Artificial Intelligence in the Fashion and Apparel Industry

Authors

DOI:

https://doi.org/10.14502/tekstilec.67.2024001

Keywords:

AI-driven design, artificial intelligence, fashion industry, virtual try-on, sustainability

Abstract

In recent times, there has been significant interest in incorporating artificial intelligence (AI) in the fashion and apparel industry, as it has the ability to bring about significant transformations across different aspects of the sector. This comprehensive review offers a systematic examination of current AI applications in fashion, and discusses implications and future opportunities. The study investigates AI uses in the sector, with a focus on virtual try-on technology, personalized recommendations, AI-driven design and supply chain optimization. This analysis explores the benefits and constraints of these applications, and is supported by real-world case studies showcasing successful deployments. The review examines how AI influences consumer insights and market trends, and highlights the effectiveness of sentiment analysis and social media monitoring as tools for understanding consumer preferences and the shaping of brand perception. It also emphasizes AI's role in analysing market trends, enabling the identification of emerging fashion trends through AI-driven market research tools. This study provides a glimpse into future possibilities and advancements AI can introduce to fashion, including potential integration with augmented reality (AR), innovative applications in fashion shows and events, and the potential to revolutionize traditional business models. This review consolidates primary findings on the introduction of AI in the fashion and apparel sector, and emphasizes AI's potential to enhance consumer experiences, sustainability practices and market efficiency.

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References

GUO, Z., WONG, W., LEUNG, S., LI, M. Applications of artificial intelligence in the apparel industry: a review. Textile Research Journal, 2011, 81(18), 1871–1892, doi: 10.1177/0040517511411968.

LIANG, Y., LEE, S.H., WORKMAN, J.E. Implementation of artificial intelligence in fashion: are consumers ready? Clothing and Textile Research Journal, 2020, 38(1), 3–18, doi: 10.1177/0887302X19873437.

AU, K.F., CHOI, T.M., YU, Y. Fashion retail forecasting by evolutionary neural networks. International Journal of Production Economics, 2008, 114(2), 615–630, doi: 10.1016/j.ijpe.2007.06.013.

CHEN, H.J., SHUAI, H.H., CHENG, W.H. A survey of artificial intelligence in fashion. IEEE Signal Processing Magazine, 2023, 40(3), 64–73, doi: 10.1109/MSP.2022.3233449.

SAYEM, A.S.M. Digital fashion innovations for the real world and metaverse. International Journal of Fashion Design, Technology and Education, 2022, 15(2), 139–141, doi: 10.1080/17543266.2022.2071139.

RAHMAN, M.S., BAG, S., HOSSAIN, M.A., FATTAH, F.A.M.A., GANI, M.O., RANA, N.P. The new wave of AI-powered luxury brands online shopping experience: the role of digital multisensory cues and customers’ engagement. Journal of Retailing and Consumer Services, 2023, 72, 1–15, doi: 10.1016/j.jretconser.2023.103273.

GU, X., GAO, F., TAN, M., PENG, P. Fashion analysis and understanding with artificial intelligence. Information Processing & Management, 2020, 57(5), 1–15, doi: 10.1016/j.ipm.2020.102276.

PARK, M., IM, H., KIM, D.Y. Feasibility and user experience of virtual reality fashion stores. Fashion & Textiles, 2018, 5(32), 1–17, doi: 10.1186/s40691-018-0149-x.

SÄRMÄKARI, N., VÄNSKÄ, A. ‘Just hit a button!’ – fashion 4.0 designers as cyborgs, experimenting and designing with generative algorithms. International Journal of Fashion Design, Technology and Education, 2022, 15(2), 211–220, doi: 10.1080/17543266.2021.1991005.

BUYUKASLAN, E., BAYTAR, F., KALAOGLU, F. Exploring the factors influencing consumers’ virtual garment fit satisfactions. Research Journal of Textile and Apparel, 2020, 24(4), 375-388, doi: 10.1108/RJTA-03-2020-0029.

BRUBACHER, K., TYLER, D., APEAGYEI, P., VENKATRAMAN, P., BROWNRIDGE, A.M. Evaluation of the accuracy and practicability of predicting compression garment pressure using virtual fit technology. Clothing and Textiles Research Journal, 2023, 41(2), 107–124, doi: 10.1177/0887302X21999314.

