Improvement of customers’ satisfaction with new product design using an adaptive neuro-fuzzy inference systems approach

Abstract

In today’s competitive world, most organizations need to successfully develop new products. The success of new products can be a competitive weapon and advantage for a firm to survive in the current dynamic markets. The most important aspect of the product design is identifying customers’ needs of products. One of the most common methods to satisfy customers’ needs is improvement of customers’ satisfaction. The present paper applies the aspects of the 4P marketing mix (product, price, place, and promotion) for modeling the relationship between customers’ satisfaction and new product design with handling nonlinearity as well as fuzziness. A methodology based on the adaptive neuro-fuzzy inference systems (ANFIS) approach is presented to improve customers’ satisfaction while setting products’ design attributes in a fuzzy environment. The intelligent approach of the present study is then applied to predict customers’ satisfaction and design new product through 4P marketing mix concept in an actual case in the freezer refrigerator industry. A complete sensitivity analysis is run to assess significance or influence of each input variable on customers’ satisfaction. The superiority of ANFIS is proved by error analysis. The proposed approach would help practitioners within the field of marketing and new product design teams to enhance customers’ satisfaction and set new products’ attributes.