productivity, innovation, and competitiveness,particularly for small and medium-sized enterprises.The concept of "real-time accounting" has been a subject of discussion since the 1970s, but ithas gained unprecedented relevance with the rapid development of information and communicationtechnologies, notably cloud solutions, blockchain technologies, and Enterprise Resource Planning(ERP) systems. Recent studies by both Ukrainian and Western scholars unequivocally confirm theheightened attention given to real-time accounting within the context of enterprises' digitaltransformation. The emphasis is increasingly placed on the shift towards "continuous auditing" andreal-time reporting, leveraging ERP systems, cloud platforms, and big data analytics to ensureconstant data availability and control. In the European discourse, the concept of the Real-TimeEconomy (RTE) is actively evolving, envisioning an environment where accounting serves not onlyas a source of financial information but also as a crucial instrument of digital management.Keywords: real-time accounting, real-time economy, accounting information systems,accounting innovation, accountants professional development.
References1. Alishani, A., et al. (2025). Real-Time economy: a new frontier in business and economicgrowth. Halduskultuur, 23(1-2), 129–155. https://doi.org/10.32994/hk.v23i1-2.3142. Alles, M., Kogan, A., & Vasarhelyi, M. A. (2000). Accounting in 2015. CPA JOURNAL,70(11), 14-21.3. Babinska, S. (2021). Accounting in the conditions of implementing modern informationtechnologies. Economy and Society, (26). https://doi.org/10.32782/2524-0072/2021-26-14. Belfo, F., Trigo, A., & Estébanez, R. P. (2015). Impact of ICT Innovative Momentum onReal-Time Accounting. Business Systems Research Journal, 6(2), 1–17. https://doi.org/10.1515/bsrj2015-00075. Kutsyk, P. O. (2023). Providing assurance on the reliability of accounting and reporting datain real-time: main approaches. Accounting, Analysis, Audit, Taxation and Financial Monitoring inthe Conditions of Post-War Reconstruction of Ukraine: Collection of materials of the IX Internationalscientific and practical conference, Kyiv, December 8, 2023. Kyiv. Retrieved from [підозрілепосилання видалено]6. Kuz, V. I. (2021). Development of accounting in the conditions of digitalization of economicand management processes. Business Inform, 6(521), 197–204. https://doi.org/10.32983/2222-4459-2021-6-197-2047. Lemishovska, O., & Lynynska, V. (2022). Accounting in the conditions of implementinginformation technologies and systems. Economy and Society, (44). https://doi.org/10.32782/2524-0072/2022-44-238. Palyukh, M., & Spilnyk, I. (2017). Accounting in the digital economy. Institute of Accounting,Control and Analysis in the Conditions of Globalization, (1-2), 83–96.https://doi.org/10.35774/ibo2019.01.0839. Popivnyak, Yu. M. (2019). Blockchain technology in accounting and auditing: current state,opportunities and prospects of application. Economy, Management and Administration, (3(89)), 137–144. https://doi.org/10.26642/ema-2019-3(89)-137-14410. Rezaee, Z., et al. (2000, April). REAL-TIME ACCOUNTING SYSTEMS. Internal Auditor,57(2), 62. Retrieved fromlink.gale.com/apps/doc/A63170655/AONE?u=anon~2a4b62ce&sid=googleScholar&xid=6e5f69b111. Schmidt, E. (n.d.). EBS Mechdata celebrates 50 years. Material Handling Wholesaler.Retrieved from https://www.mhwmag.com/features/ebs-mechdata-celebrates-50-years/12. Siegele, L. (2002, February 2). How about now? The Economist, Special Report. Retrievedfrom https://www.economist.com/special-report/2002/02/02/how-about-now13. SYSPRO Corporate. (n.d.). SYSPRO history. Retrieved fromhttps://www.syspro.com/syspro-history/14. Vysochan, O., & Hrytseliak, U. (2020). Prerequisites and problems of digital transformationof the accounting and communication process. Scientific View: Economics and Management, (3(69)).https://doi.org/10.32836/2521-666x/2020-69-22У сучасних умовах цифрової трансформації економіки спостерігається зниженняефективності бухгалтерського обліку як джерела достовірної та актуальної інформації дляприйняття управлінських рішень. Традиційний облік, зосереджений на контрольній функціїта ретроспективному відображенні операцій, не забезпечує своєчасного отриманняінформації, необхідної для оперативного управління. Це призводить до дублювання функційта фрагментації інформаційних потоків.Вирішенням цієї проблеми є перехід до обліку в реальному часі, що дозволяє підвищитиоперативність та релевантність облікової інформації, роблячи її корисною для керівництвапідприємством при прийнятті управлінських рішень. Такий підхід сприяє одночасномупосиленню функції оперативного інформування управління та інших користувачів зізбереженням контрольної функції обліку. Розвиток обліку в реальному часі безпосередньовідповідає стратегічним завданням економіки України, серед яких — зниженняадміністративного навантаження на бізнес, забезпечення прозорості економічних процесів,розвиток цифрової інфраструктури та інтеграція в європейський економічний простір. Цеузгоджується з європейською моделлю Real-Time Economy (RTE), яка вже впроваджуєтьсяв країнах Балтійського регіону як інструмент підтримки продуктивності, інновацій таконкурентоспроможності малих і середніх підприємств.Ключові слова: облік у реальному часі, економіка реального часу, облікові інформаційнісистеми, інновації в обліку, розвиток професії бухгалтера.
