China is undergoing a pivotal transition from “basically accomplished industrialization” to “advanced new-type industrialization,” where digital technologies accelerate the integration with the manufacturing system, spanning the total factors, the entire industrial chain (from low-end to high-end), and diversified context (from enterprises to industries to cross-sector integration). Establishing a self-organizing, self-adapting and evolvable digital innovation ecosystem will provide sustainable power for this new industrialization paradigm. To address this research question concerning the intrinsic dynamics of digital innovation ecosystem evolution, we adopt a “Technology-Data-Context (TDC)” framework to systematically examine the developmental trajectory of manufacturing digital innovation ecosystems and find their evolutionary paths. The principal findings of this paper are as follows: First, it examines the dynamic interplay of technology, data, and context across different evolutionary stages of digital innovation ecosystems from an endogenous perspective. Second, it analyzes the multidimensional value space constituting these innovation ecosystems. Third, it establishes a TDC-I (Technology-Data-Context-Innovation) framework as the foundational logic for understanding the micro-level dynamics, where reciprocal interactions among technological innovation, data-driven innovation, and contextual innovation propel the ecosystem’s formation and spiral evolution. This study makes marginal contributions to both digital innovation ecosystem theory and industrial digitalization research, while providing practical insights to enhance industrial digital transformation and informing policymaking for optimizing value co-creation in digital innovation ecosystem.