Cubic picture fuzzy topological data analysis with integrating blockchain and the metaverse for uncertain supply chain management

Abstract

This article explores the idea of cubic picture fuzzy sets (CPFSs) for developing blockchain-driven solutions to meet uncertain supply chain management (SCM) and contemporary urban transportation (CUT) challenges. For this objective, the concept of topological structures on CPFSs is explored and the notion of cubic picture fuzzy topology is defined with P-order and R-order. We construct CRITIC-COPRAS method based on cubic picture fuzzy topological data analysis and cubic picture fuzzy fairly aggregation operator for finding solutions to SCM, CUT, electronic toll collection, fare management, micromobility solutions, and car-sharing implementations. We also examine the transformative potential of blockchain technology within the metaverse particularly in the domains of ride-sharing and peer-to-peer mobility platforms. To systematically evaluate and prioritize these integration strategies, we employ a robust multi-criteria decision-making (MCDM) model. This comprehensive assessment covers eight criteria including, transportation efficiency, user experience, technological feasibility, and regulatory compliance. Moreover, it offers promising solutions for revenue management and data security in electronic toll collection and public transportation fare management.