A mixed-method approach to develop an eco-robust supply chain management framework for Bangladeshi RMG industries

• Prioritized eco-robust SCM strategies using AHP with expert input. • Applied QFD framework to link eco-robust strategies to sustainability/resilience goals. • Developed an optimization model to maximize eco-robust performance within budget limits. • Aligned eco-robust SCM strategies with SDGs for supporting global objectives. • Offered a roadmap for RMG managers to adopt practices enhancing eco-robust performance. The Bangladeshi Readymade Garment (RMG) industry plays a pivotal role in the national economy, yet it faces significant sustainability challenges due to high resource consumption, environmental impact, and vulnerability to supply chain disruptions. This study adopts a mixed-method approach with a QFD-based Optimization Model to develop an Eco-Robust Supply Chain Management (ERSCM) framework. By integrating sustainability and resilience into a unified model, the research provides a strategic approach to enhancing environmental performance while improving resilience against supply chain disruptions. The methodology employs a mixed-method approach: expert insights were collected and prioritized using the Analytical Hierarchy Process to rank ERSCM strategies, which were then mapped to sustainability and resilience goals through Quality Function Deployment. This relationship analysis was followed by a Mixed-Integer Linear Programming optimization to select cost-effective strategies that maximize eco-robust performance under budget constraints. The results reveal that Technology Integration, Continuous Improvement and Innovation, Supply Chain Transparency, and Stakeholder Collaboration are among the most impactful ERSCM strategies, demonstrating strong alignment with Sustainable Development Goals. The findings underscore that, even within budgetary limits, high-impact, cost-efficient strategies can be implemented to advance both sustainability and resilience. This research contributes to Sustainable Supply Chain Management literature by developing a novel QFD-based optimization model that systematically integrates sustainability and resilience. Methodologically, it combines AHP for strategic prioritization, QFD for mapping interdependencies, and MILP for cost-effective decision-making. This research also offers actionable insights for RMG industry managers aiming to transition toward eco-robust practices that support sustainable and resilient development.