Analysis of the Behaviour of Industrial Enterprises in a Competitive Environment Based on Simulation Modelling

Abstract

The application of simulation modelling for analysing the behaviour of industrial enterprises in a competitive environment is studied. It is established that the effectiveness of management decisions is largely determined by the level of adaptation of enterprise strategies to changes in macroeconomic factors, dynamics of investment activity and competitive pressure. The purpose of the study is to assess the possibilities of simulation modelling to optimise strategic decisions and improve the efficiency of enterprise management in a competitive environment.

The research methods include structural and dynamic analysis of the financial indicators of industrial enterprises of Ukraine for 2019-2023, simulation agent-based modelling, scenario analysis and forecasting methods. Calculations were carried out for three development scenarios: optimistic, basic and crisis, which allowed to identify the main trends in the financial performance of enterprises depending on the level of investment and the state of the market environment.

It has been found that the use of simulation modelling allows predicting the impact of external factors on the financial sustainability of enterprises and assessing the effectiveness of management strategies. It has been proved that macroeconomic instability and limited availability of investment resources are key factors affecting the competitiveness of enterprises. It has been established that the dependence of models on the accuracy of input data and the complexity of forecasting sudden changes in the market environment require an improved methodological approach.

The practical value lies in the possibility of using simulation modelling to analyse the behaviour of industrial enterprises in a competitive environment and develop management strategies aimed at increasing their adaptability and sustainability. The article proposes to improve approaches to forecasting the behaviour of industrial enterprises in a competitive environment by integrating adaptive algorithms, automated systems for analysing economic indicators and stochastic risk assessment methods.

Prospects for further research include expanding the modelling to take into account additional macroeconomic factors, analysing the dynamics of industrial enterprises' behaviour in a competitive environment, and using machine learning algorithms to improve the accuracy of forecasts.