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Article · Bulletin of Electrical Engineering and Informatics · April 1, 2026

Hybrid analytical framework for evaluating socio-economic factors in regional development

Айман Акынбекова, Raikhan Muratkhan, Zhanar Lamasheva, Ayagoz Mukhanova, Gulbakhar Yussupova, Serik Eslyamov

Zhanar Lamasheva
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Abstract

This study aims to develop and validate a hybrid analytical framework for evaluating the influence of socio-economic factors on regional development. The framework combines correlation analysis, principal component analysis (PCA), and fuzzy inference modeling into a unified approach, applied to 2023 data from the city of Taraz, Kazakhstan, covering 16 socio-economic indicators across demographic, economic, social, and industrial domains. The findings reveal that investments in fixed assets (r=0.8963 and q=0.000010), average monthly salary (r=0.8907 and q=0.000010), and retail trade (r=0.8885 and q=0.000010) exert the strongest positive influence, while migration balance and manufacturing show weak or negative effects. The results demonstrate that the hybrid model offers more comprehensive insights compared to single-method approaches, validating its effectiveness in capturing complex and uncertain dependencies. Practically, the model provides policymakers with a robust decision-support tool for identifying priority areas, designing targeted strategies, and ensuring sustainable regional growth, with adaptability to other regions and datasets.

Regional Economic and Spatial AnalysisEconomic Development and Regional CompetitivenessRegional Socio-Economic Development Trendsregional developmentsocioeconomic factorsprincipal component analysis

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