Responsible production in Kazakhstan’s manufacturing sector: An empirical assessment of environmental, operational, and social drivers

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The study analyzes the implementation of responsible production practices in Kazakhstan’s manufacturing sector, an area of growing importance for sustainable development in emerging economies. The aim is to examine how environmental, operational, and social factors influence production processes and community contributions. Data were collected through an online survey conducted between May and August 2024, using a voluntary response sampling method. To enhance the representativeness of the findings, the sectoral distribution of the responding enterprises was analyzed post-collection. The survey captured top, middle, and line management responses to comprehensively assess sustainability practices. Structural equation modeling (PLS-SEM) was employed to evaluate the relationships between ecological operational efficiency, environmental protection, resource efficiency, waste management, social factors, product manufacturing, and community contribution. The findings reveal that environmental protection, efficient resource use, and effective waste management significantly strengthen manufacturing performance and enhance companies’ contributions to community development. In contrast, improvements in ecological operational efficiency and workplace social initiatives do not directly impact production outcomes. The study concludes that integrating sustainable environmental and resource management practices into production processes is crucial for enhancing both manufacturing performance and broader societal outcomes. The findings offer practical implications for industrial managers, policymakers, and stakeholders aiming to promote sustainability transitions in manufacturing sectors.

Acknowledgment
This study was funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19576593).

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    • Figure 1. Conceptual model
    • Figure 2. Structural model and path coefficients
    • Table 1. Latent variables and key indicators based on the literature
    • Table 2. Companies’ characteristics
    • Table 3. Reliability and validity measures
    • Table 4. Correlation matrix of constructs
    • Table 5. Path coefficients and significance testing
    • Table 6. Hypotheses testing
    • Table 7. Indirect effects
    • Table 8. Direct effects
    • Table A1. Questionnaire elements
    • Table B1. Descriptive statistics
    • Conceptualization
      Aknur Zhidebekkyzy, Aisulu Moldabekova, Yuriy Bilan
    • Data curation
      Aknur Zhidebekkyzy
    • Investigation
      Aknur Zhidebekkyzy, Aisulu Moldabekova, Yuriy Bilan
    • Methodology
      Aknur Zhidebekkyzy, Aisulu Moldabekova
    • Project administration
      Aknur Zhidebekkyzy
    • Supervision
      Aknur Zhidebekkyzy
    • Validation
      Aknur Zhidebekkyzy, Aisulu Moldabekova, Yuriy Bilan
    • Visualization
      Aknur Zhidebekkyzy, Aisulu Moldabekova
    • Writing – original draft
      Aknur Zhidebekkyzy, Aisulu Moldabekova
    • Formal Analysis
      Aisulu Moldabekova, Yuriy Bilan
    • Writing – review & editing
      Yuriy Bilan