• Journal of Venture Innovation
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• v.3 no.1
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• pp.101-115
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• 2020

In the era of the 4th Industrial Revolution customers living began to come out, not inside the purchase funnel. Due to the diversity of product selection and the increase in digital channels, the way customers search for information and purchase it is changing innovatively. So, the customer journey in the digital age is much more complicated than the traditional funnel model suggests. Unlike many previous studies, this study was conducted for 1,200 customers in four product groups of fashion, automobile, cosmetics, and online shopping malls. As a result of the study, we investigated how digital self-efficacy plays a role in purchasing in a series of processes in which digital experience affects customer satisfaction and finally affects purchase. As a theoretical implication, as a result of introducing and testing digital self efficacy as moderated mediation effect. the digital self-efficacy between customer satisfaction and customer loyalty were determined to play a moderated mediation effect role. As a practical implication, it was necessary to actively utilize digital marketing for customers with high digital self-efficacy, but it was suggested that customers with low digital self-efficacy need to be careful about digital marketing fatigue.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.142-151
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• 2020

The reason why today's public actively uses social communication is that the necessary information is collected and classified under the name of social big data through the web space to create the big data era, an ecosystem of information. In order for big data information to be used by the public, it is necessary to visualize it easily. This study categorized the types of visualization according to the information of social big data, and targeted the experienced students including the related majors and the general public who need to directly utilize and study the actual big data visualization as an experience evaluation target. As a result of analyzing the experiences of the experienced people, important implications for the visualization method for managing, analyzing, and utilizing the data were derived. The big data visualization strategy is to be expressed in a way that fits the data environment and user's eye level on SNS. In the future, if big data visualization is applied to product service or social trend, it will be an important data in terms of broadening its role, scope of application, and application.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.82-93
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• 2019

Fashion cannot encourage co-consumption with other people as a personal item, but it can lead to new consumer needs if fashion sharing service can professionally replace the time and cost of purchasing and managing goods. The purpose of this study is to empirically investigate the factors influencing the acceptance of fashion-sharing services based on the integration theory of user acceptance and utilization (UTAUT), and to discuss the virtuous cycle and sustainability pursuit of resources through the activation of the sharing. In this study, the research model for the acceptance of fashion sharing applications is schematized, and the survey was conducted 300 women aged 20~49 years. The screens of 'Project Anne', a representative fashion sharing service in Korea, were provided as a visual data. Reliability analysis, correlation analysis, confirmatory factor analysis, structural equation analysis, and multiple group analysis were performed using SPSS 23.0 and AMOS 22.0 statistical package for statistical analysis. As a result, efficiency and social influence positively influenced behavioral intention to use, and age has found that efficiency and social influences modulate the intensity of behavioral intention to use. Therefore, for the consumer acceptance and activation of fashion sharing services, marketing activities emphasizing efficiency and strengthening social influence factors are essential. Also, it is necessary to maintain the existing target group, 30~40s, and also construct additional products and price services for the 20s. This study is of academic significance in presenting basic data for empirical research on consumer acceptance of fashion sharing, and suggests a study on the influence relationship among user experience components for real users in the future.

• Information Systems Review
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• v.22 no.2
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• pp.137-166
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• 2020

While South Koreans overseas travelling rate has been increased every year, domestic travelling rate has been at a standstill for several years. The purpose of this study is to analyze domestic traveling styles of Koreans according to their generations in order to provide generation-specific traveling services. For this purpose, we categorized the survey respondents into four different generations, which are Millennium (age 19~34), X generation (35~54), Baby Boomer (55~64) and senior by following the criterions of the Korea National Tourism Organization. After then, we analyze factors related to travel preparation process, the actual traveling activities and satisfaction after the travel. In this study, 16,713 data collected by the Ministry of Culture, Sports and Tourism are used. The results of this study show that Korean people tends to acquire domestic traveling information from their own or acquaintances past experiences. Also, they do not prefer the organized trip for domestic travels, thus do not buy package products a lot. In addition, natural scenery, rich in cultural heritage, and convenient accommodation are the most important determinant factors affecting the overall travel satisfaction of level for all generations. The traveling characteristics for each generation are as follows. Millennium get traveling information from the internet a lot, and more specifically, they refer portal sites and social network services (SNS) in many cases. Also, they tend to travel in summer peak season to popular destinations and pursues active traveling experiences. Generation X has similar traveling patterns with Millennium, however they major transportation method is using their own car. Also, transportation convenience and satisfactory leisure activity are important factors affecting the overall satisfaction level to Generation X. On the other hand, Baby boomer generation has a greater emphasis on appreciation of nature, visiting famous restaurants, and relaxation, rather than actively participating experiencing programs. They travel evenly in summer and spring/fall season to many different areas instead of focusing on popular tourist spots. In addition, shopping and eating delicious food are the important factors affecting the overall satisfaction level for them. Lastly, Senior generation has similar characteristics with Baby boomer in many ways, however, they travel a lot on the same day using public transportations or car rental service. They prefer spring and autumn trips rather than summer peak season, and tend to buy packaged travel products a lot compared with other generations. If these different traveling characteristics of each generation are considered for organizing and customizing tourism services, it is expected that domestic tourism satisfaction level will be ultimately increased.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.3_4 s.141
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• pp.547-560
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• 2005

