A Cipher Fuzzy Decision Framework for Prioritizing IoT Investments in Smart Sustainable Infrastructure

Internet of Things (IoT) investments for smart and sustainable infrastructures are becoming increasingly strategic; however, there is significant uncertainty in the literature regarding which alternatives these investments should target. Decision-makers struggle to prioritize critical infrastructure options under limited financial resources and rapidly evolving technological dynamics. Existing studies exhibit methodological limitations, particularly in providing holistic decision models and realistically modeling uncertainty. To address this gap, this study proposes a novel integrated decision-making framework. The proposed model uniquely combines Manhattan distance-based centrality for consensus expert selection, cipher fuzzy cognitive maps for criteria weighting, and cipher fuzzy principal component ranking optimization for alternative prioritization within a unified structure. The primary methodological novelty lies in the development and integration of Cipher Fuzzy Sets, a data-driven uncertainty modeling approach that directly decodes expert judgments from raw reality. Unlike classical fuzzy sets, this structure explicitly separates membership, non-membership, and hesitation through reverse encoding and calibration, thereby reducing information loss, expert bias, nonlinear distortion, and statistical noise without requiring traditional defuzzification. The empirical findings indicate that circular design is the most critical criterion for IoT investments, while distributed energy resources represent the top-ranked sustainable infrastructure alternative. By introducing a new fuzzy set structure and a fully integrated consensus-based prioritization framework, this study provides both theoretical innovation and practical guidance for strategic IoT investment planning.