Перелік посилань1. Alishani, A., et al. (2025). Real-Time economy: a new frontier in business and economicgrowth. Halduskultuur, 23(1-2), 129–155. https://doi.org/10.32994/hk.v23i1-2.3142. Alles, M., Kogan, A., & Vasarhelyi, M. A. (2000). Accounting in 2015. CPA JOURNAL,70(11), 14-21.3. Babinska, S. (2021). Accounting in the conditions of implementing modern informationtechnologies. Economy and Society, (26). https://doi.org/10.32782/2524-0072/2021-26-14. Belfo, F., Trigo, A., & Estébanez, R. P. (2015). Impact of ICT Innovative Momentum onReal-Time Accounting. Business Systems Research Journal, 6(2), 1–17. https://doi.org/10.1515/bsrj2015-00075. Kutsyk, P. O. (2023). Providing assurance on the reliability of accounting and reporting datain real-time: main approaches. Accounting, Analysis, Audit, Taxation and Financial Monitoring inthe Conditions of Post-War Reconstruction of Ukraine: Collection of materials of the IX Internationalscientific and practical conference, Kyiv, December 8, 2023. Kyiv. Retrieved from [підозрілепосилання видалено]6. Kuz, V. I. (2021). Development of accounting in the conditions of digitalization of economicand management processes. Business Inform, 6(521), 197–204. https://doi.org/10.32983/2222-4459-2021-6-197-2047. Lemishovska, O., & Lynynska, V. (2022). Accounting in the conditions of implementinginformation technologies and systems. Economy and Society, (44). https://doi.org/10.32782/2524-0072/2022-44-238. Palyukh, M., & Spilnyk, I. (2017). Accounting in the digital economy. Institute of Accounting,Control and Analysis in the Conditions of Globalization, (1-2), 83–96.https://doi.org/10.35774/ibo2019.01.0839. Popivnyak, Yu. M. (2019). Blockchain technology in accounting and auditing: current state,opportunities and prospects of application. Economy, Management and Administration, (3(89)), 137–144. https://doi.org/10.26642/ema-2019-3(89)-137-14410. Rezaee, Z., et al. (2000, April). REAL-TIME ACCOUNTING SYSTEMS. Internal Auditor,57(2), 62. Retrieved fromlink.gale.com/apps/doc/A63170655/AONE?u=anon~2a4b62ce&sid=googleScholar&xid=6e5f69b111. Schmidt, E. (n.d.). EBS Mechdata celebrates 50 years. Material Handling Wholesaler.Retrieved from https://www.mhwmag.com/features/ebs-mechdata-celebrates-50-years/12. Siegele, L. (2002, February 2). How about now? The Economist, Special Report. Retrievedfrom https://www.economist.com/special-report/2002/02/02/how-about-now13. SYSPRO Corporate. (n.d.). SYSPRO history. Retrieved fromhttps://www.syspro.com/syspro-history/14. Vysochan, O., & Hrytseliak, U. (2020). Prerequisites and problems of digital transformationof the accounting and communication process. Scientific View: Economics and Management, (3(69)).https://doi.org/10.32836/2521-666x/2020-69-2
ОСОБЛИВОСТІ ЦИФРОВОЇ ЕКОСИСТЕМИ ВАНТАЖНИХ ПЕРЕВЕЗЕНЬ: ПОРІВНЯННЯ ДОСВІДУ ЄС ТА УКРАЇНИ
Get PDFThis article develops an integrated framework for systematizing the European and Ukrainianexperience of freight transport digitalization by articulating the complementarity of three layers: theelectronic consignment notes for road transport (eCMR) as the logistics layer, the electronic FreightTransport Information (eFTI) as the regulatory channel, and customs/maritime Single Window as theorganizational node. The study sets out to establish a coherent model that aligns data interoperabilityrequirements with governance arrangements and operational performance indicators across portsand road freight. The research design combines a protocolized systematic review (PRISMA‑2020),comparative case analysis, and institutional reasoning about data stewardship inbusiness‑to‑government ecosystems. The evidence base consists of peer‑reviewed journal articlespublished between 2020 and 2025 and indexed by Scopus or Web of Science, each assigned a DOI.The proposed three‑layer model explains how eCMR provides the minimal data backbone fortransport execution, eFTI creates a legally binding channel for accepting regulatory information indigital form across all transport modes, and Single Windows operate as multi‑agency gateways thatorchestrate submission, routing, and feedback. The article formalizes stewardship configurations(public leadership, co‑leadership, and regulatory leadership) and clarifies their implications fortransaction costs, auditability, and incentives for voluntary information sharing by firms. Withinseaports, Port Community Systems are positioned as the operational integration layer interlinkedwith Maritime Single Window/EMSWe; in road freight, platform typologies (marketplaces, visibilityservices, planning optimizers, analytics) are mapped to the minimal eCMR/eFTI datasets to enableevent‑driven process reuse without redundant data entry. The article also delineates a KPI set thatconnects data quality and event models with measurable improvements—such as vessel turnaroundtime, slot accuracy, community acceptance, declaration processing time, and firm‑level efficiency—showing their dependence on interoperable data profiles. The contribution lies in synthesizing datagovernance mechanisms with semantic alignment of messages and identifying a phasedimplementation pathway for countries harmonizing with EU acquis. For Ukraine, the paperrecommends a staged approach that prioritizes data profile mapping, event‑oriented processes, andneutral data operators in ports, together with capacity‑building and targeted incentives. Theframework offers a replicable basis for policymakers and managers to orchestrate digital freightecosystems, align stakeholders around shared data assets, and monitor performance through acompact yet meaningful KPI suite.Keywords: digital ecosystem, logistics infrastructure, eCMR; eFTI; Single Window; PortCommunity System; data interoperability; data management; logistics KPIs.
References1. Balić, K., Stočko, D., & Delchev, D. (2022). The port system in addressing sustainabilityissues—A systematic literature review. Journal of Marine Science and Engineering, 10(8), 1048.https://doi.org/10.3390/jmse100810482. Brunila, O.-P., Inkinen, T., Tapaninen, U., Hämäläinen, E., & Saarikoski, J. (2021).Hindrances in port digitalization? Identifying problems in the digitalization of Finnish ports.European Transport Research Review, 13, 24. https://doi.org/10.1186/s12544-021-00523-03. Caldeirinha, V., Felício, J., Dooms, M., & Carlan, V. (2022). Port Community Systems:Accelerating the transition of the maritime supply chain. Journal of Marine Science and Engineering,10(2), 152. https://doi.org/10.3390/jmse100201524. Dasaklis, T. K., Kopanaki, E., Chountalas, P. T., Rachaniotis, N. P., Voutsinas, T. G.,Giannakis, K., & Chondrokoukis, G. (2024). Exploring the implementation challenges of theElectronic Freight Transport Information (eFTI) Regulation: An empirical perspective from Greece.Logistics, 8(1), 30. https://doi.org/10.3390/logistics80100305. Fahim, P. B. M., Nguyen, H. O., & Fahim, M. (2024). Alignment of port policy to the contextof the Physical Internet. Maritime Policy & Management.https://doi.org/10.1080/03088839.2022.21475946. Felício, J. A., Batista, M., Dooms, M., & Caldeirinha, V. (2023). How do sustainable portpractices influence local communities’ perceptions of ports? Maritime Economics & Logistics.https://doi.org/10.1057/s41278-022-00237-77. Gavalas, D., Syriopoulos, T., & Roumpis, E. (2022). Digital adoption and efficiency in themaritime industry. Journal of Shipping and Trade, 7, 11. https://doi.org/10.1186/s41072-022-00111-y8. Heikkilä, M., Kandjani, A., & Suominen, A. (2022). Innovation in Smart Ports: Futuredirections of digitalization. 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The PRISMA 2020 statement: An updated guideline for reporting systematicreviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n7121. Pan, S., Trentesaux, D., Ballot, E., Huang, G. Q., & Lam, D. (2021). Smart city for sustainableurban freight logistics: A review. International Journal of Production Research, 59(7), 2041–2063.https://doi.org/10.1080/00207543.2021.189397022. Peynirci, E. (2021). The rise of emerging technologies: A quantitative-based research on“maritime single window” in Turkey. Research in Transportation Business & Management, 46,100770. https://doi.org/10.1016/j.rtbm.2021.10077023. Raza, Z., Woxenius, J., Vural, C. A., & Lind, M. (2023). Digital transformation of maritimelogistics: Exploring trends in the liner shipping segment. Computers in Industry, 145, 103811.https://doi.org/10.1016/j.compind.2022.10381124. Rukanova, B., Henningsson, S., Henriksen, H. Z., & Tan, Y.-H. (2023). Public value creationthrough voluntary business-to-government information sharing: Mechanisms and enablingconditions. Government Information Quarterly, 40(1), 101786.https://doi.org/10.1016/j.giq.2022.10178625. Tijan, E., Jović, M., Panjako, A., & Žgaljić, D. (2021). The role of port authority in portgovernance and Port Community System implementation. Sustainability, 13(5), 2795.https://doi.org/10.3390/su1305279526. Tomicová, J., Poliak, M., & Zhuravleva, N. (2021). Impact of using e-CMR on neutralizationof consignment note. Transportation Research Procedia, 55, 1278–1285.https://doi.org/10.1016/j.trpro.2021.06.01227. van Donge, W., Bharosa, N., & Janssen, M. (2022). Data-driven government: Cross-casecomparison of data stewardship in data ecosystems. Government Information Quarterly, 39(2),101642. https://doi.org/10.1016/j.giq.2021.10164228. Wen, X., Chen, Q., Yin, Y.-Q., Lau, Y.-Y., & Dulebenets, M. A. (2024). Multi-objectiveoptimization for ship scheduling with port congestion and environmental considerations. Journal ofMarine Science and Engineering, 12(1), 114. https://doi.org/10.3390/jmse1201011429. Yap, W. Y., & Ho, J. (2023). Port strategy and performance: Empirical evidence from majorcontainer ports and implications for the role of data analytics. Maritime Policy & Management, 50(5),608–628. https://doi.org/10.1080/03088839.2021.201704030. Čerin, P., Perić Hadžić, A., & Žgaljić, D. (2023). Digitalisation of the port community throughthe development of advanced port communication systems (PCSs): A case study of the Port of Koper.Sustainability, 16(1), 348. https://doi.org/10.3390/su16010348У статті обґрунтовано необхідність систематизації європейського та українськогодосвіду цифровізації вантажних перевезень у контексті інституційної інтеграції рішеньeCMR, eFTI та митних/морських Single Window. Використано методи систематичногоогляду (PRISMA‑2020), порівняльного аналізу кейсів та інституційного аналізу управлінняданими; джерельна база—публікації 2020–2025 рр., індексовані у Scopus/Web of Science з DOI.Запропоновано тришарову модель комплементарності (eCMR—логістичні атрибутидоговору перевезення; eFTI—правовий/технічний канал подання регуляторної інформації;Single Window—організаційно‑правовий вузол мультиагентного обміну). Ідентифікованоконфігурації stewardship даних (державне, змішане, регулятивне лідерство) та їхній вплив наприйняття рішень; побудовано типологію інтеграції дорожніх цифрових платформ ізeCMR/eFTI; визначено ключові KPI портової та наземної логістики, пов’язані з якістю данихі подієвими моделями процесів (port call/road trip).Ключові слова: цифрова екосистема, логістична інфраструктура, eCMR; eFTI; SingleWindow; Port Community System; інтероперабельність даних; управління даними; логістичніKPI.
