The SERS Framework: A Stakeholder-Oriented Approach to Designing and Evaluating Distributed Ledger Systems
Description
This dataset supports the development and validation of a multi-criteria performance assessment framework for healthcare data management systems that integrate Internet of Things (IoT) and blockchain (distributed ledger technology, DLT) technologies. The framework was constructed and weighted using a two-stage expert elicitation methodology combining the Fuzzy Delphi Method (FDM) and the Analytic Network Process (ANP). Framework Structure: The assessment framework is organized around four primary performance criteria: Security, Efficiency, Resiliency, and Sustainability, each decomposed into four sub-criteria: - Security: Defended, Protected, Strengthened, Tested - Efficiency: Accessible and Affordable, Cost-effective, Optimized, Reliable - Resiliency: Recovery, Redundancy, Resourcefulness, Robustness - Sustainability: Focus on Value-Added Core Competencies, Reduce Resource Usage, Reduce Total Operation Costs, Reduce Wastes
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Expert Panel: Criteria importance was evaluated by a panel of 17 international domain experts affiliated with leading universities in the USA, UK, Canada, Germany, France, and Jordan. Experts held positions ranging from Associate Professor to Full Professor and Chief Technology Officer, with backgrounds spanning blockchain and cryptocurrency, medical informatics, cyber security, digital health, AI and data science, and IT management. Panel members averaged over 18 years in academic positions and over 18 years of IT expertise; a subset held dedicated DLT expertise ranging from 1 to 8 years. Data Collection Instruments A structured survey (included as Appendix) was administered to the expert panel. Linguistic responses on a five-point importance scale were collected and mapped to triangular fuzzy numbers (TFNs) for the Delphi stage, and to a nine-point TFN pairwise comparison scale for the ANP stage. Linguistic-to-fuzzy conversion tables (Appendix 1, Tables A.1 and A.2) are provided. Dataset Contents The main datasheet (xlsx) contains six worksheets: 1. Delphi — Raw fuzzy TFN responses (lower, middle, upper bounds) from 17 experts across all 16 sub-criteria (C11–C44), used for the Fuzzy Delphi consensus round. 2. ANP criteria — Aggregated pairwise comparison matrices (geometric mean across experts) for the four primary criteria. 3. ANP Sub Security / Efficiency / Resiliency / Sustainability\_Experts— Pairwise comparison matrices for sub-criteria within each primary criterion, aggregated across 17 experts. 4. ANP — Final ANP weights: normalized-by-cluster weights and global limiting weights for all 16 sub-criteria, alongside the supermatrix and final criterion weights derived via ANP. 5. Graphs — Summary tables and aggregated weights prepared for visualization. Final global weights assigned to the four primary criteria were approximately: Resiliency (0.262), Security (0.252), Sustainability (0.245), and Efficiency (0.241), indicating a relatively balanced but resilience-prioritizing framework. Among sub-criteria, "Protected" (Security) and "Focus on Value-Added Core Competencies" (Sustainability) received the highest global weights. Intended Use This dataset enables replication of the FDM–ANP weighting procedure, benchmarking of alternative MCDM approaches, and application of the finalized framework to evaluate IoT-blockchain healthcare architectures.