Developing human capital through innovative competencies in the context of Industry 4.0: Insights from Kazakhstan
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DOIhttp://dx.doi.org/10.21511/ppm.24(1).2026.45
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Article InfoVolume 24 2026, Issue #1, pp. 697–709
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Type of the article: Research Article
Abstract
The purpose of this study is to identify the factors influencing human capital development through the integration of key innovative competencies and to assess their contribution to readiness for Industry 4.0. A quantitative survey was conducted among 1,447 respondents aged 18–63 across Kazakhstan between September and October 2025. This population was selected because individuals aged 18–63 represent the core economically active workforce in Kazakhstan and are directly involved in human capital formation. The survey method was selected to capture a large and diverse sample and to examine relationships between latent constructs within the proposed model. Structural equation modeling using the partial least squares method (PLS-SEM) was employed to examine the relationships between innovative competencies and human capital development. The results demonstrate that all examined innovative competencies have positive and statistically significant effects on human capital development (p < 0.001). Creativity shows the strongest influence (β = 0.333), followed by emotional intelligence (β = 0.241), artificial intelligence (β = 0.135), and critical thinking (β = 0.129). Human capital, in turn, exerts a strong positive effect on readiness for Industry 4.0 (β = 0.650, p < 0.001), thereby demonstrating that developing human capital is essential for the effective adoption and coherent integration of Industry 4.0 technologies. These results provide valuable direction for policymakers, educators, and organizations aiming to enhance workforce readiness for Industry 4.0 by strategically investing in innovative skill development initiatives.
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JEL Classification (Paper profile tab)J24, O15, O33
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References39
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Tables5
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Figures2
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- Figure 1. Proposed research model
- Figure 2. Testing the hypothesized model
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- Table 1. Participants’ demographic profile
- Table 2. Measurement model results
- Table 3. Measurement model’s discriminant validity
- Таble 4. Hypotheses testing results
- Table 5. Multi-group analysis across regions of Kazakhstan
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