Перелік посилань1. Balić, K., Stočko, D., & Delchev, D. (2022). The port system in addressing sustainabilityissues—A systematic literature review. Journal of Marine Science and Engineering, 10(8), 1048.https://doi.org/10.3390/jmse100810482. Brunila, O.-P., Inkinen, T., Tapaninen, U., Hämäläinen, E., & Saarikoski, J. (2021).Hindrances in port digitalization? Identifying problems in the digitalization of Finnish ports.European Transport Research Review, 13, 24. https://doi.org/10.1186/s12544-021-00523-03. Caldeirinha, V., Felício, J., Dooms, M., & Carlan, V. (2022). Port Community Systems:Accelerating the transition of the maritime supply chain. Journal of Marine Science and Engineering,10(2), 152. https://doi.org/10.3390/jmse100201524. Dasaklis, T. K., Kopanaki, E., Chountalas, P. T., Rachaniotis, N. P., Voutsinas, T. G.,Giannakis, K., & Chondrokoukis, G. (2024). Exploring the implementation challenges of theElectronic Freight Transport Information (eFTI) Regulation: An empirical perspective from Greece.Logistics, 8(1), 30. https://doi.org/10.3390/logistics80100305. Fahim, P. B. M., Nguyen, H. O., & Fahim, M. (2024). Alignment of port policy to the contextof the Physical Internet. Maritime Policy & Management.https://doi.org/10.1080/03088839.2022.21475946. Felício, J. A., Batista, M., Dooms, M., & Caldeirinha, V. (2023). How do sustainable portpractices influence local communities’ perceptions of ports? Maritime Economics & Logistics.https://doi.org/10.1057/s41278-022-00237-77. Gavalas, D., Syriopoulos, T., & Roumpis, E. (2022). Digital adoption and efficiency in themaritime industry. Journal of Shipping and Trade, 7, 11. https://doi.org/10.1186/s41072-022-00111-y8. Heikkilä, M., Kandjani, A., & Suominen, A. (2022). Innovation in Smart Ports: Futuredirections of digitalization. Journal of Marine Science and Engineering, 10(12), 1925.https://doi.org/10.3390/jmse101219259. Heinbach, C., Beinke, J. H., Kammler, F., & Thomas, O. (2022). Data-driven forwarding: Atypology of digital platforms for road freight transport management. Electronic Markets, 32(2), 807–828. https://doi.org/10.1007/s12525-022-00540-410. Iida, J., & Watanabe, D. (2023). Focal points for the development and operation of portcommunity system—A case study of development history in Japan. Asian Transport Studies, 9,100116. https://doi.org/10.1016/j.eastsj.2023.10011611. Inkinen, T., Helminen, R., & Saarikoski, J. (2021). Technological trajectories and scenariosin seaport digitalization. Research in Transportation Business & Management, 41, 100633.https://doi.org/10.1016/j.rtbm.2021.10063312. Ivanov, D. (2020). Predicting the impacts of epidemic outbreaks on global supply chains: Asimulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case.Transportation Research Part E: Logistics and Transportation Review, 136, 101922.https://doi.org/10.1016/j.tre.2020.10192213. Jarumaneeroj, P., Mardani, A., & Kabir, G. (2024). An evolution of the Global ContainerShipping Network. Maritime Economics & Logistics. https://doi.org/10.1057/s41278-023-00273-x14. Jović, M., Tijan, E., Aksentijević, S., & Pucihar, A. (2024). Assessing the digitaltransformation in the maritime transport sector: A case study of Croatia. Journal of Marine Scienceand Engineering, 12(4), 634. https://doi.org/10.3390/jmse1204063415. Kervall, M., & Pålsson, H. (2022). Barriers to change in urban freight systems: Atechnological-institutional perspective. European Transport Research Review, 14, 29.https://doi.org/10.1186/s12544-022-00553-216. Lee, C., & Lee, S. (2024). Expanding IMO Compendium with NAVTEX messages forMaritime Single Window. Journal of Marine Science and Engineering, 12(12), 2328.https://doi.org/10.3390/jmse1212232817. Moros-Daza, A., Amaya-Mier, R., & Paternina-Arboleda, C. (2020). Port CommunitySystems: A structured literature review. Transportation Research Part A: Policy and Practice, 133,27–46. https://doi.org/10.1016/j.tra.2019.12.02118. Mthembu, S. E., & Chasomeris, M. G. (2022). A systems approach to developing a portcommunity system: A South African case. Journal of Shipping and Trade, 7, 26.https://doi.org/10.1186/s41072-022-00128-319. Orzechowski, S. C., van Hassel, E., & Sys, C. (2024). Regulatory scope of maritimeautonomous surface ships (MASS) in inland shipping: Implications for ports. Journal of Shipping andTrade, 9, 18. https://doi.org/10.1186/s41072-023-00160-x20. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ...& Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematicreviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n7121. Pan, S., Trentesaux, D., Ballot, E., Huang, G. Q., & Lam, D. (2021). Smart city for sustainableurban freight logistics: A review. International Journal of Production Research, 59(7), 2041–2063.https://doi.org/10.1080/00207543.2021.189397022. Peynirci, E. (2021). The rise of emerging technologies: A quantitative-based research on“maritime single window” in Turkey. Research in Transportation Business & Management, 46,100770. https://doi.org/10.1016/j.rtbm.2021.10077023. Raza, Z., Woxenius, J., Vural, C. A., & Lind, M. (2023). Digital transformation of maritimelogistics: Exploring trends in the liner shipping segment. Computers in Industry, 145, 103811.https://doi.org/10.1016/j.compind.2022.10381124. Rukanova, B., Henningsson, S., Henriksen, H. Z., & Tan, Y.-H. (2023). Public value creationthrough voluntary business-to-government information sharing: Mechanisms and enablingconditions. Government Information Quarterly, 40(1), 101786.https://doi.org/10.1016/j.giq.2022.10178625. Tijan, E., Jović, M., Panjako, A., & Žgaljić, D. (2021). The role of port authority in portgovernance and Port Community System implementation. Sustainability, 13(5), 2795.https://doi.org/10.3390/su1305279526. Tomicová, J., Poliak, M., & Zhuravleva, N. (2021). Impact of using e-CMR on neutralizationof consignment note. Transportation Research Procedia, 55, 1278–1285.https://doi.org/10.1016/j.trpro.2021.06.01227. van Donge, W., Bharosa, N., & Janssen, M. (2022). Data-driven government: Cross-casecomparison of data stewardship in data ecosystems. Government Information Quarterly, 39(2),101642. https://doi.org/10.1016/j.giq.2021.10164228. Wen, X., Chen, Q., Yin, Y.-Q., Lau, Y.-Y., & Dulebenets, M. A. (2024). Multi-objectiveoptimization for ship scheduling with port congestion and environmental considerations. Journal ofMarine Science and Engineering, 12(1), 114. https://doi.org/10.3390/jmse1201011429. Yap, W. Y., & Ho, J. (2023). Port strategy and performance: Empirical evidence from majorcontainer ports and implications for the role of data analytics. Maritime Policy & Management, 50(5),608–628. https://doi.org/10.1080/03088839.2021.201704030. Čerin, P., Perić Hadžić, A., & Žgaljić, D. (2023). Digitalisation of the port community throughthe development of advanced port communication systems (PCSs): A case study of the Port of Koper.Sustainability, 16(1), 348. https://doi.org/10.3390/su1601034
