• Journal of the Korean Society of Clothing and Textiles
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• v.37 no.1
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• pp.76-89
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• 2013

The exploration of the interaction effect among the components of attractiveness is impossible; therefore, this study uses an indirect estimates approach with multiple scale items that can measure the interaction effect among the components of attractiveness to solve the problem of direct estimates. Previous studies focused on intra-store type competition as their subjects; subsequently, this study dealt with intra-store type competition as well as inter-store type competition in the competing and selecting activities among fashion retailing stores with different business models (such as department stores, road brand stores, discount stores, outlets and internet shopping malls). This study suggests a generalized model for shopping attractiveness of stores and proposes a fashion retailing store type attractiveness (FaRSTA) model instead of a simple relative importance between store selection standards.

• Proceedings of the Costume Culture Conference
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• 2003.09a
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• pp.104-106
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• 2003

현대사회는 정보의 디지털화와 컴퓨터의 급속한 보급으로 인한 네트워크 환경의 발전으로 사이버 사회로의 전환과정을 거치고 있다. 인터넷이라는 새로운 매체의 등장은 단순히 객체간에 시공을 초월한 정보전달뿐 아니라 비즈니스의 방식에도 매우 큰 변화를 가져오고 있다. 이미 인터넷을 통한 무점포 판매방식은 기존의 리테일링 개념에 혁명적인 변화를 가져오고 있고 인터넷을 통한 정보교류는 고객과의 접촉방법, 고객에 대한 정보수집 등의 과정에서 저렴한 비용으로 효과적인 마케팅을 수행할 수 있게 하고 있다. (중략)

• Journal of the Korean Society of Clothing and Textiles
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• v.42 no.1
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• pp.148-158
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• 2018

This study analyzes recent trends in fashion retailing instigated by the fourth industrial revolution and approaches the trends in terms of the convergence of big data and artificial intelligence. The findings are as below. First, companies like 'Edited' and 'Stylumia' offer solutions that support the strategic decisions of fashion brands and fashion retailers by analyzing big data using artificial intelligence. Second, the convergence of big data and artificial intelligence scales personalized service on the web as examples of 'Coded Couture', 'StitchFix', and 'Thread'. Third, the insights gained from artificial intelligence and big data help create new fashion retailing platforms such as 'Botshop' and 'Lyst'. Last, artificial intelligence and big data assist with design. 'Ivyrevel' designs digital fashion, assisted by a macroscopic perspective on fashion trends, market and consumers through the analysis of big data. The Fourth Industrial Revolution brings changes across all industries that will likely accelerate. The fashion industry is also undergoing many changes with advancements in scientific technology. The convergence of big data and artificial intelligence will play a key role in the future of fast-moving industry like fashion, where fickle tastes of consumers are the main drivers.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.7-17
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• 2021

This study investigated the effect of size recommendation technology convergence on purchase intention mediated by information credibility and satisfaction. The survey for this study was conducted on Amazon Mechanical Turk targeting U. S. residing women aged 18 to 60 years old who have never used size recommendation technology. They experienced the size recommendation technology in the provided web page and returned to the survey to answer the questionnaire. The analysis was done with 213 surveys using SPSS 27.0 and Process Macro (model 6, 5,000 Bootstrapping sample). The dimensions of service quality were found to be responsiveness and ease of use, and both have a significant effect on purchase intention through information credibility and satisfaction.

• Journal of the Korean Society of Clothing and Textiles
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• v.41 no.1
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• pp.170-183
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• 2017

The rapid growth of digital consumption has significantly changed the shopping behavior of consumers. The consumption paradigm is changing; subsequently, an omni-channel has been introduced that empowers consumers to interact with firms through a myriad of touch points in multiple channels. This study is to understand the perceptions and behavioral characteristics of consumers in the purchase process (e.g., information search and purchase phase). A qualitative method was adopted for this study and data were collected through semi-structured in-depth interviews with 15 omni-channel consumers. The results of this study were as follows. At the information search stage, consistency was the most important consideration for consumers who also wanted to retain channel-specific benefits. Consumers also searched for differentiated information among distribution channels. At the purchase stage, participants choose a shopping channel according to shopping values. They utilized newly introduced services (e.g., "online purchase, offline pick-up", FinTech) that combine retail channels. Our findings provide significance in managing omni-channel services. First, it is recommended that fashion retailers provide seamlessly integrated experience to consumer and adopt a consumer-centered channel choice strategy. Second, fashion retailers must maintain a constant attitude toward shopping experience to fashion, such as shopping enjoyment and exclusiveness.