Fuzzy consensus measure on verbal opinions

In the group decision-making process, consensus is an important indication of group agreement or reliability. Traditional methods to measure consensus refer mostly to gauging variance among the participants’ opinions by transforming them into numbers in the interval scale. In this study we propose a new value-based measure, in which verbal opinions are transformed into values by means of fuzzy membership functions. To understand how the proposed method performs, we conduct two experiments to compare its performance with the variance-based methods and entropy measure. The results show that our method is more appropriate to account for participants’ consensus judgments based on verbal opinions.