본문 바로가기
KERD
논문KCI 등재

온라인 패션 리테일링의 사이즈 추천 기술 동향

Trends of Size Recommendation Technology in Online Fashion Retailing

2

조회

0

다운로드

5

인용

0

참고문헌

키워드

주제분류의상

초록

As the sales of the entire fashion industry are declining due to the Covid-19 pandemic fashion retailers introduce retailing technologies to enhance the shopping experience online. The Size Recommendation Technology(SRT) is one of the retailing technologies to support customers by recommending customers the right size by using data analysis. This study classifies the size recommendation technologies according to data types and finds the implications for online fashion retailers. 5 types of size recommendation technologies are as follows. First the size recommendation technology with virtual try-on using customer body size data, this model is meaningful as it helps customers imagine the fit and size of the product by using an avatar made with the customer's body shape. Second the recommendation technology with robotics using body type, this model helps customers to imagine how the product will be worn through various body types. Third size recommendation technology using customers’ detailed body size data, this model is meaningful in that it develops an app that can measure the detailed body size of consumers to increase the sense of reality. Fourth size recommendation technology using garments dimensions this model extends the scope of usage data beyond matching body size and product size. Lastly size recommendation technology through the conversion of consumers' body size and purchasing history this model uses previous purchase history to achieve a subjective fit of fashion items that previous models could not. This study suggests to the online retailers based on research as follows. First smooth interaction between the program and customers is necessary to enhance the online shopping experience. Second simple operation is essential for customers to complete their purchasing journey without forgetting their original purpose. Third it is necessary to develop new data hat describes purchasing habits and customer situations. SRT will be a stepping stone to improve and commercialize personalization services by helping online consumers to purchase the right size without experiencing the product in the future.

Abstract

As the sales of the entire fashion industry are declining due to the Covid-19 pandemic fashion retailers introduce retailing technologies to enhance the shopping experience online. The Size Recommendation Technology(SRT) is one of the retailing technologies to support customers by recommending customers the right size by using data analysis. This study classifies the size recommendation technologies according to data types and finds the implications for online fashion retailers. 5 types of size recommendation technologies are as follows. First the size recommendation technology with virtual try-on using customer body size data, this model is meaningful as it helps customers imagine the fit and size of the product by using an avatar made with the customer's body shape. Second the recommendation technology with robotics using body type, this model helps customers to imagine how the product will be worn through various body types. Third size recommendation technology using customers’ detailed body size data, this model is meaningful in that it develops an app that can measure the detailed body size of consumers to increase the sense of reality. Fourth size recommendation technology using garments dimensions this model extends the scope of usage data beyond matching body size and product size. Lastly size recommendation technology through the conversion of consumers' body size and purchasing history this model uses previous purchase history to achieve a subjective fit of fashion items that previous models could not. This study suggests to the online retailers based on research as follows. First smooth interaction between the program and customers is necessary to enhance the online shopping experience. Second simple operation is essential for customers to complete their purchasing journey without forgetting their original purpose. Third it is necessary to develop new data hat describes purchasing habits and customer situations. SRT will be a stepping stone to improve and commercialize personalization services by helping online consumers to purchase the right size without experiencing the product in the future.

참고문헌 (33)

