Crossing the fuzzy front end chasm: Effective product project concept selection using a 2-tuple fuzzy linguistic approach

Abstract

Many companies focus on how the product concept crosses through the fuzzy front end (FFE) of the final gate to become a new product development (NPD) project. Evaluation of product concepts is a gamble in that a wrong decision to enter the product development process may waste time and money. Although analytic hierarchy process (AHP) and some of its extension methods are widely used for this purpose, their processes consist of pairwise comparisons, meaning that multiple criteria easily confuse judgments and hinder evaluation for decision-makers in practice. Therefore, this study proposes a 2-tuple fuzzy linguistic computing analysis based on fuzzy set theory and multi-criteria decision-making (MCDM) to solve this problem. The criteria for product concept selection are completely displayed in an evaluation hierarchy from the theoretical perspective. An illustrative example of a product concept evaluation model is used to demonstrate the proposed methodology. The results indicate that it is an effective approach to prioritizing potential NPD projects from a set of feasible product concepts under budget constraints in FFE. In addition, it is feasible to manipulate the evaluation processes by computers, which can reduce the time and mistakes of information translation, and avoid information loss through computing with words.