<p>As digital technology undergoes rapid advancement and widespread adoption, a robust digital innovation ecosystem has steadily emerged and flourished. The level of knowledge sharing within the digital innovation ecosystem holds paramount significance in enhancing both the efficiency and the prowess of innovation across the entire system. Therefore, this paper presents an improved approach to interval intuitionistic fuzzy multi-attribute group decision making, specifically tailored to evaluate the level of knowledge sharing within the digital ecosystem for innovation. This method optimizes the aggregate operator of interval intuitionistic fuzzy sets (IVIFS), introduces correlation coefficient into index weights, improves the order relation method (G1 method), and calculates the final index weights by combining the objective weights obtained by interval intuitionistic fuzzy entropy. At the same time, variance improved weighted scoring function is introduced into the ranking part, and the scheme consistency index under different indexes is calculated by combining the index weights. The research contributions of this paper are reflected in three aspects: Firstly, embedding the evaluation of knowledge sharing levels into the governance framework of the digital innovation ecosystem breaks through the evaluation boundaries of innovation in a single organization or region. Secondly, the development of the evaluation model effectively solves the problem of quantifying qualitative indicators in the process of knowledge sharing, providing a new methodological tool for the evaluation of complex systems. Thirdly, through empirical tests, the applicability of the evaluation framework has been verified, providing a quantitative decision-making basis for policymakers to optimize the allocation of innovation resources.</p>