Assessment of risks associated with the development and scaling of information systems in commercial enterprises

Abstract

This study presents an enhanced methodology for assessing the risks associated with the development and scaling of information systems (IS) in retail enterprises. The method integrates a multifactorial analytical framework with advanced digital tools, including principal component analysis (PCA), scenario modeling, and machine learning techniques such as neural networks. It also incorporates dynamic monitoring and time-series analysis to account for the evolving nature of risk factors over time. The approach enables the identification of key economic, technological, organizational, social, market, and regulatory influences on IS risk levels. A practical evaluation was conducted using data from five Ukrainian retail companies—ATB, Silpo, Nova Linia, Epicentr, and Fora—over the period 2020–2024. Results demonstrate that the improved methodology provides more accurate forecasts, supports adaptive decision-making, and contributes to the formation of resilient and scalable IS strategies. This model proves particularly useful for enterprises navigating the complexities of digital transformation while aiming to minimize operational and strategic risks.