ВИЯВЛЕННЯ ГІБРИДНИХ КІБЕРАТАК У МЕРЕЖАХ ЕЛЕКТРОННИХ КОМУНІКАЦІЙ ЗАСОБАМИ ГЛИБОКОГО НАВЧАННЯ ТА ІНТЕГРОВАНИХ СИСТЕМ БЕЗПЕКИ
No full textThe article presents a comprehensive approach to modeling electronic communicationnetworks under hybrid cyber attacks using Zero Trust principles and modern data analysis methods. Theproposed integration of rapid state-change detection and statistical thresholds with multi-level learningbased on convolutional and recurrent neural networks, autoencoders, and visual telemetry fingerprints isdiscussed. It has been proven that combining sensor data, network traffic, event logs, and firmware artifactsinto a unified pipeline increases anomaly detection accuracy and reduces response latency in criticalscenarios. The study was conducted considering international standards and framework documents: theZero Trust Architecture by the U.S. National Institute of Standards and Technology (NIST SP 800-207),ISO/IEC 27001 requirements for information security management systems, NIST SP 800-218 (SSDF)secure software development recommendations, TLS 1.3 and SNMPv3 protocols, as well as the MITREATT&CK methodology for describing and analyzing adversary behavior. The article shows that combiningstatistical filtering methods, deep learning, and standardized security policies contributes to the creation ofnew tools for security operations and event management centers. From the perspective of the digitaleconomy, the results support the development of resilient communication infrastructures integrated intoecosystems of e-services, cloud platforms, and mobile applications. The proposed solutions form a practicalfoundation for improving intrusion detection and risk management systems, meet the current requirementsof global markets and cyber resilience strategies, and create conditions for long-term trust in digitaltechnologies.Keywords: hybrid cyber attacks, modeling of electronic communication networks, protocolvulnerabilities, digital economy, international standards, risk management, deep learning
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Запропоновано інтеграціюшвидкої перевірки змін стану й статистичних порогів із багаторівневим навчанням на основізгорткових і рекурентних нейронних мереж, автоенкодерів та візуальних відбитків телеметрії.Доведено, що поєднання сенсорних рядів, мережевого трафіку, журналів подій і артефактівпрошивок у єдиний конвеєр підвищує точність виявлення аномалій та знижує затримку реагуванняу критичних сценаріях. Дослідження виконано з урахуванням міжнародних стандартів і рамковихдокументів: архітектури довіри нульового рівня за Національним інститутом стандартів ітехнологій США (NIST SP 800-207), вимог ISO/IEC 27001 щодо систем управління інформаційноюбезпекою, рекомендацій із безпечної розробки програмного забезпечення NIST SP 800-218 (SSDF),протоколів TLS 1.3 і SNMPv3, а також методології MITRE ATT&CK для опису та аналізу поведінкизловмисників. У статті показано, що поєднання методів статистичної фільтрації, глибинногонавчання та стандартизованих політик безпеки сприяє формуванню нових інструментів для центрівоперацій безпеки та управління подіями. З позицій цифрової економіки результати підтримуютьрозвиток стійких комунікаційних інфраструктур, які інтегруються в екосистеми електроннихпослуг, хмарних сервісів і мобільних застосунків. Запропоновані рішення становлять практичнуоснову для удосконалення систем виявлення вторгнень і управління ризиками, відповідаютьсучасним вимогам глобальних ринків та стратегіям кіберстійкості, а також створюють умови длядовгострокового зростання довіри до цифрових технологій.Ключові слова: гібридні кібератаки, моделювання мереж електронних комунікацій,вразливості протоколів, цифрова економіка, міжнародні стандарти, управління ризиками, глибинненавчання
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КЛАСИФІКАЦІЯ АВТЕНТИЧНОГО КОНТЕНТУ У КОНТЕКСТІ ДОВІРИ СПОЖИВАЧІВ
Get PDFThe article is devoted to a topical issue in the digitalization of marketing—the systematization ofauthentic content varieties in relation to consumer trust. It examines the essence of content marketingas a shift from push to pull communication and highlights current trends in its development,emphasizing the growing role of authenticity in digital brand communication. The author provides anoriginal interpretation of the concepts of “authentic content” and “authentic content marketing,”focusing on their relevance in conditions of information overload and declining trust in traditionaladvertising messages.Theoretical models of content perception and consumer response are analyzed, including classicaland contemporary approaches that explain how communication stimuli influence cognitive, affective,and behavioral reactions. Particular attention is paid to the role of user-generated content as one ofthe most trusted forms of digital communication. The study examines the mechanisms through whichauthenticity enhances credibility, engagement, and long-term consumer–brand relationships.A classification (taxonomy) of authentic content based on the source of its creation is proposed,comprising ten varieties: UGC (User-Generated Content), EGC (Employee-Generated Content), IGC(Influencer-Generated Content), PGC (Peer-Generated Content), PCC (Customer-Created Content inresponse to a brand’s request), BGC (Brand-Generated Content), CGC (Community-GeneratedContent), CCC (Co-Created Content), TBC (Testimonial-Based Content), and SAC (SociallyAuthentic Content). In addition, an expert-based ranking of authentic content types according to thelevel of consumer trust is conducted, demonstrating that testimonial-based, user-generated, and peer-generated content achieve the highest trust levels.Examples of the identified content varieties are provided, and the importance of digital platformsfor the collection, management, and strategic use of authentic content is emphasized. The proposedclassification can support businesses in developing more effective and comprehensive contentstrategies, strengthening consumer trust, and increasing audience engagement in the digitalenvironment. Authentic content is proposed to be considered a long-term trend in the development ofdigital marketing. Based on an analysis of current trends, it is suggested that the role of authenticcontent in companies’ marketing strategies will continue to increase, particularly among youngeraudience segments.Keywords: content, content marketing, authentic content, user-generated content, sociallyauthentic content, consumer trust.
