Journal of Resource Management and Decision Engineering In Press 2027 04 01 Power Structure and Information Flow Analysis in the Health Tourism Network Using a Social Network Analysis (SNA) Approach Power Structure and Information Flow Analysis in the Health Tourism Network Using a Social Network Analysis (SNA) Approach 1 21 EN Journal Article 2026 07 16 <p>This study aimed to analyze the structure of power and patterns of information flow among stakeholders in Tehran’s health tourism network using Social Network Analysis (SNA). This quantitative, applied, cross-sectional study was conducted among 72 organizational actors involved in the health tourism network of Tehran, Iran. Participants included governmental and regulatory organizations, hospitals and specialized medical centers, health tourism facilitation agencies, physicians and clinical providers, medical travel agencies, hotels and accommodation providers, insurance-related organizations, and complementary service providers. Actors were selected using purposive and network-based sampling. Data were collected through a structured SNA questionnaire assessing directed information-exchange ties and perceived power, influence, and dependency relationships. Separate 72 × 72 adjacency matrices were constructed for information flow and power. Network-level indicators, including density, reciprocity, average geodesic distance, centralization, and component structure, as well as actor-level measures, including in-degree, out-degree, betweenness, closeness, and eigenvector centrality, were analyzed using UCINET and NetDraw. The information-flow network contained 1,094 directed ties and showed greater density (0.214) and reciprocity (0.410) than the power network, which contained 676 ties with a density of 0.132 and reciprocity of 0.290. In-degree centralization was substantially higher in the power network (61.80%) than in the information network (47.60%), indicating greater concentration of influence. The principal governmental/regulatory actor had the highest power in-degree (0.817) and eigenvector centrality (0.918), while a major health tourism facilitator demonstrated the highest betweenness centrality (0.203), identifying it as the principal broker. Governmental organizations and major hospitals formed the structural core, whereas facilitators occupied key bridging positions between clinical, tourism, and supporting sectors. Tehran’s health tourism network demonstrated a moderately integrated core–periphery structure in which information exchange was broader and more reciprocal than the distribution of power, while governmental organizations, major hospitals, and facilitators played distinct but complementary roles in governance, resource control, and interorganizational brokerage.</p> https://journalrmde.com/index.php/jrmde/article/download/424/411