Abstract: The optimal allocation of digital innovation ecosystems is of great significance for the development of new quality productive forces. Based on the theory of digital innovation systems, this paper used the QCA, NCA and DEA methods to explore the configuration paths through which digital innovation ecosystems drive the development of new quality productive forces, focusing on the 30 provincial-level regions in China. The study found that: First, no single antecedent condition within the digital innovation ecosystem can be regarded as the necessary condition to promote the development of new quality productive forces; instead, it needs to be driven synergistically through a co-development combination. Second, four configurations that promote the development of new quality productive forces are identified: the "data-driven foundational frontier innovation" model, the "data-driven enterprise-user co-creation" model, the "digital policy-driven user open innovation" model, and the "data and digital policy jointly driven diversified collaborative innovation" model, all exhibiting asymmetrical characteristics that "all roads lead to Rome". Third, weak enterprise application innovation capability is a significant factor limiting the development of new quality productive forces. This research helps reveal the "black box" mechanism of new quality productive forces formation within digital innovation ecosystems, thus providing theoretical and practical insights for promoting the development of new quality productive forces in China according to local conditions.

Key words: digital innovation ecosystem, new quality productivity, configuration path, fuzzy sets qualitative comparative analysis (fsQCA), necessary condition analysis (NCA)