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Official website. https://www.looqme.io/ (accessed September 16, 2025).Стаття присвячена актуальному питанню в умовах цифровізації маркетингу —систематизації різновидів автентичного контенту у контексті довіри споживачів. Розглянутосутність контент-маркетингу як переходу від push- до pull-комунікації. Приділено увагурозвитку і особливостям контент-маркетингу в даний час. Обґрунтовано зростаючу рольавтентичного контенту та подано тлумачення понять «автентичний контент» і«автентичний контент-маркетинг». Проаналізовано теоретичні моделі сприйняття контенту.Розглянуто сутність і приклади користувацького контенту, якому довіряють споживачі.Запропоновано класифікацію (таксономію) автентичного контенту за джерелами створення,що включає 10 різновидів: UGC (користувацький контент); EGC (контент, створенийспівробітниками); IGC (контент, створений впливовими особами); PGC (контент, створенийколегами); PCC (контент, створений клієнтами, у відповідь на запит бренду); BGC (контент,створений брендом); CGC (контент, створений спільнотою); CCC (спільно створенийконтент); TBC (контент на основі відгуків); SAC (соціально-автентичний контент). Проведенеекспертно-аналітичне ранжування різновидів автентичного контенту за ступенем довіриспоживачів, за яким лідерами є TBC/UGC/ PGC. Запропонована класифікація може бутивикористана підприємствами для розробки ефективних контент-стратегій, підвищення довіриспоживачів та залучення аудиторії в цифровому середовищі. Наведено приклади різновидівконтенту та наголошено на важливості використання цифрових платформ для збору тауправління автентичним контентом. Запропоновано розглядати автентичний контент якдовгострокову тенденцію розвитку цифрового маркетингу. На основі аналізу трендівсформульовано прогностичне припущення, що роль автентичного контенту в маркетинговихстратегіях підприємств посилюватиметься, особливо у сегментах молодшої аудиторії. Наданірекомендації брендам бути відкритими, показувати реальні цінності, внутрішні процеси,помилки і проблеми.Ключові слова: контент, контент-маркетинг, автентичний контент, користувацькийконтент, соціально-автентичний контент, довіра споживачів.
Перелік посилань1.Pulizzi, J. (2014). Epic content marketing: How to tell a different story, break through the clutter, and winmore customers by marketing less. McGraw-Hill.2. Lebedenko, S. O., & Hnitetskyi, Y. V. (2022). User-generated content: A structural model of trustformation. Economic Bulletin of NTUU “Igor Sikorsky KPI”, (23), 90–101.https://doi.org/10.20535/2307-5651.23.2022.2646553. Sukontip, P. (2024). Influence of brand-generated content credibility on customer engagement.TEM Journal, 13(4), 2894–2902. https://doi.org/10.18421/TEM134-624. Ramos, E. C., et al. (2025). User-generated content and its impact on purchase intent on TikTok.Future Internet, 17(3), 105. https://doi.org/10.3390/fi170301055.Vasan, S., et al. (2025). Examining the impact of advertising, firm-generated content, and usergenerated content on customers’ propensity to buy online. Future Business Journal, 11, Article 12.https://doi.org/10.1186/s43093-025-004926. Vitale, J. (2007). Hypnotic writing: How to seduce and persuade customers with only your words. Wiley.7. Stelzner, M. (2011). Content marketing: New methods of attracting clients in the age of the Internet.Wiley.8. Rose, R. (2024). Content marketing strategy: Harness the power of your brand’s voice. McGraw-Hill.9. Halvorson, K., & Rach, M. (2012). Content strategy for the web (2nd ed.). New Riders.10. Lieb, R. (2012). Content marketing: Think like a publisher — How to use content to market online andin social media. Que Publishing.11. Brenner, M. (2019). Mean people suck: How empathy leads to bigger profits and a better life. 11.HarperCollins Leadership.12. Kaplunov, D. (2022). Koroli sotsmerezh [Kings of social media]. Nash format.13. Petrova, I. L., & Dyachuk, I. V. (2023). Kontent-marketing: Navchalno-metodychnyi posibnyk [Contentmarketing: Educational-methodical manual]. VNZ "Universytet ekonomiky ta prava ''KROK''.https://duikt.edu.ua/ua/lib/1/category/2274/view/259 (accessed September 15, 2025).14. Vynohradova, O. V., Ihnatenko, O. V., Sovershenna, I. O., & Snitko, A. S. (2024). Kontent-marketyng:Navchalnyi posibnyk [Content marketing: Textbook]. DUIKT.https://duikt.edu.ua/uploads/l_2362_79023663.pdf (accessed September 15, 2025).15. Zintso, Y. V., & Fedoruk, M. S. (2025). Main types and formats of content for SMM. Ekonomika tasuspilstvo, (71). https://doi.org/10.32782/2524-0072/2025-71-86 (accessed September 18, 2025).16. Holt, D. (2002). Why do brands cause trouble? Journal of Consumer Research, 29(1), 70–90.https://doi.org/10.1086/33991917. Grayson, K., & Martinec, R. (2004). Consumer perceptions of iconicity and indexicality. Journal ofConsumer Research, 31(2), 296–312. https://doi.org/10.1086/42210918. Molleda, J. (2010). Authenticity and the construct’s dimensions in public relations. Journal ofCommunication Management, 14(3), 223–236. https://doi.org/10.1108/1363254101106450819. Bruhn, M., Schoenmueller, V., & Schäfer, D. (2012). Are social media replacing traditional media?Marketing Review St. Gallen, 29(1), 24–33. https://doi.org/10.1365/s11621-012-0009-420. Morhart, F., Malär, L., Guèvremont, A., Girardin, F., & Grohmann, B. (2015). Brand authenticity.Journal of Consumer Psychology, 25(2), 200–218. https://doi.org/10.1016/j.jcps.2014.11.00121. eMarketer. (2025). Authentic content: Key trends in 2025. https://www.insiderintelligence.com(accessed September 11, 2025).22. Statista. (2025). Content marketing 2025. https://www.statista.com/topics/1650/content-marketing(accessed September 10, 2025).23. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. MIT Press.24. Cialdini, R. B. (2009). Influence: The psychology of persuasion. Harper Business.25. Brodie, R. J., Hollebeek, L. D., Jurić, B., & Ilić, A. (2011). 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Korystuvatskyi content (UGC) – koly reklamnі povidomlennya dlya vasstvoryuyut tysiachі marketolohiv [User-generated content (UGC) – when thousands of marketers createads for you]. https://sendpulse.ua/blog/what-is-user-generated-content (accessed September 12, 2025).30. MMR.ua. (2022). Avtentychnist, vidsutnist brendynhu ta inshe: trendy, yaki sformuvaly kontentmarketyng u 2022 rotsi [Authenticity, lack of branding, and other trends that shaped content marketing in2022]. https://mmr.ua/show/avtentychnist-vidsutnist-brendyngu-ta-inshe-trendy-yaki-sformuvaly-kontentmarketyng-u-2022-roczi31. Kantar Ukraine. (2025). Kantar Ukraine official site. https://www.kantar.com/ua (accessed September14, 2025).32. Dmark.pro. (2025). EGC: Novyi trend u marketynhu 2025 roku [EGC: New marketing trend 2025].https://dmark.pro/uk/blog-uk/egc-novij-trend-u-marketingu-2025-roku (accessed September 14, 2025).33. MMR.ua. (2025). 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ІНФОРМАЦІЙНІ ТЕХНОЛОГІЇ ЯК ІНСТРУМЕНТ РЕАЛІЗАЦІЇ ЕКОНОМІКО-МАТЕМАТИЧНИХ МОДЕЛЕЙ
Get PDFThe article examines therole of modern information technologies as an effective tool for the implementation, optimization,and adaptation of economic-mathematical models in contemporary economic systems. Particularattention is paid to the transformation of analytical and decision-making processes under theinfluence of digital technologies such as cloud computing, big data analytics, artificial intelligence,and advanced simulation tools. The study emphasizes that economic-mathematical modelingincreasingly relies on high-performance computing environments, integrated information systems,and digital platforms that ensure operational accuracy, scalability, and rapid processing of largedatasets.The research reveals that the integration of information technologies significantly expands thefunctional capabilities of economic-mathematical models by enhancing the precision of forecasting,enabling real-time monitoring of economic processes, and supporting adaptive management underuncertainty. The article also outlines methodological approaches to constructing and validatingmodels using software packages, specialized analytical platforms, and algorithmic modelingenvironments. The advantages of digital tools for solving optimization, simulation, econometric, andmulti-criteria decision-making problems are systematically analyzed.In addition, the study identifies key challenges associated with the technological implementation ofeconomic-mathematical models, including issues of data quality, system interoperability,cybersecurity risks, and the need for highly qualified personnel. A comparative analysis of traditionaland digitally enhanced modeling approaches demonstrates that the use of IT tools substantiallyimproves computational efficiency, reduces the time needed for analytical procedures, and facilitatesthe transition from descriptive to predictive and prescriptive analytics.The findings confirm that information technologies not only serve as auxiliary instruments but act asstrategic enablers of innovative modeling solutions within economic research and practicalmanagement. The paper substantiates that the synergistic interaction between economicmathematical modeling and digital technologies forms a methodological foundation for evidencebased decision-making, contributing to the stability, efficiency, and competitiveness of enterprises inconditions of market volatility and digital transformation.Keywords: information technologies, economic and mathematical models, digital tools, optimization,forecasting, modelling.
