Heuristic Approaches to Studying the Dynamics of Economic Development for Resource Allocation in Crisis Management

Aleksy Kwilinski; Mykola Rohoza; Tetiana Hudz; Bozena Kaminska

doi:10.23762/FSO_VOL13_NO4_6

Published : 2025-12-30

Vol. 13 No. 4 (2025)

Heuristic Approaches to Studying the Dynamics of Economic Development for Resource Allocation in Crisis Management

Aleksy Kwilinski

https://orcid.org/0000-0001-6318-4001

Mykola Rohoza

https://orcid.org/0000-0002-5654-7385

Tetiana Hudz

https://orcid.org/0000-0002-2310-5425

Bozena Kaminska

https://orcid.org/0000-0002-0654-870X

DOI: https://doi.org/10.23762/FSO_VOL13_NO4_6

Abstract

Economic systems operating under high uncertainty, particularly during wartime disruptions, require robust analytical and forecasting instruments to support objective and timely resource allocation decisions within crisis management. This study aims to improve the methodological approaches and analytical toolkit for forecasting and analysing the dynamics of economic development in order to substantiate resource allocation decisions at the level of an economic entity. The research is based on statistical data describing the performance of the analysed object over the pre-war and wartime period of 2006–2024. The methodological framework integrates principles of systems analysis, multivariate statistical techniques for data collection, structuring and processing, expert judgement, and heuristic reasoning to establish the system–logical relationships among the parameters used to construct the initial analytical database. Expert assessments and a set of coefficients (indicators) were developed to operationalise the taxonomic method, enabling the calculation of an integral criterion of economic development. Furthermore, a correlation–regression forecasting model was developed to quantify the strength of relationships among factors and to rank their significance in explaining variations in the economic development index. The findings demonstrate that the proposed modelling framework provides a consistent analytical basis for forecasting economic development dynamics as a function of internal changes in liquidity, solvency, profitability and financial stability indicators, thereby increasing the objectivity and resilience of managerial decisions on resource allocation. The study contributes to the literature by advancing heuristic and data-driven approaches to modelling economic development dynamics under crisis conditions, with particular emphasis on the integration of taxonomic analysis, expert-based indicator construction, and econometric forecasting. The proposed tools may be applied in the practice of crisis management to enhance decision-making in resource distribution and may serve as a foundation for further research incorporating stochastic components and scenario-based analysis.

Keywords:

forecasting, analysis, economic development, crisis, taxonomy, model, resources.

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Kwilinski, A., Rohoza, M., Hudz, T., & Kaminska, B. (2025). Heuristic Approaches to Studying the Dynamics of Economic Development for Resource Allocation in Crisis Management. Forum Scientiae Oeconomia, 13(4), 111–145. https://doi.org/10.23762/FSO_VOL13_NO4_6

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Aleksy Kwilinski

a.kwilinski@london-asb.co.uk
https://orcid.org/0000-0001-6318-4001

Affiliation:

United Nations Economic Commission for Europe, Geneva, Switzerland; The London Academy of Science and Business, London, United Kingdom; Institute for Sustainable Development and International Relations, WSB University, Dabrowa Gornicza,

Mykola Rohoza

rogoza.ne@gmail.com
https://orcid.org/0000-0002-5654-7385

Affiliation:

Poltava University of Economics and Trade, Poltava, Ukraine; Institute of Industrial Economics of the National Academy of Sciences of Ukraine, Kyiv,

Tetiana Hudz

gtp9@ukr.net
https://orcid.org/0000-0002-2310-5425

Affiliation:

Poltava University of Economics and Trade, Poltava,

Bozena Kaminska

bozenaka@gmail.com
https://orcid.org/0000-0002-0654-870X

Affiliation:

The Senate of the Republic of Poland, Warsaw, Poland; Bialystok University of Technology, Bialystok, Poland; The London Academy of Science and Business, London,