Affective Meaning: The Kansei Engineering Approach

Ishihara, Shigekazu; Nagamachi, Mitsuo; Schütte, Simon; Jörgen, Eklund

doi:10.1016/b978-008045089-6.50023-x

Cited by 35 publications

(15 citation statements)

References 7 publications

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“…Deeply rooted in the Japanese culture, direct translation of Kansei to other language is rather difficult. Having various interpretations by different literature, Kansei is generally referred to sensitivity, sensibility, feeling and emotion (Nagamachi, 1992;Ishihara et al, 1993;Harada, 1998;Yoshikawa, 2000;Schutte, et. al.…”

Section: Literature Reviewmentioning

confidence: 99%

Design of Educational Game Tools Recognizing Body Members Using The Kansei Engineering Method

Ramadhani

Kusumanto

Nofirza

2022

JAETS

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Education is very important in realizing a strong and advanced nation. So, the process must be carried out early. Therefore, Early Childhood Education is the main foundation for the development of a nation's generation. While the standards of Early Childhood Education are not evenly distributed, in fact, there are still many that are lacking, especially in the learning media of Educational Game Tools/Alat Pembelajaran Edukatif (APE). In this research, an Educational Learning Tool will be made in the form of a puzzle using the Kansei words and Kensei engineering methods. The results of this study indicate that the child's response is very good and very helpful in the learning process. The combination of the Kansei words and Kansei engineering methods produces a unique educational game tool that makes children more interested in participating in learning

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Section: Literature Reviewmentioning

confidence: 99%

Design of Educational Game Tools Recognizing Body Members Using The Kansei Engineering Method

Ramadhani

Kusumanto

Nofirza

2022

JAETS

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“…To make Kansei Engineering applicable to European culture, Schütte proposed a modification strategy to reduce the complexity [42,43,44,45]. Besides, Schütte also discussed the selection of samples [46] and visualized Kansei Engineering steps [47].…”

Section: Kansei Engineeringmentioning

confidence: 99%

Big Data driven Product Design: A Survey

Quan¹,

Li²,

Zeng³

et al. 2021

Preprint

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With the improvement of living standards, user requirements of modern products are becoming increasingly more diversified and personalized. Traditional product design methods can no longer satisfy the market needs due to their strong subjectivity, small survey scope, poor real-time data, and lack of visual display, which calls for the development of big data driven product design methodology. Big data in the product lifecycle contains valuable information for guiding product design, such as customer preferences, market demands, product evaluation, and visual display: online product reviews reflect customer evaluations and requirements; product images contain information of shape,color, and texture which can inspire designers to get initial design schemes more quickly or even directly generate new product images. How to efficiently collect product design related data and exploit them effectively during the whole product design process is thus critical to modern product design. This paper aims to conduct a comprehensive survey on big data driven product design. It will help researchers and practitioners to comprehend the latest development of relevant studies and applications centered on how big data can be processed, analyzed, and exploited in aiding product design. We first introduce several representative traditional product design methods and highlight their limitations. Then we discuss current and potential applications of textual data, image data, audio data, and video data in product design cycles. Finally, major deficiencies of existing data driven product design studies and future research directions are summarized. We believe that this study can draw increasing attention to modern data driven product design.Keywords product design • big data • Kansei engineering • QFD • generative design * Correspondence.

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“…These results also reveal the importance of using a quantitative model when investigating the emotional user experience. Qualitative approaches, such as the Kensei Engineering approach (e.g., Guo et al, 2014;Ishihara et al, 2008), have been used within the product development cycle. Despite being useful to collect users' feedback, they are usually time consuming and are not allowing precise comparisons with similar products.…”

Section: Theoretical Implications and Managerial Implicationsmentioning

confidence: 99%

Emotional user experience of innovative humancomputer interactions: A multi-component approach

Dupré¹,

Sinclair²

2021

j. cust. behav.

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Emotions are a relevant indicator of users’ acceptance of technologies. Despite users’ subjective feeling being traditionally examined with categorical labels, the Component Process Model suggests that the cognitive and motivational component can also be examined in User Experience studies. This study focuses on emotions using innovative non-tactile Human-Computer Interaction (HCI) to perform different tasks. Results revealed that cognitive and motivational components of emotions are decisive to confirm or to infirm the self-reported subjective feeling. More precisely, non-tactile controllers triggered significantly higher cognitive appraisals than the tactile controller. These non-tactile controllers also trigger significantly higher readiness to approach and to avoid than the tactile controller, depending on the type of controller used, and on its application. The innovativeness of the controller does not necessarily involve positive emotions and needs to be situated in a specific context of use. This analysis show how User Experience testing for product development could gain in investigating the additional components of users’ emotional experience.

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Affective Meaning: The Kansei Engineering Approach

Cited by 35 publications

References 7 publications

Design of Educational Game Tools Recognizing Body Members Using The Kansei Engineering Method

Design of Educational Game Tools Recognizing Body Members Using The Kansei Engineering Method

Big Data driven Product Design: A Survey

Emotional user experience of innovative humancomputer interactions: A multi-component approach

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