Statistics supporting the design process via Kansei Engineering

摘要

Manufacturers have tried many routes to understanding consumer preferences so that they can incorporate them into their designs. In the competitive market place, it is increasingly important to look beyond the obvious and to seek more subtle indications of what product designs will be popular. When asked to describe their requirements from a product, consumers will frequently include a mixture of functional features and descriptions relating to how the design appeals to them on a more subjective emotional level (for example, must look fresh, be comforting, sound fast, must feel dependable). A methodology which is new in Europe but well established in the Far East is being investigated in a European 5th Framework project called Kensys. Kansei Engineering is a technique aimed at translating subjective requirements into product design features and thereby incorporating consumer emotion into the product design process. The Kansei method involves extensive examination of the market, discussions with designers, customer surveys and data analysis. Techniques such as factor analysis and statistical modelling are used to extract underlying traits and make predictions. Issues of selection of a representative product sample, sample size when sampling the customer base and decisions on categorising some independent variables need to be considered. This paper outlines the methodology and illustrates it using the results of a Kansei Engineering project looking at the design of men's everyday footwear.