A Multi-Dimensional Framework Using Maturity Modelling and Structural Equation Analysis for Assessing Industry 4.0 Readiness in Indian Automotive Manufacturing
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India's automotive industry is one of the largest in the world, contributing 7.1% to national GDP and employing over 35 million people directly and indirectly. Despite growing interest in Industry 4.0 (I4.0), a significant gap persists between the digital transformation aspirations of Indian automotive firms and their actual readiness to achieve it. This paper presents the Industry 4.0 Maturity Assessment Model for Indian Automotive Sector (I4MAM-IAS) — a novel, contextualised seven-dimension framework validated through a comprehensive empirical study of 55 Indian automotive firms (30 OEMs and 25 Tier-1 suppliers), yielding 387 valid survey responses from the Delhi NCR region. The study integrates a 35-item structured instrument, Structural Equation Modelling (SEM), K-means cluster analysis, one-way ANOVA, and a Performance Evaluation Index (PEI) comprising 47 validated Key Performance Indicators (KPIs) across five critical domains. Key findings reveal that: (i) technological infrastructure (β = 0.57, p < 0.01) and organisational culture (β = 0.32, p < 0.05) are the strongest predictors of maturity; (ii) 73% of firms are concentrated at Levels 2–3 (Beginner to lower Intermediate); (iii) a critical self-assessment bias exists, with 97.67% of firms self-reporting as Level 5 while objective assessment places virtually all below Level 3; and (iv) training budget alone (β = 0.11, p = 0.18) is not a significant predictor of workforce readiness. The paper offers actionable recommendations for manufacturing managers, policymakers, and researchers working toward smart manufacturing in emerging economies.
Abstract (English)
India's automotive industry is one of the largest in the world, contributing 7.1% to national GDP and employing over 35 million people directly and indirectly. Despite growing interest in Industry 4.0 (I4.0), a significant gap persists between the digital transformation aspirations of Indian automotive firms and their actual readiness to achieve it. This paper presents the Industry 4.0 Maturity Assessment Model for Indian Automotive Sector (I4MAM-IAS) — a novel, contextualised seven-dimension framework validated through a comprehensive empirical study of 55 Indian automotive firms (30 OEMs and 25 Tier-1 suppliers), yielding 387 valid survey responses from the Delhi NCR region. The study integrates a 35-item structured instrument, Structural Equation Modelling (SEM), K-means cluster analysis, one-way ANOVA, and a Performance Evaluation Index (PEI) comprising 47 validated Key Performance Indicators (KPIs) across five critical domains. Key findings reveal that: (i) technological infrastructure (β = 0.57, p < 0.01) and organisational culture (β = 0.32, p < 0.05) are the strongest predictors of maturity; (ii) 73% of firms are concentrated at Levels 2–3 (Beginner to lower Intermediate); (iii) a critical self-assessment bias exists, with 97.67% of firms self-reporting as Level 5 while objective assessment places virtually all below Level 3; and (iv) training budget alone (β = 0.11, p = 0.18) is not a significant predictor of workforce readiness. The paper offers actionable recommendations for manufacturing managers, policymakers, and researchers working toward smart manufacturing in emerging economies.
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A Multi-Dimensional Framework Using Maturity Modelling and Structural Equation Analysis for Assessing Industry 4.0 Readiness in Indian Automotive Manufacturing.pdf
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- https://iistj.org/article.php?paperid=120756