The heterogeneous performance outcomes observed in Industry 4.0 implementations suggest that technological adoption alone does not guarantee operational improvement. This study proposes a digital twin-based experimental framework integrating factorial design and moderated regression modeling to assess the complementarity between Industry 4.0 adoption and Lean maturity. A full factorial 2³ digital twin experimental structure was developed to simulate automation level, workforce training, and process standardization under stochastic operational variability. Moderated regression analysis was conducted to evaluate whether Lean maturity amplifies the marginal effect of Industry 4.0 adoption on operational performance. Results indicate significant main and interaction effects at the operational level, while moderation analysis confirms a strong positive amplification effect (ΔR² = 0.088, p < 0.001). Effect size analysis and bootstrap robustness tests further validate the findings. The study contributes by integrating experimental design and capability-based moderation modeling within a digital twin framework, offering insights for digital transformation sequencing strategies.
Digital Twin Experimentation to Evaluate the Complementarity Between Lean Maturity and Industry 4.0 Adoption
9 views
1 Downloads