A Human-Centered Evaluation Model for IoT Platforms Using a Hybrid Multi-Criteria Decision-Making Framework

This study develops a behaviorally informed evaluation model for Internet of Things (IoT) development platforms by integrating human-centered decision perspectives with a hybrid multi-criteria decision-making (MCDM) approach. Through an extensive literature review and expert consultation, this study identifies and structures the critical factors influencing users’ (customer satisfaction) and developers’ (strategy selection) perceptions of IoT platform performance. Three stages of purposive surveys were conducted to gather the judgments of experienced IoT specialists. The fuzzy Delphi method (FDM) synthesizes expert judgments to reduce 30 sub-criteria to 16 key factors through fuzzy-based consensus. The analytic hierarchy process (AHP) then converts subjective assessments into consistent and quantifiable weights of the sub-criteria to ensure hierarchical rigor. Finally, VIKOR identifies a compromise solution that balances conflicting criteria and yields robust platform rankings of four representative IoT platforms. This study finds that customer satisfaction outweighs strategic considerations in IoT platform evaluation, with Security and Privacy ranked as the top two critical criteria, followed by Technology, Implementation, Convenience, and Market. Operations optimization, Trust and verification, and Customization emerge as the most influential sub-criteria. Benchmarking four IoT platforms identifies performance gaps and provides a self-assessment tool to optimize resources, align technical performance with user perceptions, and support evidence-based policy.