Modeling the Relationship Between Corporate Performance Assessment and Information Quality

The evaluation of organizational performance (of a company or enterprise) under conditions of uncertainty (information entropy), as well as latent and/or explicit data inconsistency, may involve the following risks: misleading both external and internal stakeholders; reliance on low-quality, inaccurate, and ultimately ineffective results of business performance analysis; and inadequate assessment of indicators of financial performance. As a consequence, a symmetry of misconceptions regarding particular assets and the company’s overall financial performance emerges, leading stakeholders to make incorrect managerial and/or investment decisions, inappropriate optimization decisions, and potentially resulting in violations of stakeholder rights. The purpose of this study is to examine approaches to the mathematical modeling of the relationship between a company’s financial performance and the quality of information support (data value). The research employed general scientific research methods, as well as a methodological approach to substantiating managerial and/or investment decision-making under conditions of informational data entropy. The authors propose an approach based on the application of mathematical tools for analyzing the interrelationships among various factors affecting organizational performance evaluation and the quality of information support (data value). The implementation of the study’s findings will enable enterprises to improve such indicators as operational efficiency, financial sustainability, solvency, and others at a specific stage of the company’s life cycle.

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