Development of a decision support model for multi-stage investment decisions in production systems under risk

Authors

DOI:

https://doi.org/10.15587/2706-5448.2026.356886

Keywords:

adaptive decision-making, efficiency reserve, Bayesian decision analysis, expected utility

Abstract

The object of research is the process of making investment decisions in production systems under conditions of risk and uncertainty.

In modern enterprise conditions, making investment decisions requires choosing between several options for production development. Their effectiveness depends on possible states of the external environment. A feature of these processes is that investment decisions can have several stages, and their effectiveness depends on the conditions of implementation.

The work focused on developing a decision support model that takes into account the step-by-step implementation of investment projects and evaluates alternatives considering possible environmental scenarios. The analysis showed that traditional approaches are mostly based on one-stage decision models, which limits the ability to consider changes in project implementation conditions.

The model for supporting investment decision-making developed in the research combines single-stage and multi-stage approaches to evaluating the effectiveness of alternatives under conditions of risk. A feature of the obtained results is that they allow determining the expected result of applying multi-stage alternatives and identifying rational investment strategies. An approach to evaluating the efficiency reserve of investment projects in production was also proposed.

During the experimental verification, it was shown that the developed model allows taking into account the staged implementation of alternatives and the information that follows from this. Thanks to this, it provides the possibility of adjusting managerial decisions depending on the actual state of the environment at different stages of the implementation of the adopted decisions.

The developed model can be used in the process of substantiating investment decisions in production systems under conditions of risk.

Author Biographies

Oksana Mulesa, University of Prešov

Doctor of Technical Sciences, Professor

Department of Physics, Mathematics and Technologies

Department of Software Systems of Uzhhorod National University

Olga Kachmar

PhD, Associated Professor, Independent Researcher

Svitlana Baloha, Uzhhorod National University

PhD, Associate Professor

Department of Computer Systems and Networks

Hanna Tiutiunnykova, Uzhhorod National University

Senior Lecturer

Department of Computer Systems and Networks

Dmytro Shevchuk, Uzhhorod National University

PhD Student

Department of Computer Systems and Networks

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Development of a decision support model for multi-stage investment decisions in production systems under risk

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Published

2026-04-30

How to Cite

Mulesa, O., Kachmar, O., Baloha, S., Tiutiunnykova, H., & Shevchuk, D. (2026). Development of a decision support model for multi-stage investment decisions in production systems under risk. Technology Audit and Production Reserves, 2(2(88), 92–97. https://doi.org/10.15587/2706-5448.2026.356886

Issue

Vol. 2 No. 2(88) (2026): Information and control systems

Section

Systems and Control Processes

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Copyright (c) 2026 Oksana Mulesa, Olga Kachmar, Svitlana Baloha, Hanna Tiutiunnykova, Dmytro Shevchuk

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