A weighted ordinal logistic regression for conjoint analysis and kansei engineering

Abstract

Customer needs for emotional satisfaction are increasingly being considered by product and service designers. While several existing methods such as conjoint analysis (CA), Kano model and quality function deployment support the translation of customer requirements into technical specifications, researchers are now working to develop methods aimed at integrating affective aspects into product design. Kansei engineering (KE) is a design philosophy that considers customer perceptions and emotions by adopting a multi-disciplinary approach. CA is a useful tool within a KE project. This article presents a methodology for conducting a KE project in early development phases. This methodology is based on two new procedures. The first one is aimed at calculating attribute importance weights by using respondent choice time in controlled interviews. The second procedure allows the exploitation of such weights in an ordinal logistic regression model for analysing the results of CA experiments. By using the proposed methodology, it is possible to identify product/service attributes able to induce specific emotions and feelings in customers and consequently choose the right development strategy. An application of the method for the design of mobile phones is presented.