In today's dynamic and complex world, supply chain management is recognized as one of the most critical success factors for organizations. The LARGE supply chain (Lean, Agile, Resilient, Green, and Ethical), with its novel approach, has been introduced as a powerful tool for enhancing business innovation, particularly in knowledge-based companies. The present study aims to model and prioritize the key success factors in implementing the LARGE supply chain in innovative companies. This study employs a mixed-methods (quantitative-qualitative) approach with an applied objective, examining a statistical population composed of academic experts, organizational specialists, and senior managers of knowledge-based companies. In the qualitative phase, data were collected through interviews with 15 experts, while in the quantitative phase, 384 questionnaires were distributed and analyzed using MAXQDA, SPSS, and SMART PLS software. Findings from the qualitative phase revealed that the paradigmatic model of the LARGE supply chain for business innovation consists of seven main concepts and 28 subcategories. Themain concepts include advanced technologies in the supply chain, agility and flexibility, advanced forecasting and planning, innovation in processes and business models, customer orientation and transparency, collaboration and integration in the supply chain, and risk management and sustainability. This model encompasses six primary dimensions: causal conditions, contextual conditions, intervening conditions, strategies, and outcomes. In the quantitative phase, confirmatory factor analysis confirmed the fit indices of the model. Additionally, the results of the Friedman test identified the priority of key success factors. According to these findings, "advanced technologies in the supply chain, " particularly the subcategory of "artificial intelligence and machine learning, " were recognized as the most important factors. By presenting a comprehensive model and identifying key success factors, this research provides practical tools for improving supply chains and enhancing innovation in knowledge-based businesses. It also offers recommendations for managers and policymakers to leverage this model effectively