This study aims to investigate the relationship between environmental sustainability, social development, and governance within Kazakhstan’s agro-industrial complex. The paper applies econometric modeling and statistical analysis to assess these relationships and provide strategic recommendations for sustainable development. A dataset from 2013 to 2023, sourced from the Bureau of National Statistics of the Republic of Kazakhstan, was utilized to assess the influence of transit routes and agriculture on ESG performance. Principal component analysis (PCA) and regression modeling identified three key components – environmental (84.3%), social (98.4%), and governance (88.33%) – as significant contributors to ESG variability. The results demonstrate that transit flows positively affect environmental and governance indicators (β = 0.266, p = 0.050), while agro-industrial activity has mixed effects: improved social sustainability but increased environmental pressure. The combined impact of transit corridors and the agro-industrial complex provides a more comprehensive explanation of ESG variability (R² = 0.998), reinforcing the need for integrated policy approaches. The findings highlight the strategic importance of aligning transit infrastructure and agro-industrial development with ESG frameworks. This paper contributes to the discourse on sustainable development by offering practical insights for policymakers on optimizing logistics and agricultural strategies to promote ESG adoption, particularly in agriculture-dependent economies.
Acknowledgments
This study is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant “Strategy of structural and technological modernization of the basic sectors of the economy of the Republic of Kazakhstan based on ESG: criteria, mechanisms and forecast scenarios” BR24993089).