(untitled) (International journal of artificial intelligence, 2026)
Small businesses are the backbone of emerging economies, yet a persistent gap exists between their quantitative growth and qualitative performance. This study investigates how a comprehensive, multidimensional assessment framework can serve as a practical lever for improving small business performance in the context of Uzbekistan's transitioning economy. Drawing on primary data collected from 120 small business entities across four major regions of Uzbekistan (2023–2024), the research integrates the Balanced Scorecard (BSC) methodology, Analytic Hierarchy Process (AHP), correlation-regression analysis and cluster analysis to construct a validated Integral Performance Index (IPI). Results reveal that financial indicators alone explain only 46% of performance variance, while innovation activity (r = 0.61), customer satisfaction (r = 0.59) and employee competency (r = 0.48) collectively account for an additional 28–34% of explained variance. High-performing firms (IPI > 70; n = 31) are distinguished by systematic financial planning, CRM adoption, continuous employee training and active participation in business networks. The proposed four-dimensional IPI model (financial efficiency, customer and market, internal processes, learning and innovation) offers a scalable, context-sensitive tool for small business practitioners, policymakers and researchers. Findings contribute to the growing literature on SME performance measurement in transition economies and provide actionable guidance for evidence-based business strategy.