<p>Despite India’s significant potential in global apparel manufacturing, existing competitiveness frameworks often fail to capture the complex causal interdependencies among strategic drivers in emerging market contexts. This study addresses this gap by applying Weighted Influence Non-linear Gauge System (WINGS)-based prominence–relation analysis to systematically identify and prioritize competitiveness drivers in India’s apparel supply chains. Unlike traditional approaches that treat factors in isolation, WINGS methodology reveals cause–effect hierarchies and interaction patterns among 12 critical factors. The analysis identifies Global Trade Agreements, Location, Flexibility, and Production Costs and Labor as priority drivers with the highest systemic influence, while Resource Management, Consumer Preferences, and Government Policies act as contingent factors requiring adaptive management. Autonomous factors such as Positioning and Differentiation, Lean Practices, and Competitive Strategy function as supportive enablers, and Exports and Technology emerge as long-term outcome indicators. This study makes three key contributions: First, it extends competitiveness theory by demonstrating how macro-level enablers (Trade Agreements, Policy Frameworks) interact with firm-level capabilities (Flexibility, Resource Management) to determine systemic performance. Second, it introduces the WINGS methodology to apparel supply chain research, offering a robust framework for analyzing causal relationships under expert uncertainty. Third, it provides actionable, prioritized insights for policymakers and industry leaders to enhance India’s competitiveness in sustainable, resilient, and digitally enabled apparel supply chains.</p>