Akynbekova, Ayman
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Hybrid analytical framework for evaluating socio-economic factors in regional development Akynbekova, Ayman; Muratkhan, Raikhan; Lamasheva, Zhanar; Mukhanova, Ayagoz; Yussupova, Gulbakhar; Eslyamov, Serik; Santeyeva, Saya; Abdrakhmanova, Alfiya
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.11380

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.