Determinants and configurational pathways of healthcare big data asset valuation:an analysis using the TOE framework and fsQCA.

backgroundHealthcare big data represents a strategic national resource with substantial potential value. At the policy level, ongoing efforts have been made to promote the transformation of healthcare data resources into data assets. However, the realization of their value remains challenging due to variations in data quality, uncertainty in application scenarios, privacy-related risks, and imperfect benefit-sharing mechanisms. This study seeks to identify the key factors affecting the valuation of healthcare big data assets. The findings are expected to provide a theoretical basis for developing scientific valuation models, optimizing resource allocation, and promoting high-quality development in the healthcare industry.

methodThis study combines the Technology-Organization-Environment (TOE) framework with information ecosystem theory to develop a dynamic value-added cycle framework for healthcare big data assets. Based on expert and practitioner surveys, six key condition variables were identified: Data Quality and Standards, Data Sharing Interface, Benefit-Sharing Mechanism, Cross-Organizational Collaboration Mechanisms, Market Demand, and Data Security and Privacy Governance Capacity. Applying Fuzzy Set Qualitative Comparative Analysis (fsQCA), the study examines complex causal pathways that lead to high asset value realization from a configurational perspective.

resultsThe study indicates that the high-level value realization of healthcare big data assets is shaped by the joint effects of technological, organizational, and environmental conditions. The configurational analysis identified three representative pathways: a Quality-security driven pathway, a Demand-driven collaborative transformation pathway, and a Market transaction-driven pathway. Among these, data quality and standardization appeared across all pathways, indicating that they constitute fundamental conditions for realizing the value of healthcare big data assets. By contrast, Data Security and Privacy Governance Capacity, benefit-sharing mechanisms, and market demand showed differentiated combinational effects across pathways, suggesting that they serve as important enabling conditions for value realization.These findings indicate that the valuation of healthcare big data assets should move beyond a single-attribute assessment approach toward a scenario-based and configurational evaluation framework. Greater attention should be paid to the alignment among data quality, security governance, collaborative mechanisms, benefit-sharing arrangements, and application demand.