An analytical framework for evaluating blockchain and IoT use cases in sustainable supply chains

The integration of blockchain technology and the Internet of Things offers substantial potential to improve sustainability, transparency, and operational efficiency in supply chains. However, identifying the most appropriate blockchain–Internet of Things use case remains a complex multi-criteria decision problem due to the presence of uncertainty, conflicting objectives, and heterogeneous adoption factors. To address this challenge, this study proposes a hybrid decision-making framework that combines q-rung orthopair fuzzy sets with entropy weighting and the Weighted Aggregated Sum Product Assessment method to evaluate alternative adoption scenarios. Four blockchain–Internet of Things integration scenarios are assessed within a five-echelon manufacturing supply chain. Thirty adoption factors are identified through a systematic literature review and structured using the Technology–Organization–Environment framework. The results indicate that technology maturity (0.0375), sustainability performance (0.0368), reduction of emissions and pollution (0.0366), customer loyalty (0.0366), and investment cost (0.0364) are the most influential evaluation criteria. Among the evaluated scenarios, blockchain-enabled Internet of Things–based tracking achieves the highest preference score (0.629). Sensitivity analyses demonstrate that the rankings remain stable under varying conditions, while comparative analysis with established multi-criteria decision-making methods confirms the robustness of the proposed framework. Overall, the results provide a reliable and uncertainty-aware decision support approach that assists managers in prioritizing high-value blockchain–Internet of Things transformation pathways in complex supply chain environments.