SHIN, E., BAYTAR, F. Apparel fit and size concerns and intentions to use virtual try-on: impacts of body satisfaction and images of models’ bodies. Clothing and Textiles Research Journal, 2014, 32(1), 20–33, doi: 10.1177/0887302X13515072.

PARK, H., KIM, S. Do augmented and virtual reality technologies increase consumers’ purchase intentions? The role of cognitive elaboration and shopping goals. Clothing and Textiles Research Journal, 2023, 41(2), 91–106, doi: 10.1177/0887302X21994287.

LEE, Jung Eun. Fast-fashion retailers: types of online-based internationalization. The Research Journal of the Costume Culture, 2019, 27(1), 33–45, doi: 10.29049/rjcc.2019.27.1.033.

PATEL, A., PUROHIT, J., PATEL, S.S. Enhancing the virtual jewelry try-on experience with computer vision. In IEEE Applied Sensing Conference (APSCON), Goa, India, 2024, 1–4, doi: 10.1109/APSCON60364.2024.10465992.

SONG, H.K., ASHDOWN, S.P. Investigation of the validity of 3-D virtual fitting for pants. Clothing and Textiles Research Journal, 2015, 33(4), 314–330, doi: 10.1177/0887302X15592472.

GUAN, C., QIN, S., LONG, Y. Apparel-based deep learning system design for apparel style recommendation. International Journal of Clothing Science and Technology, 2019, 31(3), 376–389, doi: 10.1108/IJCST-02-2018-0019.

LEE, G.H., KIM, S., PARK, C.K. Development of fashion recommendation system using collaborative deep learning. International Journal of Clothing Science and Technology, 2022, 34(5), 732–744, doi: 10.1108/IJCST-11-2021-0172.

BALIM, C., ÖZKAN, K. Diagnosing fashion outfit compatibility with deep learning techniques. Expert Systems with Applications, 2023, 215, 1–13, doi: 10.1016/j.eswa.2022.119305.

SOHN, K., SUNG, C.E., KOO, G., KWON, O. Artificial intelligence in the fashion industry: consumer responses to generative adversarial network (GAN) technology. International Journal of Retail & Distribution Management, 2021, 49(1), 61–80, doi: 10.1108/IJRDM-03-2020-0091.

LEE, H., XU, Y. Influence of motivational orientations on consumers’ adoption of virtual fitting rooms (VFRs): moderating effects of fashion leadership and technology visibility. International Journal of Fashion Design, Technology and Education, 2022, 15(3), 297–307, doi: 10.1080/17543266.2022.2048423.

YANG, E.K., LEE, J.H. Classifying virtual reality-based collaboration environments: practical insights for application in fashion design. International Journal of Fashion Design, Technology and Education, 2021, 14(3), 314–324, doi: 10.1080/17543266.2021.1938701.

WANG, S., QIU, J. A deep neural network model for fashion collocation recommendation using side information in e-commerce. Applied Soft Computing, 2021, 110, 1–10, doi: 10.1016/j.asoc.2021.107753.

SINGH, M., BAJPAI, U., VIJAYRANJAN, V., PRASATH, S. Generation of fashionable clothes using generative adversarial networks: a preliminary feasibility study. International Journal of Clothing Science and Technology, 2020, 32(2), 177–187, doi: 10.1108/IJCST-12-2018-0148.

YU, Z.Y., LUO, T.-J. Research on clothing patterns generation based on multi-scales self-attention improved generative adversarial network. International Journal of Intelligent Computing and Cybernetics, 2021, 14(4), 647–663, doi: 10.1108/IJICC-04-2021-0065.

BHAGAT, R., CHAUHAN, V., BHAGAT, P. Investigating the impact of artificial intelligence on consumer’s purchase intention in e-retailing. Foresight, 2023, 25(2), 249–263, doi: 10.1108/FS-10-2021-0218.

HEINS, C. Artificial intelligence in retail – a systematic literature review. Foresight, 2023, 25(2), 264–286, doi: 10.1108/FS-10-2021-021.

PARK, N., JANG, K., CHO, S., CHOI, J. Use of offensive language in human-artificial intelligence chatbot interaction: the effects of ethical ideology, social competence, and perceived humanlikeness. Computers in Human Behavior, 2021, 121, 1–9, doi: 10.1016/j.chb.2021.106795.

