AI 2006: Advances in Artificial Intelligence

Volume 4304 of the series Lecture Notes in Computer Science pp 837-846

A Neuro-fuzzy Inference System for the Evaluation of New Product Development Projects

  • Orhan FeyzioğluAffiliated withDepartment of Industrial Engineering, Galatasaray University
  • , Gülçin BüyüközkanAffiliated withDepartment of Industrial Engineering, Galatasaray University

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As a vital activity for companies, new product development is also a very risky process due to the high uncertainty degree encountered at every development stage and the inevitable dependence on how previous steps are successfully accomplished. Hence, there is an apparent need to evaluate new product initiatives systematically and make accurate decisions under uncertainty. Another major concern is the time pressure to launch a significant number of new products to preserve and increase the competitive power of the company. In this work, we propose an integrated decision-making framework based on neural networks and fuzzy logic to make appropriate decisions and accelerate the evaluation process. We are especially interested in the two initial stages where new product ideas are selected and the implementation order of the corresponding projects are determined. We show that this two-staged intelligent approach allows practitioners to roughly and quickly separate good and bad product ideas by making use of previous experiences, and then, analyze a more shortened list rigorously.