Applying Eye-Tracking in Kansei Engineering Method for Design Evaluations in Product Development

Markus KÖHLER, Björn FALK, Robert SCHMITT
2015 International Journal of Affective Engineering  
Customers base their emotional quality judgments on their product perception. Therefore, the aim of customer-centric product development should be to satisfy needs and requirements of the specific target group and to develop products that attract user attention and evoke positive emotions. Since visual impressions are crucial for the evaluation of the Perceived Product Quality, the ascertainment of data about visual impressions should be of high importance. To use Perceived Quality data of
more » ... l impression there is a need to investigate how latent needs and requirements are influencing the conscious and unconscious visual perception. This paper presents a methodology that extends the traditional Kansei Engineering method for design evaluations for gathering customers' requirements and evaluations (e.g. questionnaires) by using Eye-Tracking. The elicitation of visual impressions with Eye-Tracking means to derive objective data of customers' product perception and evaluation. The methodology uses comparisons of design alternatives on a general as well as on an even more detailed level of product perception based on a structured approach. The paper also presents precisely a study design for applying the developed methodology and shows valid results of a conducted Eye-Tracking study by using descriptive (e.g. Pareto-analysis) and statistical analysis procedures (e.g. repeated-measures ANOVA). In conclusion, knowledge about and interpretations of the customer product evaluation and about latent and implicit requirements can be derived from the parameters ascertained with Eye-Tracking (e.g. fixations). By gradually integrating the methodology into the product development process, it can be applied by product designers for evaluating product design concepts from the customer's perspective.
doi:10.5057/ijae.ijae-d-15-00016 fatcat:dj67eriqbrcz3hidvodq6p5v6e