The intention of consumer goods is consumer acceptance and preference analysis. The important criteria of this study to find out the product attributes and consumer preferences and acceptance. The crucial to attach the buyer galaxy and the design galaxy are user perceptions of the product. In this study, the authors utilized factor analysis using SPSS 17.0 to develop a construct specifically responsible for assessing consumer preference analysis through a wide-ranging based questionnaire survey. The pattern of influence of input parameters on outputs such as consumer acceptance and preference is difficult to establish, possibly due to presence of some nonlinear relationship between them. Therefore, artificial neural network (ANN) approach is accepted and identify important deficient items. Therefore, ANN approach for consumer preference analysis is presented for identifying and consumer expectation as output affecting product different attributes in the fulfilment of consumer perceptions and finally their preferences. The important parameter of factor analysis between variables while using the training process of ANN to obtain more precise. This model could help the inventors to identify product attributes affecting the consumer preferences, and to better understand the factors that upset user perceptions and the inner interactions between them. To validate the effectiveness of the model, the nonlinear nature of ANN and provides more consistent outcomes of consumer preference analysis.
Volume 12 | Issue 5
Pages: 580-588