A Radial Basis Function Neural Network Multicultural Factors Evaluation Engine For Product Concept Development

Abstract

In recent years, new product development (NPD) has become more and more competitive and globalized. In order to succeed in the global marketplace, it is imperative to take multicultural factors into serious consideration during the stage of product concept development. Generally, the voice of customers has been treated as a starting point to downstream product definition and design metrics determination in developing new product concepts. As a result, the elicitation, representation and management of customer requirements will determine the success level of an organization's NPD efforts. Therefore, multicultural factors, also known as the ‘macro’ perspective in the business environment, are the most significant imperatives for organizations to handle, especially in the current trend of globalization. In practice, there are few holistic and promising systems for multicultural factor evaluation in customer requirements. This work aims at realizing a prototype system that combines the strengths of the laddering technique and the radial basis function neural network for customer requirements acquisition and multicultural factor evaluation. The performance of the prototype system is illustrated by using a case study on the design of a refrigerator. The results obtained from the case study are discussed.

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