The proposed methodology possesses a number of merits compared to other MCDM techniques presented in the literature
for supplier selection. First, the developed method is a group decision making process which enables the group to identify
and better appreciate the differences and similarities of their judgments. Second, the proposed approach is apt to
incorporate imprecise data into the analysis using fuzzy set theory. Third, this methodology enables to consider the impacts
of relationships among the purchased product features and supplier selection criteria, and also the inner dependence among
supplier selection criteria for achieving higher satisfaction to meet company’s requirements. Fourth, in order to calculate the
upper and lower bounds of the weights of the supplier selection criteria and the supplier assessments, the proposed method
uses the fuzzy weighted average method that rectifies the problem of loss of information that occurs when integrating
imprecise and subjective information. Thus, it is likely to produce more realistic overall desirability levels. Finally, the proposed
approach employs a fuzzy number ranking method based on area measurement, which has a high ability to discriminate
among the fuzzy numbers to be ranked. Future research will focus on applying the decision framework presented in
here to real-world group decision making problems in diverse disciplines that can be represented in a HOQ structure.