Evaluation of Sustainable Strategies for Implementing Blockchain Technology in the Solar Energy Supply Chain Under Fuzzy ZE-numbers
Abstract
The accelerating transition toward renewable energy highlights the need for decision-support frameworks that can address uncertainty, heterogeneity, and governance challenges. This study introduces a hybrid methodology that integrates fuzzy ZE-numbers into the Basic Criteria Method (BCM) and applies the Double Normalization Multiple Aggregation (DNMA) model. The proposed ZE-BCM-DNMA framework captures expert subjectivity while ensuring robust and transparent evaluation of blockchain adoption strategies in Turkey’s solar energy sector. Empirical evidence was gathered through structured linguistic assessments from three national experts, modeled via fuzzy ZE logic. The analysis identifies Strategy A6, emphasizing government-led initiatives and collaboration with private actors, and Strategy A4, focused on adaptive energy management platforms, as the most effective solutions in terms of scalability, sustainability, and technical feasibility. Sensitivity analysis demonstrates ranking stability under diverse weighting scenarios, while comparative benchmarking confirms ZE-DNMA’s superiority over fuzzy TOPSIS and VIKOR. The framework advances theory by extending ZE-number applications in multi-criteria energy decision-making and practice by offering a transferable model for emerging economies. Policy implications highlight the importance of integrating blockchain-enabled transparency, cybersecurity, and environmental accountability into national renewable strategies. The study’s unique contribution lies in bridging methodological innovation with actionable insights, positioning blockchain as a viable enabler of decentralized, resilient, and sustainable solar energy ecosystems. Future research may expand the model to other renewable domains and incorporate dynamic weighting to reflect evolving technological and regulatory contexts.