A granular consensus-reaching process using blockchain-based mechanisms to foster trust relationships in fuzzy group decision-making

Abstract

Granular computing is a framework encompassing tools, techniques, and theories that utilize information granules to address complex problems. Recently, it has become a popular area of study for managing uncertainty in group decision-making. Numerous models using granular computing have been developed to tackle issues such as incomplete information, consistency, and consensus in fuzzy group decision-making. However, existing granular-based approaches fail to consider two critical factors in managing consensus: (i) the individual’s willingness to engage and (ii) the necessity of mitigating bias in interpersonal interactions. To address these gaps, we propose a new granular consensus-reaching process inspired by the blockchain technology, which helps create trust among participants. Unlike most previous methods, our approach minimizes biased interactions among participants by using a communication structure based on blockchain and smart contracts. In this setup, participants’ identities, opinions, and decisions regarding the acceptance or rejection of received recommendations remain private from other peers. Additionally, our approach includes a trust-building mechanism, also based on blockchain, encouraging individuals to rethink and adjust their opinions. It differs from most previous trust-building methods by removing the requirement of opinion similarity and avoiding trust propagation. Instead, it builds trust among participants by allowing them to see how many peers have accepted suggested modifications. This enhances computational efficiency in creating trust and speeds up consensus. To demonstrate how effective our approach is, we provide a numerical example, along with a sensitivity analysis of its key assumptions and a discussion of its strengths and weaknesses. The results confirm that this new granular consensus-reaching process is valid, effective, and practical.