A Proportional 3-Tuple Fuzzy Linguistic Screening Evaluation Model in New Product Development

It is particularly important for companies to screen new products before new products are launched to the markets. So far, lots of approaches have been excavated. However, due to uncertain, vague and incomplete information as well as dynamically complex process regarding to new product development (NPD), many approaches face with various limitations and restrictions, which lead to a dilemma that evaluators can’t take into account the aspects related to human nature, such as confidence levels, integrity of subject judgments, to evaluate new products reasonably. In this paper, we propose a proportional 3-tuple fuzzy linguistic evaluation model for screening new products and related computation operator based on canonical characteristic values (CCV). It is shown that this new model has a good ability to reflect human nature through the probability and the variable representing missing information. Thus, it not only can reflect the confidence levels of evaluators in the way of probability, but is also able to refract accuracy of subject judgment, whereby improving the precision and reasonability of final result.