Supply Chain Risk Prioritization in Indian 4-Wheeler Electric Vehicles based on MCDM-IVIFS

As per today’s scenario, the deployments electric vehicle (EV) and their mobilization with great acceptance in society has increased considerably. The rapid growth of India’s 4-wheeler EV market is driven by strong policy support and environmental goals, but has introduced complex new supply chain risks. So, a robust risk prioritization framework tailored for the Indian 4-wheeler EV supply chain is designed in this work. The proposed approach integrates cause-and-effect analysis, Failure Mode and Effects Analysis (FMEA), and an advanced fuzzy Multi-Criteria Decision-Making (MCDM) method using Interval-Valued Intuitionistic Fuzzy Sets (IVIFS). This fusion allows for precise and dynamic risk assessment by capturing uncertainty, expert hesitation, and variability in feedbacks. The formulated work effectively identifies critical supply chain vulnerabilities under ambiguous conditions. The system computational efficiency, accuracy, and decision reliability performances are evaluated and compared with traditional fuzzy MCDM. Additionally, the study highlights the model's alignment with key United Nations Sustainable Development Goals (SDGs), especially in promoting sustainable mobility in India. The framework offers practical implications for policymakers and industry stakeholders to strengthen EV adoption strategies and supply chain resilience.