Abstract: Facing escalating environmental challenges and global competition, manufacturing enterprises must adopt disruptive green innovation strategies to achieve sustainable economic and environmental benefits. Disruptive green innovation refers to the process where enterprises introduce green products or services with different performance attributes from those required by mainstream consumers, initially targeting low-end or niche markets, and gradually improving the product to disrupt the mainstream market. Despite its importance in enhancing sustainable competitiveness and meeting the "dual carbon" goals, disruptive green innovation faces challenges due to its complexity, high risks, and uncertainty. This raises an important question: What factors lead to the more effective implementation of disruptive green innovation, and how do these factors interact? This study adopts a mixed-methods approach by combining case studies of BYD and Luyuan with fuzzy-set qualitative comparative analysis (fsQCA), to explore the factors driving disruptive green innovation. The results of case study identify several key drivers, including innovation ecosystem coopetition, green knowledge acquisition, green R&D investment, environmental resource coordination, and big data analytics capability. Using survey data from 332 manufacturing enterprises in strategic emerging industries, this study applies fsQCA to uncover configurational pathways driving disruptive green innovation. Key findings include: (1) Innovation ecosystem coopetition, green knowledge acquisition, green R&D investment, environmental resource orchestration, and big data analytics capability constitute core antecedents of disruptive green innovation. (2) No single antecedent is a necessary condition for disruptive green innovation. (3) Six configurational paths enabling high disruptive green innovation are categorized into four types: collaboration-dominant knowledge-data-driven, competition-dominant knowledge-R&D-driven, coopetition-dominant R&D-data-driven, and capability-dominant pathways, with substitutable relationships among element combinations under specific conditions. (4) Non-high disruptive green innovation configurations fall into two types: collaboration-resource-data-constrained and knowledge-R&D-data-constrained. This research provides theoretical and practical insights into how enterprises achieve disruptive green innovation across diverse contexts. This study makes several theoretical contributions. First, this study enriches the research on antecedent factors of disruptive green innovation by case study. Currently, research on the drivers of disruptive green innovation is still in its early stages. Through exploratory case studies, this study investigates key antecedents of disruptive green innovation and expands the understanding of this concept. Second, this study also identifies the configuration paths driving disruptive green innovation, which improves and deepens the analytical paradigm of its formation mechanism. Existing studies on the antecedents of disruptive green innovation have rarely focused on the joint effects of multiple factors. Given the complexity and systemic nature of disruptive green innovation, this study applies the fsQCA method from a configurational perspective to explore the co-action of factors such as innovation ecosystem coopetition, green knowledge acquisition, green R&D investment, environmental resource orchestration, and big data analytics capability. By adopting a mixed-methods approach, this study offers a more comprehensive interpretation of the research model, revealing results that might be overlooked by a single method. This approach helps to improve the understanding of how enterprises conduct disruptive green innovation. From a practical perspective, this study suggests that enterprises should adjust their innovation paths based on their strengths and market demands, optimizing their roles and strategies within the innovation ecosystem, especially when facing international competition. Digital technologies, particularly big data analytics capability, are identified as key drivers for disruptive green innovation. Enterprises should also strengthen co-opetition relationships with partners, engage in cross-sector collaboration, and share knowledge to enhance green innovation. Additionally, investing in green R&D and improving resource coordination are essential for achieving sustainable green innovation.