• 제목/요약/키워드: 의류추천

검색결과 66건 처리시간 0.029초

온라인 구매후기 작성동기가 패션제품 재구매의도 및 추천의도에 미치는 영향 (The Effect of Online Review Writing Motives of Internet Shopping on Repurchase Intention and Recommendation Intention about Fashion Merchandise)

  • 구태희;구양숙
    • 한국의류산업학회지
    • /
    • 제12권2호
    • /
    • pp.188-193
    • /
    • 2010
  • The purpose of this study was to investigate the online review writing motives of online shopping on repurchase intention and recommendation intention about fashion merchandise. The questionnaire was administered to 279 people who had experience in online shopping. The data were analyzed by utilizing factor analysis, multiple regression analysis and t-test. The results of this study were as follow. First, the online review writing motives were divided into three categories such as benefit pursuit/hedonic shopping value, information transmission and evaluation. Second, the consumer who has experience of writing review prefers to repurchase other products in that online shopping mall and to recommend those products more than the consumer who doesn't have that experience. Third, the benefit pursuit/hedonic and information transmission had an effect on repurchasing intention and recommendation intention.

빅데이터 기반 패션 추천 도우미 Shoes Navigator 설계 및 구현

  • 조현우 ;장지완 ;최현선;정목동
    • 한국정보처리학회:학술대회논문집
    • /
    • 한국정보처리학회 2023년도 추계학술발표대회
    • /
    • pp.389-390
    • /
    • 2023
  • 본 논문에서는 패션 매칭의 어려움을 해결해주기 위하여 '무신사' 쇼핑몰을 이용하여 크롤링하고 이를 정제한 dataset을 이용하여 패션 스타일의 핵심 요소 중 하나인 신발에 초점을 맞추어, 이미지 기반의 패션 매칭 시스템인 빅데이터 기반 패션 도우미, Shoes Navigator 를 제안한다. 이를 위해 컴퓨터 비전 및 딥 러닝 기술을 활용하여 이미지에서 의류 항목을 자동으로 감지하고, 스타일, 색상과 같은 패션 특성을 추출한다. 또한, 사용자의 개인적인 스타일을 고려하여 최적의 매칭을 제안하기 때문에 패션 코디 문제를 용이하게 해결할 수 있다.

딥러닝을 이용한 의류 이미지의 텍스타일 소재 분류 (Textile material classification in clothing images using deep learning)

  • 이소영;정혜선;최윤성;이충권
    • 스마트미디어저널
    • /
    • 제12권7호
    • /
    • pp.43-51
    • /
    • 2023
  • 온라인 거래가 증가하면서 의류 이미지는 소비자의 구매 결정에 큰 영향을 미치게 되었다. 의류 소재에 대한 이미지 정보의 중요성이 강조되고 있으며, 의류 이미지를 분석하여 사용된 소재를 파악하는 것은 패션 산업에 있어서 중요하다. 의류에 사용된 텍스타일의 소재는 육안으로 식별하기 어렵고, 분류 작업에도 많은 시간과 비용이 소모된다. 본 연구는 딥러닝 알고리즘을 기반으로 의류 이미지로부터 텍스타일의 소재를 분류하고자 하였다. 소재를 분류함으로써 의류 생산 비용을 절감하고, 제조공정의 효율성을 증대하는데 도움이 되며 소비자에게 특정 소재의 제품을 추천하는 AI 서비스에 기여할 수 있다. 의류 이미지를 분류하기 위해 머신비전 기반의 딥러닝 알고리즘 ResNet과 Vision Transformer를 이용하였다. 760,949장의 이미지를 수집하였고, 비정상 이미지를 검출하는 전처리 과정을 거쳤다. 최종적으로 총 167,299장의 의류 이미지와 섬유라벨 19개, 직물라벨 20개를 사용하였다. ResNet과 Vision Transformer를 사용해서 의류 텍스타일의 소재를 분류하였으며 알고리즘 성능을 Top-k Accuracy Score 지표를 통해 비교하였다. 성능을 비교한 결과, ResNet 보다 Vision Transformer 알고리즘이 더 우수하였다.

속성값 메트릭스를 이용한 상의-하의 자동 의류매칭 방법 (A Method of Upper-Lower Clothes Automatic Matching Using Attribute-values Matrix)

  • 김정인
    • 한국멀티미디어학회논문지
    • /
    • 제13권9호
    • /
    • pp.1348-1356
    • /
    • 2010
  • 정보통신기술의 발달로 인터넷을 이용하는 패션/코디 쇼핑몰은 그 시장이 매년 큰 폭으로 증가하고 있다. 패션/코디 쇼핑몰의 개수가 증가함에 따라 소규모 쇼핑몰 운영자들은 자신의 사이트에 방문자를 늘이기 위하여 첫 페이지에 다양한 이벤트나 어울리는 상의-하의로 치장을 하게 된다. 운영자는 매일 혹은 며칠에 한번 씩 첫 페이지의 내용을 수작업으로 바꾸어서 방문자에게 항상 신선한 느낌으로 상품을 소개한다. 온라인 패션 쇼핑몰에서 판매하는 다양한 상품들에 대하여 상의와 하의의 어울리는 정도를 자동으로 계산하여 표기할 수 있다면, 첫 페이지의 장식을 도와줄 수 있을 뿐 아니라 오프라인에서의 점원에 의한 추천을 대신하여 사용자들의 연계 구매에도 한층 편리할 것으로 기대된다. 본 연구에서는 코디 전문가가 상의-하의 의류에 대하여 휴리스틱에 의한 어울림 값을 속성별 매트릭스 형태로 등록하여, 실제 의류들에 대하여 상의-하의 의류를 자동 매칭해주는 시스템을 설계하고 구현하였다.