The purpose of this study was to segment Chinese career women by experience in purchasing Korean clothing and to analyze and compare clothing purchasing behavior between the 2 groups and to provide useful information to Korean manufacturers for establishment of marketing strategies for China. The subjects were 602 career women of middle and high class In their 20's and 30's. A total of 602 questionnaires were analyzed by using frequency, mean, Cronbach's $\alpha$, factor analysis, t-test and $X^2$-analysis. The results were as follows: 1. The demographic variables such as an age, residential city, marriage, and total monthly income were proven to be significantly different between the 2 groups except an academic background. 2. The clothing purchase behavior variables such as purchasing motive, using informants, clothing selection standards, store selection standards, purchasing place, satisfaction after purchasing clothes, shopping time, average monthly expenditure on clothing, purchasing frequency of casual wear, purchasing price, and paying method were proven to be significantly different between the 2 groups. However, the clothing purchase behavior variables such as purchasing frequency of formal wear and purchasing price of fur coat and sweater were proven not to be significantly different between the 2 groups.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.3_4 s.141
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• pp.478-490
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• 2005

The purpose of this study identifies effect of apparel merchandise characteristics on experienced emotion for apparel shopping and effect of consumer's emotion on attitude toward the internet shop. The data were collected from a sample of 271 internet shopper of university students(male: 82, femaie: 189). They visited the on-line shop for apparel shopping and after searching a casual clothing which they wanted to buy, requested to answer the questionnaire. The covariance structural model and research hypothesis analyzed by using AMOS 4.0 program. The results are as follows: First, the structural model is accepted($X^2$=128.30/d.f.=119/p=0.26, GFI=0.95 ; AGFI=0.93; RMR:0.05: NFI=0.94; PNFI=0.73). Second, apparel merchandise characteristics(price, information, assortment) of the internet shop lead a consumer's positive emotions for apparel shopping. Limited assortment variety of product induce negative emotions. Third, positive and negative emotions that consumer experienced for apparel shopping influence attitude toward the internet shop.

• The Journal of Information Technology and Database
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• v.2 no.2
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• pp.55-69
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• 1995

전문직 종사자는 많은 정보활동을 수행한다. 특히 끊임없이 변하는 소비자의 욕구에 부응하는 새로운 패션상품을 기획해야하는 머쳔다이저는 의상디자인 능력과 상품기획 능력을 동시에 겸비하고 있어야 한다. 이 두가지 다른 내용을 동시에 흡수할 수 있는 전공교육 프로그램이 마련되어 있지 못한게 국내실정이다. 그리하여 패션 머쳔다이저는 업무수행에서 필요로 하는 정보 및 지식을 끊임없이 수집, 분석하려는 노력을 취해야한다. 이들이 주로 탐색해나가는 정보의 성격이 업무수행성과에 영향을 미치는 가를 판단코자함이 본 연구의 관심주제이다. 정보활동에 관한 기존연구는 개인의 특성, 경험 등이 정보활동 형태에 영향을 주는 요인이리고 지적한다. 본 연구에서는 머쳔다이저가 성장해온 경력외의 분야에 더 많은 정보를 탐색하게되면 보다 합리적인 머쳔다이징 의사결정을 내릴 수 있게되고 또 한 이들의 업무수행 성과도 그에 따라 차이가 날 것이라는 주요가설을 설정하였다. 아울러 이의 검정을 위해 설문조사를 수행하였다. 국내 주요백화점의 특정 지점에 매장을 갖고 있는 의류제조업체의 머쳔다이저를 대상으로 조사한 결과, 본 연구의 주요가설은 채택되었다. 이러한 연구결과는 국내 의류업체가 머쳔다이저를 위한 정보활동 프로그램을 마련할 때 활용될 수 있을 것이다. 본 연구가 패션분야를 떠난 일반적 정보활동 분야에 기여한 점은, 업무를 효과적으로 수행하는데 부족하다고 여겨지는 분야의 정보를 많이 획득해나갈수록 그 활용에 따른 효과가 크게 나타난다는 점이다. 이는 정보활동에 대한 계획수립시 유용하게 적용될 수 있을 것이다.

• Korean Journal of Plant Resources
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• v.17 no.3
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• pp.358-364
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• 2004

Today, in both domestic and foreign markets, various ginseng products are collected. However, the discrimination of kinds of ginseng is not working well because of improper technical management, which has a bad effect on the normal trade of ginseng. Therefore, the author publishes the text, based not only on many years of real experience of ginseng product mangement but also on the study of the features of wild ginseng, Jang Roy and cultivated ginseng.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.427-428
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• 2021

정보통신기술의 발달로 전자상거래의 증가와 소비자들의 제품에 대한 경험과 지식의 공유가 활발하게 진행됨에 따라 소비자는 제품을 구매하기 위한 자료수집, 활용을 진행하고 있다. 따라서 기업은 다양한 기능들을 반영한 제품이 치열하게 경쟁하고 있는 현 시장에서 우위를 점하고자 소비자 리뷰를 분석하여 소비자의 정확한 소비자의 요구사항을 분석하여 제품기획 프로세스에 반영하고자 텍스트마이닝(Text Mining) 기술과 딥러닝(Deep Learning) 기술을 통한 연구가 이루어지고 있다. 본 논문의 기초자료가 되는 데이터셋은 포털사이트의 구매사이트와 오픈마켓 사이트의 소비자 리뷰를 웹크롤링하고 자연어처리하여 진행한다. 감성분석은 딥러닝기술 중 CNN(Convolutional Neural Network), LSTM(Long Short Term Memory) 조합의 모델을 구현한다. 이는 딥러닝을 이용한 제품기획 프로세스로 소비자 요구사항 반영, 경제적인 측면, 제품기획 시간단축 등 긍정적인 영향을 미칠 것으로 기대한다.