Indian manufacturing companies are progressively implementing Industry 4.0 technologies to enhance the level of operational efficiency and the managerial decision-making process; nevertheless, there is limited empirical evidence of how the adoption of the Digital Twin (DT) affects performance, especially in the emerging economy environment. This research examines how researchers can use Digital Twin capabilities to improve the efficiency of operations and effectiveness of decisions in Indian manufacturing companies. Quantitative, cross-sectional research design was used based on the data on surveys conducted on 126 professionals working in the automotive, electronics, and process manufacturing industries. The proposed relationships and the mediation effects were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings suggest that the capabilities of Digital Twin positively influence the operational efficiency (β = 0.61, p < 0.001), which explains a third of its variation (R²= 0.37). Operational efficiency, on the other hand, has an overwhelming effect on decision-making effectiveness (β 0.53, p < 0.01) and the model accounts for 41 % of the variation in decision outcomes (R²= 0.41). The mediation analysis proves that the relationship between the Digital Twin capabilities and the decision-making effectiveness is partially mediated by operational efficiency. The decomposition analysis also shows that the largest marginal contribution to efficiency gains is yielded by analytics-based Digital Twin applications that are linked to a significant shortening of decision lead time. This paper concludes that the strategic value of Digital twins is that they merge real-time monitoring, simulation, and analytics to provide cumulative operational and managerial value. Such results provide practical information to manufacturing managers who want to focus on high-impact Digital Twin implementations.
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