패션 챗봇 상품추천 서비스의 지각된 품질이 지각된 유용성, 신뢰 및 소비자 반응에 미치는 영향 (The Effects of Perceived Quality of Fashion Chatbot's Product Recommendation Service on Perceived Usefulness, Trust and Consumer Response)

  • 이유리;김효정;박민정
    • 한국의류학회지
    • /
    • 제46권1호
    • /
    • pp.80-98
    • /
    • 2022
  • Artificial intelligent chatbot services have recently become common in fashion e-retailing and are expected to improve online shopping by making it easy to recommend products. This study examines whether the perceived quality of a fashion chatbot affects consumers' trust and perception of usefulness, which in turn influences satisfaction and intention to use, in accordance with the information system success model. The study also investigates differences in perceived quality and consumer response variables between high and low groups of self-efficacy. A total of 341 consumers participated in an online survey. The results revealed that information quality and system quality had a significant impact on perceived usefulness and trust, and that service quality significantly impacted trust. Perceived usefulness and trust had a positive effect on consumer satisfaction, which in turn had a positive effect on intention to use. In addition, the findings revealed that people who had higher self-efficacy showed higher scores on perceived usefulness, trust, satisfaction, and intention to use chatbots as compared to people who had lower self-efficacy. This study suggested theoretical implications by applying the information system success model theory to fashion chatbot studies. It also suggested practical implications for e-commerce marketers developing retail strategies.

온라인 상품추천 서비스에 대한 소비자 사용 의도 -신뢰-몰입의 매개역할을 중심으로- (Consumers' Usage Intentions on Online Product Recommendation Service -Focusing on the Mediating Roles of Trust-commitment-)

  • 이하경;윤남희;장세윤
    • 한국의류학회지
    • /
    • 제42권5호
    • /
    • pp.871-883
    • /
    • 2018
  • This study tests consumer responses to online product recommendation service offered by a website. A product recommendation service refers to a filtering system that predicts and shows items that consumers would like to purchase based on their searches or pre-purchase information. The survey is conducted on 300 people in an age group between 20 and 40 years in a panel of an online survey firm. Data are analyzed using confirmatory factor analysis and structural equation modeling by AMOS 20.0. The results show that personalization quality does not have a significant effect on trust, but relationship quality and technology quality have a positive effect on trust. Three types of quality of recommendation service also have a positive effect on commitment. Trust and commitment are factors that increase service usage intentions. In addition, this study reveals the moderating effect of light users vs heavy users based on online shopping time. Light users show a negative effect of personalization quality on trust, indicating that they are likely to be uncomfortable to the service using personal information, compared to heavy users. This study also finds that trust vs commitment is an important factor increasing service usage intentions for heavy users vs light users.

오픈마켓 의류구매에서의 재품 및 쇼핑몰 속성 만족이 구매행동에 미치는 영향 -쇼핑몰 신뢰, 재구매 의도, 추천 의도를 중심으로- (The Influences of Satisfaction of Product and Shopping Mall Properties on Clothing Purchasing Behavior in Internet Open Market -Focusing on Mall Reliability, Repurchase Intention, and Recommendation Intention-)

  • 지혜경
    • 한국의상디자인학회지
    • /
    • 제14권3호
    • /
    • pp.161-176
    • /
    • 2012
  • This study aims to find out the influence of satisfaction of the product and shopping mall attributes on mall reliability, repurchase intention, and recommendation intention in internet open market. For this purpose, this study surveyed 266 male and female consumers in their 20's~40's for empirical analysis who have ever purchased clothing through internet open markets. Respondents are selected using the convenience sampling through online survey in August 2011. For statistical analysis, descriptive statistics, reliability analysis, factor analysis, t-test, ANOVA, and regression analysis are carried out using SPSS for Windows 12.0. The results are as follows; First, it was identified that there were Significant differences in consumers' satisfaction on product and shopping mall attributes according to purchase price, degree of purchase, and the demographics. Second, it was identified that performance, sewing condition, the stability of the form, texture, harmony with other clothes, the response of people, fashionability, seller, origin, detailed explanation on products, interaction with shopping malls, and ease-of-use have significant influence on the reliability of open market. Third, it was identified that easiness to be active in, the stability of the food, design, suitability to T.P.O, price, origin, detailed explanation on products, product assortment, reputation of shopping malls, ease-of-use, and delivery charge policy have significant influence on the repurchase intention. Fourth, it was identified that easiness to be active in, the stability of the form, design, suitability to T.P.O, price, origin, detailed explanation on products, product assortment, reputation of shopping malls, ease-of-use, and delivery charge policy have significant influence on the intention to recommend.

