Economic and mathematical model of a comprehensive assessment of the productivity of a trading company

Abstract

This article presents an economic and mathematical model for a comprehensive assessment of a trading company’s performance, developed to provide analytical support for e-business development. The model comprises three interconnected components: a financial component, providing a retrospective assessment of profitability, liquidity, and business activity; a productivity component, characterizing the operational effectiveness of resource use; and an artificial intelligence component, generating predictive estimates based on machine learning algorithms—random forest and gradient boosting. The results of all three components are aggregated into a single integrated indicator, Q, whose value determines the company’s affiliation with one of three risk zones. Each zone corresponds to a specific set of corrective measures distributed among the responsible departments, which ensures the transformation of the integrated assessment into targeted planning targets. The practical significance of the model lies in its applicability as a tool for the early detection of threats to the financial stability of a trading organization.