References1. Cabinet of Ministers of Ukraine. (2022, July). National Recovery Plan of Ukraine [Draft presentedat the Lugano Conference]. https://uploadsssl.webflow.com/621f88db25fbf24758792dd8/62c166751fcf41105380a733_NRC%20Ukraine%27s%20Recovery%20Plan%20blueprint_ENG.pdf#:~:text=Integration%20of%20Ukrainian%20economy%20into,of%20wealth%2C%20and%20overall%20wellbeing2. Center for European Policy Analysis (CEPA) & Kyiv School of Economics (KSE). (2024, April).Resilience, Reconstruction, Recovery: The Path Ahead for Ukraine. https://cepa.org/comprehensivereports/resilience-reconstruction-recovery-the-path-ahead-for-ukraine/3. Ivanchenko, V. (2022). Economic and Mathematical Methods in Enterprise Management. Kyiv:Naukа. 215 p.4. Klein, J., & Peters, D. (2021). Digital Modelling Systems and Decision Optimization. Journal ofEconomic Modelling, 45, 80–95.5. European Investment Bank (EIB). (2023, June 21). EIB Group and European Commission launchnew 40 million euro programme to support small and medium businesses affected by Rusia`s war inUkraine. https://www.eib.org/en/press/all/2023-233-eib-group-and-european-commission-launchnew-eur40-million-programme-to-support-small-and-medium-businesses-affected-by-russia-s-warin-ukraine#:~:text=EIB%20Group%20and%20European%20Commission,21%20June%2020236. Zhang, L., & Liu, Y. (2023). Machine Learning in Economic Forecasting: Methods andApplications. Economic Review, 12, 450–470.7. Belorus, O., & Halchynskyi, O. (2021). Digital Transformation of the Economy: Concepts andTools. Kyiv: KNEU. 190 p.8. Kramarenko, H. (2022). Modern IT Solutions in Business Process Management. Lviv: LNU. 142p.9. House of Commons Library (UK). (2024, July 15). Post-conflict reconstruction assistance toUkraine (Briefing Paper No. 9728). https://researchbriefings.files.parliament.uk/documents/CBP9728/CBP9728.pdf#:~:text=While%20plans%20may%20vary%2C%20all,salaries%20of%20public%20sector%20workers10. Ministry of Economy of Ukraine. (n.d.). Ukraine Facility: Economic support programme.https://www.ukrainefacility.me.gov.ua/11. Organization for Economic Cooperation and Development (OECD). (2024, May 22). EnhancingResilience by Boosting Digital Business Transformation in Ukraine.https://www.oecd.org/en/publications/2024/05/enhancing-resilience-by-boosting-digital-businesstransformation-inukraine_c2e06e50.html#:~:text=disruption%20of%20supply%20chains%2C%20difficulties,relocation%20to%20more%20secure%20regions12. United Nations Development Programme (UNDP) Ukraine. (2024, February 20). Assessmentof the Impact of the War on MSMEs in Ukraine.https://www.undp.org/ukraine/publications/assessment-wars-impact-micro-small-and-mediumenterprisesukraine#:~:text=Micro%2C%20small%2C%20and%20medium,in%20the%20face%20of%20adversityУ статті досліджено роль інформаційних технологій у реалізації економікоматематичних моделей для підтримки управлінських рішень в умовах цифровоїтрансформації економіки. Визначено ключові інструменти, що забезпечують ефективнупобудову, верифікацію та впровадження моделей різного рівня складності. Проаналізованосучасні тенденції застосування інформаційних технологій у сфері економічного моделювання,включаючи машинне навчання, хмарні обчислення, візуальну аналітику та системиоптимізації. Обґрунтовано переваги інтеграції ІТ-платформ із математичними методами для розв’язання задач прогнозування, оптимізації логістичних та фінансових процесів,управління ризиками та оцінювання ефективності діяльності підприємств. Запропонованокласифікацію цифрових інструментів моделювання та визначено їх застосовність у бізнеспрактиці. Результати дослідження засвідчують, що використання сучасних інформаційнихтехнологій є критичним чинником підвищення точності, швидкодії та адаптивностіекономіко-математичних моделей.Ключові слова: інформаційні технології, економіко-математичні моделі, цифровіінструменти, оптимізація, прогнозування, моделювання.