  • PDF

패션 기업의 CSR 활동에 대한 인지적 적합성이 소비자 추천 및 구매의도에 미치는 영향 (Impact of the Perceived Fit of a Fashion Company's CSR Activities on the Recommendation and Purchasing Intention of Consumers)

  • 이정임;신수연
    • 한국의류학회지
    • /
    • 제35권7호
    • /
    • pp.816-827
    • /
    • 2011
  • There is an increasingly fierce competition in the current fashion industry due to equalized technology, a shortened fashion cycle and changing lifestyle; however, it is not easy to map out successful marketing strategies that influence the outcome of business administration. This study discussed the importance of changing environments for the fashion industry and of CSR activities. The findings of the study were as follows. First, consumers who found the fashion company to perform more appropriate CSR activities rated its CSR activities more favorably. Second, consumers who considered the company's CSR activities more suitable for themselves viewed the CSR activities more favorably. Third, consumers who rated a fashion company's CSR activities more favorably showed a more favorable attitude to the company. Fourth, consumers who viewed a fashion company's CSR activities more favorably had a greater intention to recommend the company. Fifth, consumers who viewed a fashion company's CSR activities more favorably had a more buying intention for the company. Sixth, the consumers who took a more favorable attitude to a fashion company had a stronger recommendation intention for that fashion company. Seventh, the consumers who showed a more favorable attitude to a fashion company had a bigger buying intention. Eighth, the consumers who had a greater recommendation intention for a fashion company had an increased buying intention as well.

온·오프라인 지인의 추천메시지가 제품태도와 구매의도에 미치는 영향 (Effect of On/off-line Acquaintance's Recommendation Message on Product Attitude and Purchase Intention)

  • 이정우;김미영
    • 한국의류학회지
    • /
    • 제40권6호
    • /
    • pp.1010-1024
    • /
    • 2016
  • This study identifies the influence of on/off-line acquaintances' recommendation messages on fashion product attitude and purchase intention on the online purchase of fashion products in two-sided word of mouth situations as well as compares the difference in influence according to bond-base with equidistance. This study was conducted for one month on university students in their 20s who were believed to be active in smartphone use. Out of the collected 174 copies of the questionnaire, 162 copies were used for analysis. The questionnaire was classified into online and offline recommendation messages of an acquaintance. We present two-sided fashion product reviews made similar to the type found in an actual shopping mall web-site. As for analysis, confirmatory factory analysis, structural equation modeling, and multi-group analysis were conducted using AMOS 19.0. The analysis results are as follows. First, on/off-line acquaintances' recommendation messages had significant influences on product attitude in the situation where two-sided reviews on fashion products were presented; however, those messages did not influence purchase intention. Recommendation messages positively increased product attitude and enhanced purchase intention if acquaintances' recommendation messages were mediated between on/off-line acquaintances' recommendation messages and purchase intention. Consequently, a mediating effect on product attitude was revealed. Second, there was no difference between online acquaintances and offline acquaintances in terms of the influence of acquaintances' recommendation messages on product attitude and purchase intention, in the situation where two-sided reviews were presented on online fashion products. Therefore, no control effect according to the type of acquaintance was confirmed.

소비자의 선택 과부하와 유사성 회피 성향이 온라인 추천 서비스의 혁신성과 사용 적합성 지각에 미치는 영향 (The Effect of Consumers' Choice Overload and Avoidance of Similarity on Innovativeness and Use Compatibility in Online Recommendation Service)

  • 윤남희;이하경;장세윤
    • 한국의류산업학회지
    • /
    • 제21권2호
    • /
    • pp.141-150
    • /
    • 2019
  • Online recommendation services help people search for an appropriate product among a huge assortment in stores that also minimize consumers' choice overload. People with a need for uniqueness are likely to prefer this online recommendation service based on individual needs and tastes. This study verifies the effect of consumers' choice overload and similarity avoidance in consumers' evaluation towards an online recommendation service with a focus on innovativeness and use comparability. Two-hundred consumers participated in this study and data were collected through an online survey firm. A mock retailer's webpage was created and showed six types of sneakers, which was presented as a result of product recommendation based on consumers' personal information. Data was analyzed using confirmatory factor analysis (CFA), analysis of variance (ANOVA), and regression analysis. The results show that people with a high similarity avoidance perceive an online recommendation service as an innovative and compatible service. They also perceive a high level of use compatibility for an online recommendation service, especially when it is difficult to choose a product under choice overload. Innovativeness and use compatibility of an online recommendation service increase behavioral intention. The results of this study can contribute to strategies to start online recommendation services from online retailers' websites that identify circumstances in which consumers can adopt innovative services in a positive manner.