• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.207-212
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• 2007

Recently, requriements that people want to receive various information related with fashion are increasing. A lot of internet shopping malls and corporations provide information about fashion. However, those systems do not give enough information about fashion. To solve these problems, the paper provides the recommend technique for providing complex fashion information on mobile devices. The providing system implements fasion ontology by using XML. The XML ontology has dewey number as an attribute. The recommend technique uses this number and find LCA(Lowest Common Ancestor) on the fashion ontology. Then those child nodes under the LCA are recommended as related information. The results are displayed on the mobile browser. The system provides function for taking a picture or movie of fashion contents. Those movies and pictures are UCC(User Created Content)s. The system is a novel system that can recommend complex fasion information on mobile devices.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.427-428
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• 2013

본 논문에서는 정보화에 취약한 농가의 약점을 보완할 수 있는 정보포털 시스템을 설계하여 중소규모의 농가 쇼핑몰, 블로그 등을 스토리텔링과 결합하여 온라인으로 홍보가 가능하도록 하였다. 농산물 홍보용 허브 플랫폼은 농가들이 운영하는 수없이 많은 쇼핑몰과 농 특산물을 홍보하기 위한 마케팅채널과 직접 자신의 농산물을 소개할 수 있는 채널을 구축하여 소비자와 생산자 실시간 온라인 대화채널 구축을 통한 소통 공간 조성 및 신뢰성을 확보할 수 있다.

• Journal of Distribution Science
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• v.16 no.2
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• pp.89-99
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• 2018

Purpose - In this study, we discuss the current status and barriers of digital transformation focused on small businesses. More specifically, this study consists of two studies. The purpose of study 1 is to investigate the effect of digitization of small businesses on the sales of stores and the number of visiting customers. The purpose of Study 2 is to examine the status and obstacles of online channels use by small businesses. Research design, data, and methodology - In Study 1, we will examine the changes in sales and visitor numbers of stores that are rapidly adapting to digital transformation among small business. For this, we utilize the actual situation of store management survey conducted by the Small Enterprise and Market Service. Specifically, multiple regression equations were used to determine whether blogs and online shopping malls were operating, and the proportion of credit cards to sales as independent variables and sales and number of visiting customers as dependent variables. Next, in Study 2, we surveyed the 15 small business owners in the latest survey on the actual situation of store management survey conducted in 2015, and conducted an in-depth interview to examine the barriers to the use of online channels by small business. Results - As a result of study 1, it is found that the small business who run the blogs have higher sales and visits than the small business who do not. However, there is no difference in the sales and the number of visiting customers between the stores that operate the online shopping malls and those that do not. Second, the higher the proportion of credit cards, the higher the sales and the number of visiting customers. In study 2, we analyzed the barriers to the expansion of online channels by in-depth interviews. Interviews show that barriers to access to online channels are limited by search neutrality, high commission burden, and low bargaining power. These problems are caused by the insufficiency of small business compared to online and mobile portal and O2O platform vendors. Conclusions - This study suggests that small business who have difficulty in establishing direct online channels need digital transformation of small business. In addition, when using such an external platform, we have identified the problems that small business face.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.71-89
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• 2019

In order to come up with satisfying product and improvement, firms use traditional marketing research methods to obtain consumers' opinions and further try to reflect them. Recently, gathering data from consumer communication platforms like internet and SNS has become popular methods. Meanwhile, with the development of information technology, mobile companies are launching new digital products for children to protect them from harmful content and provide them with necessary functions and information. Among these digital products, Kids Phone, which is a wearable device with safe functions that enable parents to learn childern's location. Kids phone is relatively cheaper and simpler than smartphone but it is noted that there are several problems such as some useless functions and frequent breakdowns. This study analyzes the reviews of Kids phones from domestic mobile companies, identifies the characteristics, strengths and weaknesses of the products, proposes improvement methods strategies for devices and services through SNS consumer analysis. In order to do that customer review data from online shopping malls was gathered and was further analyzed through text mining methods such as TF/IDF, Sentiment Analysis, and network analysis. Customer review data was gathered through crawling Online shopping Mall and Naver Blog/$Caf\acute{e}$. Data analysis and visualization was done using 'R', 'Textom', and 'Python'. Such analysis allowed us to figure out main issues and recent trends regarding kids phones and to suggest possible service improvement strategies based on sentiment analysis.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.1-31
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• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• Journal of the Korean Society of Clothing and Textiles
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• v.35 no.9
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• pp.1112-1124
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• 2011

