A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design
Biology provides a rich and novel source of inspiration for product design. An increasing number of industrial designers are gaining inspiration from nature, producing creative products by extracting, classifying, and reconstructing biological features. However, the current process of gaining biolog...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-11-01
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| Series: | Symmetry |
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| Online Access: | https://www.mdpi.com/2073-8994/12/11/1860 |
| _version_ | 1797548148356284416 |
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| author | Shijian Luo Yufei Zhang Jie Zhang Junheng Xu |
| author_facet | Shijian Luo Yufei Zhang Jie Zhang Junheng Xu |
| author_sort | Shijian Luo |
| collection | DOAJ |
| description | Biology provides a rich and novel source of inspiration for product design. An increasing number of industrial designers are gaining inspiration from nature, producing creative products by extracting, classifying, and reconstructing biological features. However, the current process of gaining biological inspiration is still limited by the prior knowledge and experience of designers, so it is necessary to investigate the designer’s perception of biological features. Herein, we investigate designer perceptions of bionic object features based on Kansei engineering, achieving a highly comprehensive structured expression of biological features forming five dimensions—Overall Feeling, Ability and Trait, Color and Texture, Apparent Tactile Sensation, and Structural Features—using factor analysis. Further, producing creative design solutions with a biologically inspired design (BID) has a risk of failing to meet user preferences and market needs. A user preference prediction support tool may address this bottleneck. We examine user preference by questionnaire and explore its association with the perceptual evaluation of designers, obtaining a user preference prediction model by conducting multiple linear regression analysis. This provides a statistical model for identifying the relative weighting of the perception dimensions of each designer in the user preference for an animal, giving the degree of contribution to the user preference. The experiment results show that the dimension “Overall Feeling” of the designer perception is positively correlated with the “like” level of the user preference and negatively correlated with the “dislike” level of the user preference, indicating that this prediction model bridges the gap caused by the asymmetry between designers and users by matching the designer perception and user preference. To a certain extent, this research solves the problems associated with the cognitive limitations of designers and the differences between designers and users, facilitating the use of biological features in product design and thereby enhancing the market importance of BID schemes. |
| first_indexed | 2024-03-10T14:55:22Z |
| format | Article |
| id | doaj.art-e25a98759d4649fd8b07feaaaf7e15bd |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-03-10T14:55:22Z |
| publishDate | 2020-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-e25a98759d4649fd8b07feaaaf7e15bd2023-11-20T20:41:24ZengMDPI AGSymmetry2073-89942020-11-011211186010.3390/sym12111860A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired DesignShijian Luo0Yufei Zhang1Jie Zhang2Junheng Xu3Department of Industrial Design, Zhejiang University, Hangzhou 310027, ChinaDepartment of Industrial Design, Zhejiang University, Hangzhou 310027, ChinaSchool of Design, The Hong Kong Polytechnic University, Hong Kong, SARDepartment of Industrial Design, Zhejiang University, Hangzhou 310027, ChinaBiology provides a rich and novel source of inspiration for product design. An increasing number of industrial designers are gaining inspiration from nature, producing creative products by extracting, classifying, and reconstructing biological features. However, the current process of gaining biological inspiration is still limited by the prior knowledge and experience of designers, so it is necessary to investigate the designer’s perception of biological features. Herein, we investigate designer perceptions of bionic object features based on Kansei engineering, achieving a highly comprehensive structured expression of biological features forming five dimensions—Overall Feeling, Ability and Trait, Color and Texture, Apparent Tactile Sensation, and Structural Features—using factor analysis. Further, producing creative design solutions with a biologically inspired design (BID) has a risk of failing to meet user preferences and market needs. A user preference prediction support tool may address this bottleneck. We examine user preference by questionnaire and explore its association with the perceptual evaluation of designers, obtaining a user preference prediction model by conducting multiple linear regression analysis. This provides a statistical model for identifying the relative weighting of the perception dimensions of each designer in the user preference for an animal, giving the degree of contribution to the user preference. The experiment results show that the dimension “Overall Feeling” of the designer perception is positively correlated with the “like” level of the user preference and negatively correlated with the “dislike” level of the user preference, indicating that this prediction model bridges the gap caused by the asymmetry between designers and users by matching the designer perception and user preference. To a certain extent, this research solves the problems associated with the cognitive limitations of designers and the differences between designers and users, facilitating the use of biological features in product design and thereby enhancing the market importance of BID schemes.https://www.mdpi.com/2073-8994/12/11/1860biologically inspired designdesigner perceptionuser preferenceKansei engineering |
| spellingShingle | Shijian Luo Yufei Zhang Jie Zhang Junheng Xu A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design Symmetry biologically inspired design designer perception user preference Kansei engineering |
| title | A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design |
| title_full | A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design |
| title_fullStr | A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design |
| title_full_unstemmed | A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design |
| title_short | A User Biology Preference Prediction Model Based on the Perceptual Evaluations of Designers for Biologically Inspired Design |
| title_sort | user biology preference prediction model based on the perceptual evaluations of designers for biologically inspired design |
| topic | biologically inspired design designer perception user preference Kansei engineering |
| url | https://www.mdpi.com/2073-8994/12/11/1860 |
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