A fuzzy analysis method for new-product development

Abstract

This paper reports a new idea-screening method for new product development (NPD) with a group of decision makers having imprecise, inconsistent and uncertain preferences. The traditional NPD analysis method determines the solution using the membership function of the fuzzy set which cannot treat the negative evidence. The advantage of vague sets with the capability of representing negative evidences supports the decision makers with ability of modeling uncertain objects. In this paper, we present a new method for new-product screening in the NPD process by relaxing a number of assumptions so that imprecise, inconsistent and uncertain ratings can be considered In addition, a new similarity measure of vague sets is introduced to proceed with the ratings aggregation for a group of decision makers. From numerical illustrations, the proposed model can outperform conventional fuzzy methods. It is able to provide decision makers (DMs) with consistent information and to model the situation where vague and ill-defined information exist in the decision process.