Product Aesthetic Design: A Machine Learning Augmentation
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DOI: 10.1287/mksc.2022.1429
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Cited by:
- Yu, Yugang & Wang, Bo & Zheng, Shengming, 2024. "Data-driven product design and assortment optimization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 182(C).
- Hui Li & Jian Ni & Fangzhu Yang, 2024. "Product Design Using Generative Adversarial Network: Incorporating Consumer Preference and External Data," Papers 2405.15929, arXiv.org, revised May 2025.
- Stefan Stremersch & Elke Cabooter & Ivan Guitart & Nuno Camacho, 2025. "Customer insights for innovation : A framework and research agenda for marketing," Post-Print hal-04731671, HAL.
- Stefan Stremersch & Elke Cabooter & Ivan A. Guitart & Nuno Camacho, 2025. "Customer insights for innovation: A framework and research agenda for marketing," Journal of the Academy of Marketing Science, Springer, vol. 53(1), pages 29-51, January.
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Keywords
aesthetics; generative adversarial networks; generating new products; machine learning; prelaunch forecasting; product development; variational autoencoders;All these keywords.
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