Abstract
Kansei Engineering (KE) is a longstanding method to utilize affective measures for the production of more user-centric product designs. KE focuses on the use of specific words to classify users’ feelings about a product or their desires for its function and feel. With the expansion of KE’s application to service design and in conjunction with computing, designers can expand upon the original KE method to produce results that best satisfy end users’ desires. With the purpose of exploring the areas and nature of KE’s emergence, this study utilizes bibliometric analysis and data mining tools to generate insights on prominent authors, sub-topics, and regions involved in the study of KE. Analyses are shown in the form of descriptive figures exported from software tools used for bibliometric analysis. Insights from these figures and study of prominent KE articles reveal an opportunity for review and reappraisal of KE as a topic. A review of recent literature supports the idea that KE is a growing topic of interest in the field of ergonomics, with an increasing set of applications stretching beyond traditional product design.
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Tillinghast, D.J., Aekanth, S.G. (2023). Systematic Review on the Emergence of Kan-sei Engineering as a Human Factors Method. In: Duffy, V.G., Landry, S.J., Lee, J.D., Stanton, N. (eds) Human-Automation Interaction. Automation, Collaboration, & E-Services, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-031-10784-9_9
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