Перелік посилань1. Cabinet of Ministers of Ukraine. (2022, July). National Recovery Plan of Ukraine [Draft presentedat the Lugano Conference]. https://uploadsssl.webflow.com/621f88db25fbf24758792dd8/62c166751fcf41105380a733_NRC%20Ukraine%27s%20Recovery%20Plan%20blueprint_ENG.pdf#:~:text=Integration%20of%20Ukrainian%20economy%20into,of%20wealth%2C%20and%20overall%20wellbeing2. Center for European Policy Analysis (CEPA) & Kyiv School of Economics (KSE). (2024, April).Resilience, Reconstruction, Recovery: The Path Ahead for Ukraine. https://cepa.org/comprehensivereports/resilience-reconstruction-recovery-the-path-ahead-for-ukraine/3. Ivanchenko, V. (2022). Economic and Mathematical Methods in Enterprise Management. Kyiv:Naukа. 215 p.4. Klein, J., & Peters, D. (2021). Digital Modelling Systems and Decision Optimization. Journal ofEconomic Modelling, 45, 80–95.5. European Investment Bank (EIB). (2023, June 21). EIB Group and European Commission launchnew 40 million euro programme to support small and medium businesses affected by Rusia`s war inUkraine. https://www.eib.org/en/press/all/2023-233-eib-group-and-european-commission-launchnew-eur40-million-programme-to-support-small-and-medium-businesses-affected-by-russia-s-warin-ukraine#:~:text=EIB%20Group%20and%20European%20Commission,21%20June%2020236. Zhang, L., & Liu, Y. (2023). Machine Learning in Economic Forecasting: Methods andApplications. Economic Review, 12, 450–470.7. Belorus, O., & Halchynskyi, O. (2021). Digital Transformation of the Economy: Concepts andTools. Kyiv: KNEU. 190 p.8. Kramarenko, H. (2022). Modern IT Solutions in Business Process Management. Lviv: LNU. 142p.9. House of Commons Library (UK). (2024, July 15). Post-conflict reconstruction assistance toUkraine (Briefing Paper No. 9728). https://researchbriefings.files.parliament.uk/documents/CBP9728/CBP9728.pdf#:~:text=While%20plans%20may%20vary%2C%20all,salaries%20of%20public%20sector%20workers10. Ministry of Economy of Ukraine. (n.d.). Ukraine Facility: Economic support programme.https://www.ukrainefacility.me.gov.ua/11. Organization for Economic Cooperation and Development (OECD). (2024, May 22). EnhancingResilience by Boosting Digital Business Transformation in Ukraine.https://www.oecd.org/en/publications/2024/05/enhancing-resilience-by-boosting-digital-businesstransformation-inukraine_c2e06e50.html#:~:text=disruption%20of%20supply%20chains%2C%20difficulties,relocation%20to%20more%20secure%20regions12. United Nations Development Programme (UNDP) Ukraine. (2024, February 20). Assessmentof the Impact of the War on MSMEs in Ukraine.https://www.undp.org/ukraine/publications/assessment-wars-impact-micro-small-and-mediumenterprisesukraine#:~:text=Micro%2C%20small%2C%20and%20medium,in%20the%20face%20of%20adversit
ПЛАНУВАННЯ ЧАСТОТНИХ РЕСУРСІВ І ВІДСТАНЕЙ У ВИСОКОЩІЛЬНИХ МЕРЕЖАХ WI-FI
No full textThe development of nanonetworks is drivenby their wide range of applications: nano-devices interconnected into a single system form a “transportartery” for data transmission, yet miniature sensors face strict constraints on energy consumption,computational capability, and memory capacity. This necessitates energy-efficient routing approaches inelectromagnetic nanonetworks. The paper provides a consolidated review of contemporary methods fordelivering packets to their destination based on systematic collection, analysis, and synthesis of researchresults from recent years. A comparative study of key forwarding schemes is presented with an assessmentof their advantages and limitations, and the most promising solutions are outlined. The findings enable awell-grounded selection of a forwarding method aligned with the requirements of a specific nanonetwork.Keywords: Internet of Nano-Things, nanonetwork, data transmission, routing, forwarding scheme
References1. Yu H., Ng B., Seah W. K. G. TTL-Based Efficient Forwarding for Nanonetworks WithMultiple Coordinated IoT Gateways. IEEE Internet of Things Journal. 2018. Vol. 5, no. 3. P. 1807–1815. URL: https://doi.org/10.1109/jiot.2018.2812868.2. Survey on Terahertz Nanocommunication and Networking: A Top-Down Perspective / F.Lemic et al. IEEE Journal on Selected Areas in Communications. 2021. Vol. 39, no. 6. P. 1506–1543.URL: https://doi.org/10.1109/jsac.2021.3071837.3. H. Yu, B. Ng, W. K. G. Seah and Y. Qu. TTL-based efficient forwarding for the backhaul tierin nanonetworks. 2017 14th IEEE Annual Consumer Communications & Networking Conference(CCNC), Las Vegas, NV, USA, 2017, pp. 554-559. URL:https://doi.org/10.1109/CCNC.2017.7983167.4. Cruz Alvarado M. A., Bazán P. A. Understanding the Internet of Nano Things: overview,trends, and challenges. e-Ciencias de la Información. 2018. URL:https://doi.org/10.15517/eci.v1i1.33807.5. Yu H., Ng B., Seah W.K.G. Forwarding Schemes for EM-based Wireless NanosensorNetworks in the Terahertz Band. Proceedings of the 2nd ACM International Conference on NanoscaleComputing and Communication (NANOCOM ’15). New York: ACM, 2015. С. 1–6. URL:https://doi.org/10.1145/2800795.2800799.6. Xu J., Zhang Y., Jiang J., Kan J. An Energy Balance Clustering Routing Protocol for IntraBody Wireless Nanosensor Networks. Sensors. 2019. Vol. 19, no. 22. P. 4875. URL:https://doi.org/10.3390/s192248757. Yao X.-W., Wu Y.-C.-G., Huang W. Routing techniques in wireless nanonetworks: A survey.Nano Communication Networks. 2019. Vol. 21. P. 100250. URL:https://doi.org/10.1016/j.nancom.2019.100250.8. Bouchedjera I. A., Louail L., Aliouat Z. Addressing and flood-based communications for thesoftware-defined metamaterial paradigm. Nano Communication Networks. 2020. P. 100336. URL:https://doi.org/10.1016/j.nancom.2020.100336.9. Iqbal I., Nazir M., Sabah A. Design of Energy-Efficient Protocol Stack forNanocommunication Using Greedy Algorithms. Journal of Computer Networks andCommunications. 2022. Vol. 2022. P. 1–22. URL: https://doi.org/10.1155/2022/3150865.Розвиток наномереж зумовленийшироким спектром їхніх застосувань: нанопристрої, з’єднані в єдину систему, утворюють«транспортну артерію» передавання даних, однак мініатюрні сенсори мають жорсткі обмеження заенергоспоживанням, обчислювальною спроможністю та обсягами пам’яті. Це висуває вимогу доенергоефективних підходів маршрутизації в електромагнітних наномережах. У роботі поданоузагальнювальний огляд сучасних методів доставлення пакетів до адресата на основісистематичного збирання, аналізу та синтезу результатів досліджень останніх років. Проведенопорівняльне вивчення ключових схем переадресації з оцінкою їхніх переваг і обмежень та окресленонайперспективніші рішення. Отримані висновки дають змогу обґрунтовано обирати методпереадресації відповідно до вимог конкретної наномережі.Ключові слова: Інтернет наноречей, наномережа, передача даних, маршрутизація, схемапереадресації