The development of computer graphics and Internet technology has created a 3D Web-based virtual world that has transformed the global fashion industry environment. In this study, the application cases of 3D virtual fashion education were analyzed to discuss the necessity and application of a 3D apparel CAD curriculum as part of a special education for global fashion talent at Korean fashion-related colleges. Prior studies, literature, photo data and Internet data (in and out of Korea) were used for this study. The demonstration case studies were conducted for the virtual fashion education 'SLCC 2007' of Buffalo State College (U.S.), 'Ratava's Line (2004)' of SFU/FIT Collaborative Design Project (Canada and U.S.) and '2011 Graduation Fashion Show' of Ueda Fashion College (Japan). The results of the study show that the 3D apparel CAD system (as a core technology of the IT fashion industry) would allow the current mass production concept to change to a new paradigm of 'mass customization' along with new fashion business types that include global fashion companies and Web-based Internet, mobile and virtual-world shopping malls. In addition, it appears that the system should be included in the curriculum of fashion-related colleges and institutes to educate technical designers for the global fashion industry and global fashion talent with comprehensive system operation and management ability, and to promote single proprietor companies.

• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.1
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• pp.45-60
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• 2024

This study analyzes the athleisure wear purchase status, wearing conditions, and design preferences of men in their 20s and 30s and provides basic data for the development of men's athleisure wear that reflects consumer preferences. An online survey was conducted on 200 men from August 23 to August 27, 2023. The questionnaire consisted of a total of 48 questions, including 8 questions about the respondent's general information, 19 questions about the purchase status of athleisure wear, 6 questions about the status of wearing athleisure wear, and 15 questions about athleisure wear design preferences. The survey results are as follows. The most common motive for exercise participation was 'maintaining health.' 'Nike' was the most preferred and purchased brand among athleisure wear brands, and the main place of purchase of athleisure wear was 'Internet and mobile shopping malls', reflecting the recent purchasing trend of the MZ generation. When purchasing athleisure wear, the most common selection criterion was 'design', followed by 'fitting comfort', 'possibility to use as daily wear', and 'price'. The most common route to obtain purchase information was 'Internet search', and the 'overall satisfaction' with athleisure wear was found to be satisfactory with an average of 3.83. The most common reason for wearing athleisure wear was 'because it is comfortable to do activities', followed by 'because it can be used as everyday wear'. Lastly, 'black', 'short-sleeved t-shirt', 'short length' sleeve, 'round neckline', 'waist length', and 'relaxed loose fit' were preferred for the top design, and 'black', 'shorts', 'full elastic type' waistband, 'regular fit that fits the body well' were preferred for the bottom design.

• Trans-
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• v.10
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• pp.73-113
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• 2021

Previous studies show that VR images can influence consumers' attitudes and behaviors by evoking imagination. In this study, we introduce a reality-based closed-loop 3D image (hereafter Virtualgraph). Then we try to see whether such image would increase evocativeness in a mobile commerce environment and whether higher telepresence of the visual image of a product can increase the purchase intention of that product. In order to find the above, we developed a model comprised of constructs containing telepresence, perceived value price, perceived food quality, and vividness of visual imagery questionnaire (VVIQ). We used Virtualgraph application to conduct an experiment, and then conducted an interview as well as a survey. As results of the experiment, survey and interview, we found the followings. First, users evoke imagination better with Virtualgraph than with still images. Second, increased evocativeness affects purchase intention if the perceived quality of fresh food product is satif actory. Third, increased evocativeness makes users value products higher and do even much higher when the perceived quality of fresh food product is good. From the interview, we could find that the experimental group had higher purchase intentions and perceived products as more expensive ones. Also, they perceived images of products clearer and more vivid than did the control group. We also discuss the strategic implications of using Virtualgraph in mobile shopping malls.