GUPTA, S., MODGIL, S., CHOI, T.M., KUMAR, A., ANTONY, J. Influences of artificial intelligence and blockchain technology on financial resilience of supply chains. International Journal of Production Economics, 2023, 261, 1–16, doi: 10.1016/j.ijpe.2023.108868.

TOORAJIPOUR, R., SOHRABPOUR, R., NAZARPOUR, A., OGHAZI, P., FISCHL, M. Artificial intelligence in supply chain management: a systematic literature review. Journal of Business Research, 2021, 122, 502–517, doi: 10.1016/j.jbusres.2020.09.009.

JAIN, S., GANDHI, A.V. Impact of artificial intelligence on impulse buying behaviour of Indian shoppers in fashion retail outlets. International Journal of Innovation Science, 2021, 13(2), 193–204, doi: 10.1108/IJIS-10-2020-0181.

SHI, M., CHUSSID, C., YANG, P., JIA, M., LEWIS, Van Dyk, CAO, W. The exploration of artificial intelligence application in fashion trend forecasting. Textile Research Journal, 2021, 91(19-20), 2357–2386, doi: 10.1177/00405175211006212.

SANDERS, N.R., BOONE, T., GANESHAN, R., WOOD, J.D. Sustainable supply chains in the age of AI and digitization: research challenges and opportunities. Journal of Business Logistics, 2019, 40(3), 229–240, doi: 10.1111/jbl.12224.

DOMINA, T., LEE, S.E., MacGILLIVRAY, M. Understanding factors affecting consumer intention to shop in a virtual world. Journal of Retailing and Consumer Services, 2012, 19(6), 613–620, doi: 10.1016/j.jretconser.2012.08.001.

SONG, S.Y., KIM, Y.K. Factors influencing consumers’ intention to adopt fashion robot advisors: psychological network analysis. Clothing and Textiles Research Journal, 2022, 40(1), 3–18, doi: 10.1177/0887302X20941261.

PARK, E.J., KIM, E.Y., FORNEY, J.C. A structural model of fashion-oriented impulse buying behavior. Journal of Fashion Marketing and Management: an International Journal, 2006, 10(4), 433–446, doi: 10.1108/13612020610701965.

KIM, J., FORSYTHE, S. Hedonic usage of product virtualization technologies in online apparel shopping. International Journal of Retail & Distribution Management, 2007, 35(6), 502–514, doi: 10.1108/09590550710750368.

TRAN, A.D., PALLANT, J.I., JOHNSON, L.W. Exploring the impact of chatbots on consumer sentiment and expectations in retail. Journal of Retailing and Consumer Services, 2021, 63, 1–10, doi: 10.1016/j.jretconser.2021.102718.

LING, X., ZHENYU, J., HONG, Y., PAN, Z. Development of novel fashion design knowledge base by integrating conflict rule processing mechanism and its application in personalized fashion recommendations. Textile Research Journal, 2023, 93(5-6), 1069–1089, doi: 10.1177/00405175221129868.

HU, Z-H., LI, X., WEI, C., ZHOU, H-L. Examining collaborative filtering algorithms for clothing recommendation in e-commerce. Textile Research Journal, 2019, 89(14), 2821–2835, doi: 10.1177/0040517518801200.

KIM, H.Y., LEE, J.Y., MUN, J., JOHNSON, K. Consumer adoption of smart in-store technology: assessing the predictive value of attitude versus beliefs in the technology acceptance model. International Journal of Fashion Design. Technology and Education, 2017, 10(1), 26–36, doi: 10.1080/17543266.2016.1177737.

PANTANO, E., GIGLIO, S., DENNIS, C. Making sense of consumers’ tweets: sentiment outcomes for fast fashion retailers through Big Data analytics. International Journal of Retail & Distribution Management, 2019, 47(9), 915–927, doi: 10.1108/IJRDM-07-2018-0127.

SHIN, E., BAYTAR, F. Apparel fit and size concerns and intentions to use virtual try-on: impacts of body satisfaction and images of models’ bodies. Clothing and Textiles Research Journal, 2014, 32(1), 20–33, doi: 10.1177/0887302X13515072.

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Published

2024-09-19

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Scientific article

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How to Cite

Singh, S. (2024). Artificial Intelligence in the Fashion and Apparel Industry. Tekstilec, 67(3), 225-240. https://doi.org/10.14502/tekstilec.67.2024001