Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration
Core user demands of wardrobe furniture design are becoming increasingly complex. Traditional design methods fail to systematically analyze the interrelationships among these multidimensional factors. This study integrated web text mining, the Decision-Making Trial and Evaluation Laboratory (DEMATEL...
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North Carolina State University
2025-06-01
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| Series: | BioResources |
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| Online Access: | https://ojs.bioresources.com/index.php/BRJ/article/view/24663 |
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| author | Xinlian Li Peijun Jia Jinyang Xu |
| author_facet | Xinlian Li Peijun Jia Jinyang Xu |
| author_sort | Xinlian Li |
| collection | DOAJ |
| description | Core user demands of wardrobe furniture design are becoming increasingly complex. Traditional design methods fail to systematically analyze the interrelationships among these multidimensional factors. This study integrated web text mining, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, and the Analytic Network Process (ANP) to construct a causal network model for wardrobe design, and further optimized design proposals through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By applying Python technology, user evaluation data were extracted from mainstream e-commerce platforms, with high-frequency user demand keywords being identified and categorized into four key dimensions. DEMATEL was employed to quantify the causal intensity and centrality of the identified factors; ANP was subsequently utilized to construct a network hierarchy, revealing the feedback mechanisms between functional modules and user experience. Finally, TOPSIS was applied to rank three design proposals, among which Option 3—featuring flexible space partitioning, auto-sensing lighting, and anti-tip design—was selected as the optimal solution. The findings demonstrate that integrating text mining with the DEMATEL-ANP-TOPSIS framework can effectively identify the prioritization of user needs, thereby providing scientific decision support for furniture design. |
| format | Article |
| id | doaj-art-b5e193ac80ef4ac8a27567f4a1c17deb |
| institution | DOAJ |
| issn | 1930-2126 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | North Carolina State University |
| record_format | Article |
| series | BioResources |
| spelling | doaj-art-b5e193ac80ef4ac8a27567f4a1c17deb2025-08-20T03:02:26ZengNorth Carolina State UniversityBioResources1930-21262025-06-01203669267122977Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP IntegrationXinlian Li0Peijun Jia1Jinyang Xu2International Institute of Creative Design, Shanghai University of Engineering Science, Shanghai, 200000, ChinaXiamen Academy Of Arts and Design, Fuzhou University, Xiamen, Fujian, 361021, ChiSchool of Arts, Southeast University, Nanjing, Jiangsu, 214135, ChinaCore user demands of wardrobe furniture design are becoming increasingly complex. Traditional design methods fail to systematically analyze the interrelationships among these multidimensional factors. This study integrated web text mining, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, and the Analytic Network Process (ANP) to construct a causal network model for wardrobe design, and further optimized design proposals through the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). By applying Python technology, user evaluation data were extracted from mainstream e-commerce platforms, with high-frequency user demand keywords being identified and categorized into four key dimensions. DEMATEL was employed to quantify the causal intensity and centrality of the identified factors; ANP was subsequently utilized to construct a network hierarchy, revealing the feedback mechanisms between functional modules and user experience. Finally, TOPSIS was applied to rank three design proposals, among which Option 3—featuring flexible space partitioning, auto-sensing lighting, and anti-tip design—was selected as the optimal solution. The findings demonstrate that integrating text mining with the DEMATEL-ANP-TOPSIS framework can effectively identify the prioritization of user needs, thereby providing scientific decision support for furniture design.https://ojs.bioresources.com/index.php/BRJ/article/view/24663dematel-anptopsiswardrobe designweb text minings |
| spellingShingle | Xinlian Li Peijun Jia Jinyang Xu Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration BioResources dematel-anp topsis wardrobe design web text minings |
| title | Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration |
| title_full | Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration |
| title_fullStr | Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration |
| title_full_unstemmed | Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration |
| title_short | Demystifying User Needs in Wardrobe Furniture Design: A Network Analysis via Text Mining and DEMATEL-ANP Integration |
| title_sort | demystifying user needs in wardrobe furniture design a network analysis via text mining and dematel anp integration |
| topic | dematel-anp topsis wardrobe design web text minings |
| url | https://ojs.bioresources.com/index.php/BRJ/article/view/24663 |
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