Comparison of Two Quantitative Analysis Techniques to Predict the Evaluation of Product Form Design

Hung-Yuan Chen,Ting-Chun Tung,Yu-Ming Chang

doi:10.1155/2014/989382

Abstract

Consumer satisfaction with a product’s form plays an essential role in determining the likelihood of its commercial success. A consumer perception-centered design approach is proposed in this study to aid product designers with incorporating consumers’ perceptions of product forms in the design process. The consumer perception-centered design approach uses the linear modeling technique (multiple linear regression) and the nonlinear modeling technique (neural network) to determine the satisfying product form design for matching a given product image. A series of experimental evaluations are conducted to collect evaluation results for examining the relationship between the automobile profile features and the consumers’ perceptions of the automobile image. The result of predictive performance comparison shows that both the nonlinear neural network modeling technique and the multiple linear regression technique are comparably good for predicting the consumers’ likely response to a particular automobile profile since the predictive performance difference between the two modeling techniques is very slight in this study. Although this study has chosen a 2D automobile profile for illustration purposes, the concept of the proposed approach is expansively applicable to 3D automotive form design or other consumer product forms.

Highlights

Consumers interact with a huge number of diverse products during the course of their daily lives and subconsciously develop sophisticated product evaluation skills
This study has chosen a 2D automobile profile for illustration purposes, the concept of the proposed approach is expansively applicable to 3D automotive form design or other consumer product forms
To avoid the subjective judgments in the design process and to objectively relate consumers’ psychological satisfaction with a product to its form features, many systematic design approaches have been proposed for modeling the correlation between the form features of a product and the consumers’ perception of the product image [1,2,3,4]

Summary

Introduction

Consumers interact with a huge number of diverse products during the course of their daily lives and subconsciously develop sophisticated product evaluation skills. A consumer’s purchase decision is based on a product’s functionality and fitness for use, and on the psychological response induced by its physical appearance This phenomenon is apparent in the case of mature consumer products such as automobiles, mobile phone, tableware, and computer accessories. To avoid the subjective judgments in the design process and to objectively relate consumers’ psychological satisfaction with a product to its form features, many systematic design approaches have been proposed for modeling the correlation between the form features of a product and the consumers’ perception of the product image [1,2,3,4] Amongst such techniques, Kansei Engineering (KE) is a fundamental consumer-oriented systematic design approach in which the consumers’ feelings or product image perceptions are expressed using suitable image descriptors. KE has emerged as one of the most powerful techniques for taking account of the correlation between a product’s attributes and the induced product image during the design process [5]

Methods

Results

Conclusion