A decision-making framework for blockchain platform evaluation in spherical fuzzy environment

Blockchain systems with critical features (e.g., security, flexibility against attacks, and data traceability) have created possibilities for users to develop innovative economic and business models. Despite the abundance and variety of features of blockchain technology, choosing a suitable and reliable blockchain platform is somewhat challenging. Several criteria, including profitability, sustainability, and popularity, should be considered to identify such platforms. Accordingly, this study investigates the blockchain platform evaluation and selection as a multi-criteria decision-making (MCDM) problem. In this regard, we propose an integrated approach based on the extended version of MCDM methods in a spherical fuzzy environment. In the developed approach, the main criteria are weighted using the developed spherical fuzzy best-worst method (SF-BWM) to reduce uncertainty in pairwise comparisons. Then, the 15 blockchain platforms are analyzed and ranked using spherical fuzzy measurement of alternatives and ranking according to the compromise solution (SF-MARCOS). The outputs of the SFBWM-MARCOS approach imply that Bitcoin and Ethereum are placed in the first and second priorities, respectively. The comparison of the results with other MCDM methods and sensitivity analysis demonstrates the performance of the proposed approach and its ranking stability in various scenarios.