Digital Transformation and Administration Innovation 4 Serial Number 14 2026 07 01 A Systemic Analysis of the Health Entrepreneurial Ecosystem for Improving the Performance of Knowledge-Based Startups: Applying Soft Systems Methodology A Systemic Analysis of the Health Entrepreneurial Ecosystem for Improving the Performance of Knowledge-Based Startups: Applying Soft Systems Methodology 1 19 10.61838/dtai.264 EN Journal Article 2026 01 12 <p>This article aims to analyze the problematic situation of the health entrepreneurial ecosystem and to develop a systemic framework for improving the performance of knowledge-based startups in this field. The main problem addressed in this study is that the performance of health startups is not merely determined by technical capabilities, internal resources, or the initial business idea; rather, it is shaped within a network of interactions among government and regulatory bodies, knowledge-based firms, healthcare centers, markets, universities, intermediary institutions, and investors. This study is applied-developmental in terms of purpose and qualitative-exploratory in terms of method. Soft Systems Methodology (SSM) was employed to analyze the complex, multi-actor, and ill-structured nature of the research problem. Data were collected through semi-structured interviews with 20 experts, managers of knowledge-based firms, startup actors, investors, managers of science parks and accelerators, and health ecosystem specialists in Tehran. Participants were selected through purposive and snowball sampling. Data analysis was conducted based on the main stages of SSM, including identifying the problematic situation, developing the rich picture, formulating root definitions, conducting CATWOE analysis, designing conceptual models, comparing the real world with the desirable models, and identifying feasible and desirable change actions. The findings indicate that the key problem of the health entrepreneurial ecosystem is not the absolute absence of actors, but institutional misalignment, weak intermediary mechanisms, conflicting decision logics, lack of patient capital, weak institutional learning, and poor uncertainty management. The study concludes that improving the performance of health startups requires a transition from reactive, fragmented, and person-centered governance toward anticipatory, participatory, evidence-based, and learning-oriented governance.</p> https://journaldtai.com/index.php/jdtai/article/download/264/279