Abstract: Abstract: With the deepening implementation of the innovation-driven development strategy, new types of research and development (R&D) institutions, serving as pivotal platforms for the full integration of Industry-University-Research (IUR), play a central role in facilitating the efficient flow of innovation resources, accelerating the commercialization of scientific and technological achievements, and driving industrial transformation and upgrading. Their internal governance directly influences the rational allocation of research resources, the innovative vitality of researchers, and the market-oriented application of research outputs, thereby profoundly influencing the overall effectiveness, resilience, and competitiveness of the national innovation system. However, these institutions are confronted with complex governance challenges, including multi-stakeholder participation, ambiguous organizational boundaries, and dynamically evolving objectives that linear and static governance theories cannot adequately address. While prior studies have examined macro-level issues, such as organizational model innovation and policy support systems, as well as micro-level concerns, including governance structure optimization and incentive design, they have not adequately captured the dynamic interactions among internal governance elements or the underlying mechanisms by which organizations adapt to environmental changes. To tackle these challenges, this study proposes an analytical framework based on the theory of Complex Adaptive Systems (CAS) to investigate the internal governance logic of new types of R&D institutions. We selected six representative domestic and international cases and applied grounded theory methodology to systematically examine their governance practices and optimization pathways. The findings reveal that the internal governance of new types of R&D institutions aligns with a dynamic framework under CAS, characterized by "system identification → stakeholder interactions → resource flows → adaptation mechanisms." This framework elucidates how these institutions attain effective governance and sustainable development in complex environments. In terms of system identification, these institutions implement a multi-tiered framework encompassing institutions, departments, and individual actors, which underpins effective collaboration and enables the strategic allocation of resources. Regarding stakeholder interactions, the internal governance of these institutions operates as a complex adaptive system involving multiple stakeholders, whose effective functioning relies on dynamic interactions both among internal actors and between the organization and its external environment, exhibiting characteristics of complexity and nonlinearity. With respect to resource flows, the sustainability of internal governance depends on the circulation of diverse elements—financial, informational, material, knowledge-based, and human resources—among governance actors and between the institution and its environment. This process ultimately establishes a self-reinforcing cycle in which resource flow drives innovation, which in turn promotes further flow. Finally, concerning adaptive mechanisms, these new types of R&D institutions demonstrate a dynamic capacity to respond to changes in internal and external conditions, which can be conceptualized as a closed-loop process of perception, decision-making, implementation, and feedback. Based on these findings, the study offers the following policy recommendations:(1) Strengthen the construction of system identification to clarify the collaborative orientation among multiple stakeholders; (2) Optimize resource allocation and flow mechanisms to streamline multidimensional interaction channels; (3) Enhance mechanisms for resource circulation to ensure efficient allocation of key elements, (4) Establish a closed-loop adaptive mechanism to improve dynamic responsiveness. These recommendations provide comprehensive and actionable guidance for enhancing the internal governance, innovation efficiency, and long-term strategic development of new types of R&D institutions.