• Human Ecology Research
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• v.59 no.4
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• pp.449-463
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• 2021

The aim of this study was to analyze the perceptions and entering status of small business online fashion retailers on portal shopping and fashion shopping malls. Case studies were conducted on a total of 10 research samples. The results were as follows: first, regarding the strategic factors of online fashion stores, 'price competitiveness' is important, especially in portal shopping and low-cost brands; 'product assortment' is important but not essential in all platforms; and 'differentiation' is important to continuously secure loyal customers in fashion shopping malls. Customer satisfaction leads to customer loyalty, and customer loyalty affects the sales conversion rate and brand growth of online sales channels. Factors that promoted sales activities in online sales channels were exposure, advertisements, SNS, events, special exhibitions, and events. Hindrance factors were low price competition, overheated competition, and the MD of sales channels. Second, the research samples used multiple online sales channels, including portal shopping malls and fashion shopping malls, in addition to their own malls. The selection factors were platform reputation and commission, branding, and customer inflow through exposure. Portal shopping malls were perceived as providing easy access, advertising/customer communication, exposure/search, price competitiveness, scalability, and intense competition, whereas fashion shopping malls were perceived as providing a brand image and concept, brand promotion, high commissions, difficult entry, and low profits. The factors for success in portal shopping malls were exposure/search, price competitiveness, and brand recognition, whereas the factors for success in fashion shopping malls were differentiation, brand, exposure/advertisement, product assortment, and MD.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.597-603
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• 2022

With the continuation of the pandemic environment, digital transformation is being applied in various fields of the fashion industry. Augmented reality technology is a form of overlapping virtual images on the real world, and as online shopping expands in non-face-to-face environments, the use of augmented reality technology in fashion and beauty fields is affecting consumer satisfaction and sales growth. In this study, the characteristics of augmented reality contents used in the fashion industry following digital transformation were extended to the fields of clothing, accessories, virtual fashion stores, and AR fashion shows to analyze the case characteristics of augmented reality. Augmented reality technology in the fashion industry focuses on promoting clothing and accessory products through SNS or homepage through marketing activities. It is raising positive values such as raising awareness. The range of types of augmented reality used in the future digital fashion environment will continue to expand, and by deriving the usage characteristics of augmented reality technology, it is intended to contribute to presenting a future vision of the fashion industry.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.121-133
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• 2022

The main purpose of this paper is to examine the efficacy and future potential of a newly-emerging concept of a metaverse in online education environment. In order to achieve this goal, this paper showcases various scenes that happened in the metaverse classes using the ifland app. Through an in-depth analysis of theoretical grounds and preliminary survey findings of 32 university students, this study suggests that as students in a metaverse space are engaged in the interactive learning process and environment with an avatar that projects oneself, it can be an effective educational platform coming from the benefits of gamification and edutainment. In addition, a metaverse space provides existential encounters and hands-on experiences, which in turn increases the level of 3D learning immersion. It may overcome the shortcomings of online live streaming platforms such as Zoom or Webex that provide 2D experiences. Based on the findings, this paper further suggests a blueprint for online education suitable for the transition to a digital society.

• Journal of Korean Library and Information Science Society
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• v.54 no.2
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• pp.155-178
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• 2023

Due to the rapid advancement of information technology and changes in the reading environment, the readers' advisory services provided by public libraries are facing challenges and opportunities. Recognizing the need for public libraries to respond and propel their services forward, this study analyzed the current status of online readers' advisory services offered by public libraries in Korea and discusses areas that require improvement. To achieve this, the study analyzed the online readers' advisory services in 50 public libraries located in Seoul and six metropolitan cities (Incheon, Daejeon, Daegu, Gwangju, Busan, and Ulsan) across seven categories. These categories encompass various aspects, such as announcing reading programs and new books, identifying and addressing reader needs, developing content by librarians, generating content by readers, providing guidance on external reading information, connecting with professional book review databases and online websites, and utilizing social media services. Through this analysis, the study identified areas for improvement to enhance online readers' advisory services in public libraries and ultimately improve reader satisfaction. It suggested enhancing activities such as librarians' book recommendations and reviews for individual readers, reader participation, and interaction.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.237-249
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• 2017

This research aims to gain a better understanding of college students' thoughts on what factors make them happy and contribute to enhancing their happiness. We focused on the relationship between their self-assessed happiness and various factors affecting happiness, such as their socio-economic status, relationships with others, future orientation, and daily activities. Survey data were collected from October, 2014 to December, 2014 at a South Korean University. The final total number of respondents was 474 from 500 distributed questionnaires, after excluding 26 responses with missing values and unanswered items. The response was comprised of 247 male students, and 227 female students, and of 268 freshmen, 145 sophomores, 35 juniors, and 26 senior students. Factors that were statistically significant were gender, year, average cost of leisure, appearance satisfaction, conversation hour with parents, having girlfriend/boyfriend, sexual experience, number of friends, satisfaction with major, Grade Point Average (GPA), studying hours, time for self-improvement, reading hours, use of smart phone hours, number of daily meals, exercise hour, schedule management and future goal setting. This research was conducted utilizing only data from one university and so it may not be appropriate to generalize the results. Moreover, some of the variables are not in line with previous studies on happiness. Some other mediating variables may exist. Therefore, following research should be conducted.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1197-1210
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• 2017

This study aimed to compare premature ejaculation and erectile function according to penile characteristics. 99 adult men responded to a questionnaire on penile characteristics, premature ejaculation and erectile function. In the questionnaire survey, 69 questionnaires were analyzed except missing or incomplete answers. All collected data were analyzed by independent t test, Chi-square test using SPSS 22. Glans > penis type showed significant differences in subjective premature ejaculation and objective premature ejaculation compared to Glans ${\frac{._-}{.}$ penis type (p <.05). Men with subjective premature ejaculation showed significant differences in objective premature ejaculation, treatment intent, and satisfaction compared to men without subjective premature ejaculation (p <.05). Presence of objective premature ejaculation, presence of treatment intent, and marital status were significantly different in satisfaction (p <.05). In economic status, high was significantly different in confidence for erectile function compared to middle or low (p <.05). The results of this study suggest that the premature ejaculation and erectile function according to the penile characteristic may be different and may be used as a basis for the development of an intervention program for sexual rehabilitation of men with premature ejaculation and erectile dysfunction.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.249-257
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• 2020

The study aims to explore whether the Supplier's social medial activities and the consumer's social media activities mediate between the characteristics of purchasing cosmetics and the intention of purchasing. To answer this question, a total of 321 consumers participated in the study, and a self-report type of questionnaires were utilized to collect the data. For the data analysis, descriptive statistical analysis and structural equation modeling(SEM) were applied. The results from the study are as follows. First, the characteristics of purchasing cosmetics did not affect the intention of purchasing cosmetics. Second, both the Supplier's and the consumer's social media activities positively predicted the intention of purchasing, among which the consumer's activities were ascertained to make more influential impact on the intention of purchasing cosmetics. Third, both Supplier's and consumer's social media activities completely mediated between the characteristics of purchasing cosmetics and the intention of purchasing. More discussions are suggested for marketing strategies in the study.