In India Quick commerce (Q-commerce) is rapidly transforming urban retail by enabling the delivery of vital products within 10 to 30 minutes. The Q-commerce market of Indian country is expanding rapidly. In forecasting report of Statista, the market is projected to reach US$5.6 billion in 2026 and US$10.2 billion by 2031, reflecting the increasing demand for rapid last-mile delivery services along with continued growth of the market. Objective of this study is to determine and classified the key barriers influencing its sustainable growth. Multi-criteria decision-making (MCDM) approach is applied, integrating Entropy Weight Method (EWM), Simple Additive Weighting (SAW), and Interpretive Structural Modelling (ISM). With study of literature 16 major barriers were identified. Expert opinion evaluated to determine their interrelationships and relative importance. Most remarkable barriers are infrastructure constraints, limitations in AI-based demand forecasting, packaging waste issues, and concerns regarding product authenticity in this research work. Gig worker instability, inefficiencies in last-mile delivery, regulatory uncertainties, and high consumer price sensitivity further hinder sectoral expansion. ISM framework employed to classify all barriers into hierarchical levels foundational, intermediate, and dependent demonstrating how fundamental challenges influence operational performance and customer satisfaction. By integrating multiple decision-making methodologies, this study gives a well-structured framework for identifying barrier interrelationships and practical insights for platform operators, policymakers, and logistics stakeholders to support sustainable Q-commerce evolution in India.