• Journal of Digital Convergence
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• v.11 no.2
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• pp.115-125
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• 2013

Unexpected consumer dissatisfaction emerges through rapid growth and expansion of on-line shopping channel. This research focused on the fashion online retail channels' negative aspect caused by service failure which possibly disappointed consumers. We also tried to seek for appropriate service recovery types based on frequently offered recovery types on-line. Data from college students were analyzed. Results indicate that fitting problem, insufficient information, product defect, inventory problem and slow delivery were the main service failure types in apparel e-shopping. Regression analysis identified that among these types, insufficient information, product defect, and slow delivery had significant influence on channel satisfaction after post recovery effort. Results also confirmed significant relationships between channel satisfaction and channel switching. Consumers perceived benefit level causes overall channel satisfaction level to rise while perceived risk leads to lower level of channel satisfaction. Choosing desirable service recovery activities in each service failure situations is necessary in order to raise consumer's channel satisfaction in online apparel shopping.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.443-446
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• 2014

최근 인터넷을 이용한 의류 관련 쇼핑몰이 증가되고 있다. 그에 따라 이용자들도 오프라인 매장뿐만 아니라 온라인 쇼핑몰 매장을 즐겨 찾고 있으며, 이에 따라 온라인 쇼핑몰의 차별성이 중요시 되고 있다. 본 논문에서는 이러한 온라인 쇼핑몰의 차별성을 극대화하기 위해서 오프라인 매장의 장점을 살리고자 하였다. 오프라인 매장에서는 매장 직원에 의한 상의 하의 추천이 가능하고 이에 따라 매출향상 및 이용자의 만족도를 이끌어내고 있다. 이러한 오프라인 매장의 장점을 온라인에서도 그대로 실현하기 위해서 의류의 색상을 계산하여 나오는 색상 값을 색조합표를 기반으로 하여 가장 어울리는 의류에 대해 자동으로 추천해주는 시스템을 설계하였다.

• Proceedings of the Costume Culture Conference
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• 2003.04a
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• pp.99-100
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• 2003

최근, IT산업의 급격한 발달과 쇼핑패턴의 변화로, 전 세계적으로 온라인쇼핑의 이용자가 증가되고 있다. 이러한 변화와 더불어 학계에서 중요하게 다루어진 부분은 소비자들이 사이버공간이라는 새로운 쇼핑매개체를 어떻게 받아들이는가 하는 부분, 즉 온라인 쇼핑에서 기존의 구매방식과는 다르게 어떠한 위험들이 지각되고 있는가 하는 것이다. 온라인 쇼핑에서 지각되는 위험을 알고, 이를 고려한 쇼핑환경을 조성한다면, 소비자들이 온라인 쇼핑패턴을 받아들이고 신뢰하게 되며, 나아가 특정 온라인 쇼핑몰에 상표충성 하도록 할 수 있을 것이다. (중략)

• Journal of the Korean Society of Clothing and Textiles
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• v.33 no.6
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• pp.880-892
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• 2009

An overflow of information leads consumers to be easily distracted and to neglect the information being provided to them. E-tailers have to select types of information sources and provide their consumers with the most appropriate information. This study was done to specifically contribute to the research in proposing strategies of providing information of the Internet merchant to the e-shoppers through the analysis of relationships among the online purchase motives of consumers, the use of information sources, and decision making styles. This research categorizes the use of information sources into information sources concerning online stores and information sources concerning products. The uses of information sources relative to online stores are classified into the neutral, human, and marketer-oriented sources. The uses of information sources concerning the products are classified into the online and offline source. This study provides important suggestions for e-tailers to provide information about stores as well as products to the consumers with adaptable strategies.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06b
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• pp.83-87
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• 2010

스마트폰의 대중화로 사용자들의 상위 욕구를 충족시켜주는 개인화된 서비스의 다양한 어플리케이션들은 사용자에게 편의를 제공하여 생활을 향상시킨다는 점을 하나의 전제로 하고 있으나, 이를 구성하는 주된 역할을 수행할 서비스들의 요구사항을 부합시키는 스마트폰 성능이 현 기술에 적응적으로 대응하기에는 한계가 있다. 기존 3D VWS는 온라인 의류 쇼핑몰을 위한 시스템으로 사용자에게 의류 착용후의 모습을 제공하여 쇼핑몰 업무의 효율성 및 의류반품비용의 절감과 더불어 쇼핑몰 이용자에게 만족을 주어, 전반적인 온라인 쇼핑몰 이익 상승을 기대할 수 있게 한다. 하지만 3D VWS는 초고속 인터넷환경과 고사양 컴퓨터에서 원활한 서비스가 가능하기 때문에 스마트폰 환경에 이를 수용하고 동작시키기 위해서는 극복해야 할 많은 문제점을 가지고 있다. 이러한 문제를 극복하기 위해서 본고에서는 2D 이미지 확대/축소를 통하여 사용자에게 의류 착용후의 모습을 간접적으로 제공하는 2D VWS를 이용하여 스마트폰 기반 VWS 연구의 초석을 다지는데 도움이 되고자 한다.

