Barriers to Workforce Strategy Development in the Automotive Industry: An Empirical Analysis of the Indian Passenger Vehicle Sector Using ISM and MICMAC

The automotive industry in India is undergoing a rapid digital transformation, necessitating a skilled workforce proficient in emerging technologies. However, multiple barriers impede the effective adoption of such a workforce. This study aims to analyze the interrelationships and hierarchical structure of these barriers within the Indian passenger vehicle sector. Data were collected through semi-structured interviews conducted between April 2024 and July 2025 with senior professionals from leading automotive companies and academicians with established publications in the field (ABDC A- or B-ranked journals). Of the 40 potential respondents approached via email and LinkedIn, 10 provided written consent and participated in the interviews. The responses were transcribed and subjected to thematic analysis, which identified ten key barriers influencing skilled workforce adoption in the era of automotive digital transformation. Interpretive Structural Modeling (ISM) was used to establish the hierarchical structure of these barriers, while MICMAC (Matrice d’Impacts Croisés-Multiplication Appliquée à un Classement) analysis was employed to classify them according to their driving and dependence power. The root causes appear to include poor training infrastructure, shortcomings in industry-academia collaboration, and policy inefficiencies. These root causes strongly influence other dependent barriers, such as the limited availability of digital skill sets, the high cost of upskilling, and low workforce adaptability due to organizational resistance to change. This structured understanding provides strategic insights for policymakers, industry leaders, and educators seeking to design targeted interventions to strengthen the digital workforce ecosystem in India’s passenger vehicle sector.