Abstract
Having an accurate understanding of the individual’s Kansei needs and afterwards designing products that match these needs are particularly important in the era of mass personalisation. Although customers’ Kansei needs have been addressed by Kansei engineering, difficulties remain in handling the differences of individual Kansei. In this paper, individual Kansei variance is considered to transform the Kansei words into multisensory design elements, to help designers better understand the individual's Kansei needs. First, a fuzzy cognitive model is proposed to identify the individual Kansei differences in Kansei words by taking customers’ characteristics and purchasing motives into consideration. Second, a fuzzy cognitive model-based mapping method is proposed to interpret Kansei words into multisensory design elements. The method incorporates a fuzzy clustering method and basic-emotion systems to identify Kansei variance and to determine design elements’ membership of Kansei words dynamically. Finally, the prototype application of the proposed method on a compact SUV is illustrated. The results suggest that individual differences in Kansei terms do exist among customers in the same market segment, and the proposed method has good feasibility and practicability in handling individual Kansei differences in emotional design. Those Kansei dimensions that are more prominent in individual Kansei variance are highly recommended for further digging, which would benefit carrying out personalised customisation and differentiated design.
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Acknowledgements
We are grateful to the reviewers and the editors for their constructive suggestions and valuable comments. Appreciation is also given to Dr Lin Li and Xu Na for their assistance in preparing the experimental materials.
Funding
This work was supported by the Natural Science Foundation of Hubei province [No. 2019CFB542] and the National Natural Science Foundation of China [Nos. 52075292, 51605255].
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Dong, Y., Zhu, R., Peng, W. et al. A fuzzy mapping method for Kansei needs interpretation considering the individual Kansei variance. Res Eng Design 32, 175–187 (2021). https://doi.org/10.1007/s00163-021-00359-8
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DOI: https://doi.org/10.1007/s00163-021-00359-8