• Annual Conference of KIPS
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• 2018.05a
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• pp.500-503
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• 2018

최근 스마트폰의 보급률이 높아지면서 인터넷 쇼핑몰의 접근성이 용이해지고 있고 그로 인해 사용자들의 인터넷 쇼핑의 이용이 보편적이게 되었다. 그 중 여성 의류 분야는 많은 비중을 차지하고 있으며 현재도 꾸준히 성장하고 있는 추세이다. 많은 여성 소비자들은 개인의 취향에 맞는 의류들을 추천받기를 원한다. 본 논문에서는 협업 필터링에서 발생하는 cold start 문제를 이름, 나이, 선호 스타일, 자주 사용하는 쇼핑몰 등 개인 성향을 이용하여 해결하는 협업 필터링과 개인 성향을 이용한 여성 의류 쇼핑몰 추천 시스템을 제안한다.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.1061-1069
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• 2011

With the development of information technology, online commercial transactions have been steadily increasing. However it is not easy to recommend the clothes in coordination with individual physical features. This paper presents a fashion coordination recommender system for women's clothes. The system includes the functionality of recommending clothes best-suited for customers in consideration of their individual physical features. It has also been designed to recommend clothes in vogue for those who are fashion-sensitive by considering the fashion trend of the times. Operated in an optional or coupling way, these functionalities of our system result in an intelligent fashion coordination system which recommends dress items to customers in various ways.

• Journal of the Korean Home Economics Association
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• v.47 no.9
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• pp.101-110
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• 2009

The purpose of this study was to examine the effect for information load on perceived information quality and website quality, and the relationships among perceived information quality, website quality and behavioral intentions in online apparel shopping contexts. The information load theory provided the theoretical framework for this study. The research strategy employed an online experimentation using an apparel mock website. The total of 647 responses were used for data analyses. The model of the study was tested by MANOVA and SEM. The results of MANOVA revealed the effect of information load on perceived information quality and website quality. The medium level of information load was perceived as having more positive information quality and website quality as compared to the low or high level of information load. The findings of SEM revealed the positive effect of information quality on website quailty, the positive effect of website quality on WOM and willingness to pay more, and the negative effect of website quailty on willingness to switch. Online apparel retailers and website designers need to manage information quantity and quality by understanding the importance of information load.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.11
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• pp.1475-1484
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• 2005

The purposes of this study were 1) to examine the dimension of fashion shopping mall attributes and shopping value related to online shopping, and 2) to investigate the effects of fashion shopping mall attributes and shopping value on purchase intention in online shopping. Data were obtained from 423 online fashion shopping mall consumers who have experiences of buying products or visiting to online fashion shopping mall in Busan, and were analyzed using by factor analysis, Cronbach's alpha, path analysis of LISREL 8.53. The results showed online fashion shopping mall attributes were composed of Visual information, Loading speed Space composition, Product assortment, Checkout service, and Help desk. Shopping value perceived by online fashion shopping mall consumers were consisted two factors: Hedonic value and Utility value. Hedonic value and Utility value Perceive by online consumers were influenced by Product assortment, Visual information, Help desk, and Space composition of shopping mall. Additionally, hedonic and utility shopping values perceive by online consumers impacted online purchase intention. Findings suggest that fashion shopping mall attributes mediated by shopping values are important in predicting purchase intention of online shopping mall. Implications are drawn for the information useful to consumer behavior researchers and retailers of online fashion shopping mall.

• The Journal of Bigdata
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• v.7 no.2
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• pp.217-224
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• 2022

Since online shopping has become common, people can easily buy fashion goods anytime, anywhere. Therefore, consumers quickly respond to various environmental variables such as weather and sales prices. Therefore, utilizing big data for efficient inventory management has become very important in the fashion industry. In this paper, the changes in sales volume of fashion goods due to changes in temperature is analyzed via the proposed big data analysis algorithm by utilizing actual big data from Korean fashion company 'A'. According to the simulation results, it was confirmed that Bidirectional-LSTM(Bi-LSTM) compared to LSTM(Long Short-Term Memory) takes more simulation time about more than 50%, but the prediction accuracy of non-periodic time series data such as clothing product sales data is the same.