The rapid emergence of Industry 4.0 technologies has significantly transformed modern automotive supply chains, compelling automotive industries to adopt agile and digitally integrated operational systems. However, Agile Supply Chain Management 4.0 (ASCM 4.0) adoption remains challenging due to the presence of multiple organizational, technological, financial, cultural and human-related barriers. Therefore, this study aims to identify, validate and prioritize the critical barriers affecting ASCM 4.0 adoption in Indian automotive OEM SCs through a case-based empirical investigation. This study facilitates to industrial managers with a practical implementation roadmap, along with mitigation strategies for barriers in the adoption of ASCM 4.0 in their supply network.
In this study, the PRISMA approach was used to identify the barriers based on the literature of 519 Scopus articles over the span of 2015–2026 in the automotive supply chain. Four automotive OEMs were selected for a case study to obtain input on the obtained results. Further, barriers were screened by 250 experts input from case industries and relevant industries, and based on statistical analysis, 23 barriers were finalized. Moreover, the finalized barriers are ranked through the Grey Relational Analysis (GRA)-Step-wise Weight Assessment Ratio Analysis (SWARA) approach. The obtained results are validated through sensitivity analysis (ρ = 0.912).
The results revealed that “Lack of Technical Skills and Digital Workforce”, “High Investment/ROI Uncertainty”, “Resistance to Change”, “Inadequate Infrastructure” and “Cybersecurity and Data Privacy Concerns” are the most critical barriers affecting ASCM 4.0 implementation in Indian automotive OEMs. One notable finding was that “Siloed Departments and Poor Communication” ranked 21st on GRA but topped in SWARA weights, suggesting that practitioners consistently treat cross-functional coordination as the most prominent barrier in the longer run as compared to other barriers when implementing ASCM 4.0. This gap between objective scores and expert judgment is itself a meaningful result.
The study proposes a practical implementation roadmap, managerial readiness checklist, KPI-based monitoring dashboard and barrier mitigation strategies to support automotive OEMs in planning and executing ASCM 4.0 transformation initiatives. The proposed framework can assist managers and policymakers in prioritizing implementation strategies and improving SC agility, resilience and digital readiness. The findings also have societal and environmental implications, as AI-driven demand sensing helps reduce waste and supports inclusive digital workforce development in India's automotive OEMs.
This study contributes to the existing literature by providing a case-based empirical investigation of ASCM 4.0 barriers specifically focusing on Indian automotive OEMs and not generalized manufacturing units. Moreover, it treats ASCM 4.0 as distinct from digital SC, smart SC or Industry 4.0-enabled SC. Rather than a barrier-ranking exercise, the study proposes implementation-oriented tools for automotive OEM managers and policymakers.