Список використаної літератури1. Yu H., Ng B., Seah W. K. G. TTL-Based Efficient Forwarding for Nanonetworks WithMultiple Coordinated IoT Gateways. IEEE Internet of Things Journal. 2018. Vol. 5, no. 3. P. 1807–1815. URL: https://doi.org/10.1109/jiot.2018.2812868.2. Survey on Terahertz Nanocommunication and Networking: A Top-Down Perspective / F.Lemic et al. IEEE Journal on Selected Areas in Communications. 2021. Vol. 39, no. 6. P. 1506–1543.URL: https://doi.org/10.1109/jsac.2021.3071837.3. H. Yu, B. Ng, W. K. G. Seah and Y. Qu. TTL-based efficient forwarding for the backhaul tierin nanonetworks. 2017 14th IEEE Annual Consumer Communications & Networking Conference(CCNC), Las Vegas, NV, USA, 2017, pp. 554-559. URL:https://doi.org/10.1109/CCNC.2017.7983167.4. Cruz Alvarado M. A., Bazán P. A. Understanding the Internet of Nano Things: overview,trends, and challenges. e-Ciencias de la Información. 2018. URL:https://doi.org/10.15517/eci.v1i1.33807.5. Yu H., Ng B., Seah W.K.G. Forwarding Schemes for EM-based Wireless NanosensorNetworks in the Terahertz Band. Proceedings of the 2nd ACM International Conference on NanoscaleComputing and Communication (NANOCOM ’15). New York: ACM, 2015. С. 1–6. URL:https://doi.org/10.1145/2800795.2800799.6. Xu J., Zhang Y., Jiang J., Kan J. An Energy Balance Clustering Routing Protocol for IntraBody Wireless Nanosensor Networks. Sensors. 2019. Vol. 19, no. 22. P. 4875. URL:https://doi.org/10.3390/s192248757. Yao X.-W., Wu Y.-C.-G., Huang W. Routing techniques in wireless nanonetworks: A survey.Nano Communication Networks. 2019. Vol. 21. P. 100250. URL:https://doi.org/10.1016/j.nancom.2019.100250.8. Bouchedjera I. A., Louail L., Aliouat Z. Addressing and flood-based communications for thesoftware-defined metamaterial paradigm. Nano Communication Networks. 2020. P. 100336. URL:https://doi.org/10.1016/j.nancom.2020.100336.9. Iqbal I., Nazir M., Sabah A. Design of Energy-Efficient Protocol Stack forNanocommunication Using Greedy Algorithms. Journal of Computer Networks andCommunications. 2022. Vol. 2022. P. 1–22. URL: https://doi.org/10.1155/2022/3150865
МЕТОД ІТЕРАЦІЙНОГО СТВОРЕННЯ ОЗНАК НА ОСНОВІ ШТУЧНОГО ІНТЕЛЕКТУ ДЛЯ ПРОГНОЗУВАННЯ ВІДТОКУ
No full textThe article proposes an iterative feature generation method using largelanguage models (LLMs) to improve the efficiency of customer churn prediction in SaaS platforms. Theproposed approach combines an LLM generator and an LLM critic in a closed feedback loop, enablingmulti-step refinement and selection of relevant features based on model performance metrics. Experimentalresults on streaming platform data demonstrated an increase in the F1-score compared to the baselineapproach. The obtained experiment results confirm the effectiveness of the iterative use of LLMs forautomating feature creation and enhancing the accuracy of churn prediction models.Keywords: churn prediction, large language models, feature generation, machine learning, artificialintelligence
References1. Suguna R., Suriya P., Pai H. A. et al. Mitigating class imbalance in churn prediction withensemble methods and SMOTE. Scientific Reports. 2025. Vol. 15. P. 16256. URL:https://doi.org/10.1038/s41598-025-01031-0.2. Noviandy T. R., Idroes G. M., Hardi I. et al. A model-agnostic interpretability approach topredicting customer churn in the telecommunications industry. Infolitika Journal of Data Science.2024. Vol. 2, no. 1. P. 34–44. URL: https://doi.org/10.60084/ijds.v2i1.199.3. ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn FeatureEngineering. Algorithms. 2025. Vol. 18, no. 4. P. 238. URL: https://doi.org/10.3390/a18040238.4. Large Language Models Can Automatically Engineer Features for Few-Shot TabularLearning. arXiv preprint. 2024. URL: https://arxiv.org/abs/2404.09491.5. Imani M., Joudaki M., Beikmohammadi A., Arabnia H. R. Customer churn prediction: asystematic review of recent advances, trends, and challenges in machine learning and deep learning.Machine Learning and Knowledge Extraction. 2025. Vol. 7, no. 3. P. 105. URL:https://doi.org/10.3390/make7030105.6. Hegselmann S., Buendia A., Lang H., Agrawal M., Jiang X., Sontag D. TabLLM: Few-shotclassification of tabular data with large language models. arXiv preprint. 2022. URL:https://doi.org/10.48550/arXiv.2210.10723.7. Gong N., Wang X., Ying W., Bai H., Dong S., Chen H., Fu Y. Unsupervised featuretransformation via in-context generation, generator-critic LLM agents, and duet-play teaming. arXivpreprint. 2025. URL: https://arxiv.org/abs/2504.21304.8. Zhao H., Chen H., Yang F., Liu N., Deng H., Cai H., Wang S., Yin D., Du M. Explainabilityfor large language models: a survey. ACM Transactions on Intelligent Systems and Technology. 2024.Vol. 15, no. 2. URL: https://doi.org/10.1145/3639372.9. Zhang X., Zhang J., Rekabdar B., Zhou Y., Wang P., Liu K. Dynamic and adaptive featuregeneration with LLM. arXiv preprint. 2024. URL: https://arxiv.org/abs/2406.03505.10. Kaggle dataset: Predictive Analytics for Customer Churn Dataset. URL:https://www.kaggle.com/datasets/safrin03/predictive-analytics-for-customer-churn-dataset.У статті запропоновано метод ітераційногостворення ознак із використанням великих мовних моделей (LLM) для підвищення ефективностіпрогнозування відтоку клієнтів у SaaS-платформах. Запропонований підхід поєднує LLM-генераторі LLM-критик у замкненому контурі зворотного зв’язку, що забезпечує багатокроковевдосконалення та відбір релевантних ознак на основі показників якості моделі. Експериментальнірезультати на даних стрімінгової платформи показали підвищення F1-міри у порівнянні з базовимпідходом. Експериментальні результати підтверджують ефективність ітераційного використанняLLM для автоматизації створення ознак і підвищення точності моделей прогнозування відтокукористувачів.Ключові слова: прогнозування відтоку, великі мовні моделі, створення ознак, машинненавчання, штучний інтелект
Список використаної літератури1. Suguna R., Suriya P., Pai H. A. et al. Mitigating class imbalance in churn prediction withensemble methods and SMOTE. Scientific Reports. 2025. Vol. 15. P. 16256. URL:https://doi.org/10.1038/s41598-025-01031-0.2. Noviandy T. R., Idroes G. M., Hardi I. et al. A model-agnostic interpretability approach topredicting customer churn in the telecommunications industry. Infolitika Journal of Data Science.2024. Vol. 2, no. 1. P. 34–44. URL: https://doi.org/10.60084/ijds.v2i1.199.3. ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn FeatureEngineering. Algorithms. 2025. Vol. 18, no. 4. P. 238. URL: https://doi.org/10.3390/a18040238.4. Large Language Models Can Automatically Engineer Features for Few-Shot TabularLearning. arXiv preprint. 2024. URL: https://arxiv.org/abs/2404.09491.5. Imani M., Joudaki M., Beikmohammadi A., Arabnia H. R. Customer churn prediction: asystematic review of recent advances, trends, and challenges in machine learning and deep learning.Machine Learning and Knowledge Extraction. 2025. Vol. 7, no. 3. P. 105. URL:https://doi.org/10.3390/make7030105.6. Hegselmann S., Buendia A., Lang H., Agrawal M., Jiang X., Sontag D. TabLLM: Few-shotclassification of tabular data with large language models. arXiv preprint. 2022. URL:https://doi.org/10.48550/arXiv.2210.10723.7. Gong N., Wang X., Ying W., Bai H., Dong S., Chen H., Fu Y. Unsupervised featuretransformation via in-context generation, generator-critic LLM agents, and duet-play teaming. arXivpreprint. 2025. URL: https://arxiv.org/abs/2504.21304.8. Zhao H., Chen H., Yang F., Liu N., Deng H., Cai H., Wang S., Yin D., Du M. Explainabilityfor large language models: a survey. ACM Transactions on Intelligent Systems and Technology. 2024.Vol. 15, no. 2. URL: https://doi.org/10.1145/3639372.9. Zhang X., Zhang J., Rekabdar B., Zhou Y., Wang P., Liu K. Dynamic and adaptive featuregeneration with LLM. arXiv preprint. 2024. URL: https://arxiv.org/abs/2406.03505.10. Kaggle dataset: Predictive Analytics for Customer Churn Dataset. URL:https://www.kaggle.com/datasets/safrin03/predictive-analytics-for-customer-churn-dataset