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Kansei for the Digital Era
Linköping University, Department of Management and Engineering, Product Realisation. Linköping University, Faculty of Science & Engineering.
Univ Teknol MARA UiTM, Malaysia.
Univ Politecn Cataluna, Spain.
Hiroshima Int Univ, Japan.
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2024 (English)In: INTERNATIONAL JOURNAL OF AFFECTIVE ENGINEERING, ISSN 2187-5413, Vol. 23, no 1, p. 1-18Article in journal (Refereed) Published
Abstract [en]

For over 40 years, Kansei-based research and development have been conducted in Japan and other East Asian countries and these decades of research have influenced Kansei interpretation. New methods and applications, including virtual reality and artificial intelligence, have emerged since the millennium, as the Kansei concept has spread throughout Europe and the rest of the world. This paper reviews past literature and industrial experience, offering a comprehensive understanding of Kansei, the underlying philosophy, and the methodology of Kansei Engineering from the approach of psychology and physiology, both qualitatively and quantitatively. The breadth of Kansei is described by examples, emerging from both industry and academia. Additionally, thematic mapping of the state-of-the-art as well as an outlook are derived from feedback obtained from structured interview of thirty-five of the most distinguished researchers in Kansei. The mapping provides insights into current trends and future directions. Kansei is unique because it includes the consideration of emotion in the design of products and services. The paper aims at becoming a reference for researchers, practitioners, and stakeholders across borders and cultures, looking for holistic perspectives on Kansei, Kansei Engineering, and implementation methods. The novelty of the paper resides in the unification of authors amongst pioneers from different parts of the world, spanning across diversified academic backgrounds, knowledge areas and industries.

Place, publisher, year, edition, pages
JAPAN SOC KANSEI ENGINEERING , 2024. Vol. 23, no 1, p. 1-18
Keywords [en]
Affective design; Artificial intelligence; Data analytics; Product innovation
National Category
Other Mechanical Engineering
Identifiers
URN: urn:nbn:se:liu:diva-199694DOI: 10.5057/ijae.IJAE-D-23-00003ISI: 001112381600001OAI: oai:DiVA.org:liu-199694DiVA, id: diva2:1821114
Available from: 2023-12-19 Created: 2023-12-19 Last updated: 2024-11-06

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
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  • Other locale
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Output format
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