When customers are questioned on what they want, a list of needs normally referring to functionality is obtained. Designers and engineers can translate this voice of the customer into technical parameters, so that the product fulfills those needs. However, customers do not usually explain their emotional needs, probably because they are not aware of having them or are unable to tell which they are. Even when those emotional needs are discovered, it is not obvious which technical properties of th...
When customers are questioned on what they want, a list of needs normally referring to functionality is obtained. Designers and engineers can translate this voice of the customer into technical parameters, so that the product fulfills those needs. However, customers do not usually explain their emotional needs, probably because they are not aware of having them or are unable to tell which they are. Even when those emotional needs are discovered, it is not obvious which technical properties of the product will elicit those desired emotions.
Some markets are currently so crowded of similar products in terms of functionality that adding an “emotional touch” can make a difference. How do designers create “emotional products”? They usually rely on their intuition, creativity and experience. But they also use different qualitative and quantitative methods to collect information on how products are perceived and used. Several of these methods can be grouped under the umbrella term “emotional design” or “affective design”. One of the methods is the so-called kansei engineering (KE).
Kansei engineering is a method for incorporating emotions in the product development phase. The main purpose is discovering which technical parameters of a product elicit the chosen emotions. The method was first proposed by Prof. Mitsuo Nagamachi in the 70’s and 80’s, but gained attention in this XXI century, in part due to work by Prof. Simon Schütte at Linköpings Universitet. KE studies are based on self-reporting emotional reactions with questionnaires (usually ratings on Likert or semantic differential scales). A set of different prototypes is shown to participants in the study, and ratings are given on elicited emotions. Each emotion acts as a response in a design of experiments.
There is a large range of statistical tools commonly used in KE studies, mainly multivariate techniques and regression models. Data in KE studies have a great amount of variability, and as building prototypes is costly, there is always the attempt to discover a lot of things (having a lot of factors) but only a few runs in the experiment (probably too few!). All these issues pose interesting statistical challenges; in fact, kansei engineering is a discipline “in need of statistics”.
This seminar will take the form of a workshop, where you will be asked to discuss and work with your colleagues. We will first cover the basic ideas behind kansei engineering studies, and present the model used to conduct them. After several examples, a real (simple) KE study will be prepared by participants in small groups. This small example will be used to discuss some statistical tools useful in KE. For instance, multivariate techniques for summarizing information, and for automatically detecting “crazy” participants, will be covered. As “customers” of KE studies are often designers, a great importance is placed on visual presentation of results. Quantification theory type I (QT1), a special version of regression analysis commonly used in KE, which makes interpretation of results easier when all independent variables are categorical, will also be explained (the ideas behind QT1 are, in fact, useful far beyond KE studies).
When the seminar finishes, you will have a good understanding of what kansei engineering is, and how statistics can contribute to this field. Moreover, you will have learnt some “tricks”, such as QT1, that make statistical output easier to interpret to a broad audience.