An ISM-DEMATEL approach for developing a structured strategic pathway in medical device innovation

The development of the biomedical startup industry requires constant adaptation to clinical demands and changes in the healthcare system. Biomedical startups face multiple challenges across all stages from early research to market entry, and existing literature lacks a systematic framework for sequencing strategic priorities in the Medical Device Innovation Process (MDIP). This study interviewed 39 experts from the BioMed Commercialization Center (BMCC), including review committee members, project managers, and innovation team members, and conducted a survey of 60 experienced biomedical practitioners, yielding 52 returned questionnaires, of which 35 were valid for analysis. Through content analysis, 18 key MDIP factors were identified. Interpretive Structural Modeling (ISM) was applied to construct a hierarchical structure of these factors, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was subsequently used to quantify and prioritize the net influences among factors within each ISM level. Compared with our previous ISM-based study [1], the present study extends the analysis by integrating DEMATEL to clarify the directional relationships among interacting factors within hierarchical level and to develop a structured strategic pathway. ISM identified seven hierarchical levels among the 18 MDIP factors, with Clinical Needs Assessment positioned as the root-driving factor. DEMATEL further prioritized the net influences within each ISM level and generated a seven-phase strategic pathway linking clinical needs, clinical and regulatory planning, market feasibility, business model development, technology implementation, production assessment, supply chain planning, and intellectual property protection. The integrated ISM-DEMATEL framework transforms a complex 18 factor innovation landscape into a structured strategic pathway. This framework may help biomedical startup practitioners understand the relative ordering and interdependencies among influencing factors, providing an analytical foundation for decision-making prioritization under resource-constrained conditions. Further empirical validation is required to determine whether application of the framework improves innovation performance or resource allocation.