  1. Ha, S., "Online apparel retailing:Roles of e-shopping quality and experiential e-shopping motives", Journal of Service Management, 23(2), pp.197~215 (2012)[DOI]
  2. "1월 온라인쇼핑 15조 '역대 2위'…모바일비중 첫 70%대" (2021)[URL]
  3. "Amazon rolls out a new AR shopping feature for viewing multiple items at once" (2020)[URL]
  4. "Chane’s new lipscanner technology is proof that virtual reality beauty testing is here to stay" (2021)[URL]
  5. Hsiu-Ju Hsu, "Clothing Evaluative Criteria: A Cross-National Comparison of Taiwanese and United States Consumers", Clothing and Textiles Research Journal, 20(4), pp.246~252 (2002), SAGE Publications[DOI]
  6. Kim, J., "Effects of level of internet retailer's service quality on perceived apparel quality, perceived service quality, perceived value, satisfaction, and behavioral intentions toward an internet retailer", Clothing and Textiles Research Journal, 28(1), pp.56~73 (2010)
  7. 나윤규, "인터넷 쇼핑에서의 지각된 위험과 신뢰가 지각된 유용성, 태도 및 패션상품 구매의도에미치는 영향", 한국의류학회지, 32(5), pp.834~845 (2008), 한국의류학회
  8. Hanna Lee, "Technology visibility and consumer adoption of virtual fitting rooms (VFRs): a cross-cultural comparison of Chinese and Korean consumers", Journal of Fashion Marketing and Management: An International Journal, 24(2), pp.175~194 (2020), Emerald[DOI]
  9. "2018 Consumer returns in the retail industry"[URL]
  10. Almousa, M., "The relationship between experience and demographic variables on concern with apparel fit in online context", International Business Research, 13(1), pp.11~17 (2020)[DOI]
  11. Rosa, J. A., "Keeping the body in mind : The influence of body esteem and body boundary aberration on consumer beliefs and purchase intentions", Journal of Consumer Psychology, 16(1), pp.79~91 (2003)[DOI]
  12. Blazquez, M., "Fashion shopping in multichannel retail : the role of technology in enhancing the custome rexperience", International Journal of Electronic Commerce, 18(4), pp.97~116 (2014)
  13. 서초, "중국 20대 소비자들의 인터넷 쇼핑 위험지각이 구전(e-WOM)에 미치는 영향", 한국의류학회지, 38(5), pp.690~704 (2014), 한국의류학회
  14. 류은정, "인터넷 의류쇼핑몰의 서비스 품질과 구매의도의 영향 요인에 관한 연구", 복식문화연구, 10(3), pp.261~269 (2002), 복식문화학회
  15. Jiaziken, "지각된 위험, 해외직구 사이트 정보특성, 혁신성이 소비자 신뢰 및 호의도와 구매의도에 미치는 영향 –중국 소비자를 중심으로-", 석사, pp.2018
  16. Shin, E., "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, 32(1), pp.20~33 (2014)[DOI]
  17. Aurélie Merle, "Whether and How Virtual Try-On Influences Consumer Responses to an Apparel Web Site", International Journal of Electronic Commerce, 16(3), pp.41~64 (2012), Informa UK Limited[DOI]
  18. Efendi Nasibov, "A fuzzy logic apparel size decision methodology for online marketing", International Journal of Clothing Science and Technology, 31(2), pp.299~315 (2019), Emerald[DOI]
  19. Y. S. Ding, "Intelligent optimal selection of garment sizes by using immune algorithm and AHP method", Journal of the Textile Institute, 99(3), pp.281~286 (2008), Informa UK Limited[DOI]
  20. 황수연, "의류 인터넷 쇼핑몰의 가상 아바타 피팅 모델이 소비자 구매행동에 미치는 영향연구:기존 온라인 쇼핑몰 모델과 가상 피팅 아바타 모델 비교", 패션 비즈니스, 17(5), pp.57~69 (2013), 한국패션비즈니스학회[DOI]
  21. "The avatar’s new clothes" (2011)[URL]
  22. "‘쇼핑몰 가상피팅’ 직접 해보니... 온라인보완 ‘ 신세계’" (2016)[URL]
  23. "Fits.Me’s shape-shifting robot lets you try on clothes, online" (2012)[URL]
  24. Abels, A., "Construction of a female shape-changing robotic mannequin", Journal of Automation and Control Engineering, 1(2), pp.132~134 (2013)[DOI]
  25. Guo, Z., "The design of a form-changing female fitting robot", Journal of Advanced Mechanical Design, Systems, and Manufacturing, 10(8) (2016)[DOI]
  26. Peng, S., "Development of an interactive robotic mannequin for fashion industry", doctor, pp.2013
  27. "You can soon buy custom fast fashion from Japan’s biggest E-Comm compan" (2018)[URL]
  28. "Billionaire to sell stake in Zozotown to Yahoo Japan for $3.7bn" (2019)[URL]
  29. "Size Recommendation Technology at Uniqlo"[URL]
  30. "Size Recommendation Technology at ASOS"[URL]
  31. 조연주, "뷰티 소비자의 온라인 경험가치가 소비자 행복과 브랜드신뢰 및 구매의도에 미치는 영향 -쇼핑경험의 SNS 구전정보특성의 조절효과를 중심으로-", 박사, pp.2019
  32. 김상률, "브랜드 프랜차이즈 매장에서의 감각적 경험이브랜드 태도, 경험적 가치, 그리고 소비자 행복에 미치는영향", 2016 한국창업학회 춘계학술대회, pp.311~332 (2016)
  33. Congying Guan, "Apparel recommendation system evolution: an empirical review", International Journal of Clothing Science and Technology, 28(6), pp.854~879 (2016), Emerald[DOI]

관련 논문AI추천

이 간행물의 다른 논문 (9건)