Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content
Consumers tend to purchase and use furniture products that fulfill their emotional needs. However, existing bamboo furniture design departments lack a systematic and scientific approach to morphological design, and their innovation capabilities remain insufficient. This study proposes a generative d...
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| Language: | English |
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North Carolina State University
2025-08-01
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| Series: | BioResources |
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| Online Access: | https://ojs.bioresources.com/index.php/BRJ/article/view/24842 |
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| author | Jing Liu Honghe Gao Olga Yezhova |
| author_facet | Jing Liu Honghe Gao Olga Yezhova |
| author_sort | Jing Liu |
| collection | DOAJ |
| description | Consumers tend to purchase and use furniture products that fulfill their emotional needs. However, existing bamboo furniture design departments lack a systematic and scientific approach to morphological design, and their innovation capabilities remain insufficient. This study proposes a generative design method for bamboo furniture that integrates Game Theory (GT) with AI-Generated Content (AIGC), grounded in Kansei Engineering. This approach aims to assist design departments in developing creative products that align with consumers’ emotional needs, thereby fostering sustainable consumption and advancing the bamboo furniture industry. First, consumer-driven Kansei words were collected and categorized. Then, subjective and objective weight values of consumer requirements were calculated using Grey Relational Analysis (GRA) and entropy, respectively. Based on GT, a comprehensive weight value was determined to accurately identify key consumer requirements. Next, Diffusion Models in AIGC technology were employed to generate new furniture images, followed by morphological deconstruction. Finally, a House of Quality based on Fuzzy Quality Function Deployment was constructed to establish the mapping relationship between key consumer requirements and new morphological elements, determining the optimal furniture design parameters. The proposed method integrates the strengths of both subjective and objective approaches, enhancing the accuracy and scientific rigor of design decision-making. |
| format | Article |
| id | doaj-art-a5bf0f7f66ed465b8eb34d678fc99c58 |
| institution | Kabale University |
| issn | 1930-2126 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | North Carolina State University |
| record_format | Article |
| series | BioResources |
| spelling | doaj-art-a5bf0f7f66ed465b8eb34d678fc99c582025-08-20T17:36:16ZengNorth Carolina State UniversityBioResources1930-21262025-08-01204861186313195Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated ContentJing Liu0Honghe Gao1Olga Yezhova2Liaoning Petrochemical University, Dandong Road West Section, 1, 113001 Fushun, ChinaLiaoning Petrochemical University, Dandong Road West Section, 1, 113001 Fushun, China; Kyiv National University of Technologies and Design, Kyiv Povitroflotskyi Prospekt, 31, 03037 Kyiv, UkraineKyiv National University of Technologies and Design, Kyiv Povitroflotskyi Prospekt, 31, 03037 Kyiv, UkraineConsumers tend to purchase and use furniture products that fulfill their emotional needs. However, existing bamboo furniture design departments lack a systematic and scientific approach to morphological design, and their innovation capabilities remain insufficient. This study proposes a generative design method for bamboo furniture that integrates Game Theory (GT) with AI-Generated Content (AIGC), grounded in Kansei Engineering. This approach aims to assist design departments in developing creative products that align with consumers’ emotional needs, thereby fostering sustainable consumption and advancing the bamboo furniture industry. First, consumer-driven Kansei words were collected and categorized. Then, subjective and objective weight values of consumer requirements were calculated using Grey Relational Analysis (GRA) and entropy, respectively. Based on GT, a comprehensive weight value was determined to accurately identify key consumer requirements. Next, Diffusion Models in AIGC technology were employed to generate new furniture images, followed by morphological deconstruction. Finally, a House of Quality based on Fuzzy Quality Function Deployment was constructed to establish the mapping relationship between key consumer requirements and new morphological elements, determining the optimal furniture design parameters. The proposed method integrates the strengths of both subjective and objective approaches, enhancing the accuracy and scientific rigor of design decision-making.https://ojs.bioresources.com/index.php/BRJ/article/view/24842ai-generated contentgenerative designbamboo furnituregame theorydiffusion modelfuzzy quality function deployment |
| spellingShingle | Jing Liu Honghe Gao Olga Yezhova Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content BioResources ai-generated content generative design bamboo furniture game theory diffusion model fuzzy quality function deployment |
| title | Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content |
| title_full | Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content |
| title_fullStr | Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content |
| title_full_unstemmed | Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content |
| title_short | Generative Design of Bamboo Furniture Combining Game Theory and AI-Generated Content |
| title_sort | generative design of bamboo furniture combining game theory and ai generated content |
| topic | ai-generated content generative design bamboo furniture game theory diffusion model fuzzy quality function deployment |
| url | https://ojs.bioresources.com/index.php/BRJ/article/view/24842 |
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