Аңдатпа
Kazakhstan’s regional innovation policy, including its Smart Specialisation and Quadruple Helix approaches, relies predominantly on static indicators, leaving the separate contributions of technological change and efficiency catch-up to productivity dynamics unexamined. This study decomposes total factor productivity (TFP) change in the innovation systems of Kazakhstan’s regions into efficiency-catch-up and technological-change components using a Malmquist-DEA framework, and identifies the spatial and structural determinants of this change. The research hypothesis is that the average decline in regional innovation productivity over 2014–2024 is driven predominantly by technological regress (a contracting production frontier) rather than efficiency catch-up, and that this process is institutional rather than geographic in nature. The study draws on an official panel from the Bureau of National Statistics of the Republic of Kazakhstan for 2014–2024 across 17 regions (187 observations), combining panel regression, Malmquist-DEA decomposition, spatial autocorrelation analysis, principal component and cluster analysis, and explainable machine learning (Random Forest, gradient boosting, CatBoost with SHAP). Results show that the geometric-mean TFP change between 2014–2016 and 2022–2024 was 0.662, driven predominantly by technological regress (0.543) and partly offset by positive efficiency catch-up (1.219). No significant global spatial autocorrelation of productivity change was detected (Moran’s I = 0.148; p = 0.436), confirming an institutional rather than geographic diffusion mechanism. The findings indicate that Kazakhstan’s Smart Specialisation and GovTech/AI Governance policies should be reoriented toward technological renewal rather than efficiency improvement alone.