• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.57-64
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• 2018

User-based collaborative filtering is a method of recommending an item to a user based on the preference of the neighbor users who have similar purchasing history to the target user. User-based collaborative filtering is based on the fact that users are strongly influenced by the opinions of other users with similar interests. Item-based collaborative filtering is a method of recommending an item by comparing the similarity of the user's previously preferred items. In this study, we create a recommendation model using user-based collaborative filtering and item-based collaborative filtering with consumer's consumption data. Collaborative filtering is performed by using RFM (recency, frequency, and monetary) technique with purchasing data to recommend items with high purchase potential. We compared the performance of the recommendation system with the purchase amount and the performance when applying the RFM method. The performance of recommendation system using RFM technique is better.

• Fashion & Textile Research Journal
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• v.25 no.1
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• pp.41-51
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• 2023

This study attempted to analyze the context characteristics and consumer characteristics that affect fashion curation shopping. The data used for this study were 223 questionnaires targeting male and female college students in their 20s in Busan and South Gyeongsang Province who had had the curated shopping experience in the latest three months. The SPSS program was used for the data analysis, and a reliability measurement, factor analysis, multiple regression analysis, T-test, and one-way ANOVA were conducted. The results were as follows. First, fashion curation shopping exhibited three factors: product subscription, marketing use, and product recommendation shopping. Furthermore, the context characteristics had sub concepts of five factors: selection, sharing, experience, discovery, and storage. Second, the context characteristics (selection, sharing, experience, discovery, and storage) had a significant influence on product subscription, marketing use, and product recommendation, which belong to the curation shopping category. Third, the fashion consumers' price sensitivity, trend sensitivity, and product knowledge had a deep impact on the marketing use and product recommendation. Fourth, there was no difference in the fashion curation shopping by male and female consumers and the average monthly fashion shopping frequency, and there were differences in shopping cost and time. This study can analyze the context and consumer characteristics that affect fashion curation shopping to establish an efficient fashion curation shopping system in practical terms. Additionally, academically, it can be proposed as basic data on the development of measurement tools for analyzing consumer behavior that prefers fashion curation shopping.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.

• The Research Journal of the Costume Culture
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• v.17 no.3
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• pp.367-382
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• 2009

The aim of the current study was to investigate the impact of store attribute satisfaction on intentions of revisit and recommendation among clothing consumers. The data were collected from 319 consumers through survey and frequency analysis, reliability analysis, factor analysis, and multiple regression analysis were used to obtain results. The findings were as follows: 1. From factor analysis, seven factors were distracted: Fact 1(brand and price), Fact 2(store's facility and environment), Fact 3(product), Fact 4(transportation convenience and access), Fact 5(selling and advertisement), Fact 6(store's atmosphere), and Fact 7(salesman's service). 2. Four factors had statistically significant influence on overall satisfaction of clothing consumers. The most influential factor was Fact 2(store's facility and environment) and Fact 5(selling and advertisement), Fact 1(brand and price), and Fact 4(transportation convenience and access) showed their effects on overall satisfaction in an hierarchical rank-order following Fact 2. 3. Four factors such as Fact 2(store's facility and environment), Fact 1(brand and price), Fact 4(transportation convenience and access) and Fact 5(selling and advertisement) in an hierarchical rank-order from Fact 1 had statistically significant impact on intentions of revisit. 4. Six factors such as Fact 1(brand and price), Fact 2(store's facility and environment), Fact 3(product), Fact 5(selling and advertisement), Fact 6(store's atmosphere), and Fact 7(salesman's service) in an hierarchical rank-order from Fact 1 had statistically significant influence on the intention of recommendation. 5. The results further showed that among seven factors, Fact 1(brand and price), 'Fact 2(store's facility and environment), and Fact 5(selling and advertisement) had impact on both the intention of revisit and the intention of recommendation.

• Fashion & Textile Research Journal
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• v.23 no.5
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• pp.586-597
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• 2021

Personalized product recommendation service is receiving attention as a new marketing strategy while supporting consumer information search and purchasing decisions. This study attempted to verify the effect of self-reference on service use behavior through the dual path of cognitive attitude and emotional attachment. Using convenience sampling, an online survey was conducted with 324 women who were in their 20s and 30s. After collecting and compiling the survey data, the reliability and validity of variables constituting the conceptual research model were verified through confirmatory factor analysis using AMOS 22.0. Next, the significance of sequentially mediated pathways was verified using Process 3.5 Model 80. The results showed that self-referencing not only significantly affects service use intention by simply mediating cognitive attitudes but also sequentially mediates cognitive attitudes and additional information search. Furthermore, self-referencing was significant as an indirect path to service use intention by mediating additional information search. However, in the path mediated by emotional attachment, self-referencing was considered as a simple mediated path leading to service usage intention. These results indicate a dual path in the psychological mechanism, through cognitive and emotional evaluation, that prompts consumer behavioral responses to the personalized product information provided in the shopping process.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.157-167
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• 2021

The study analyzes the factors affecting the intention and recommendation to use the mobile banking applications of 314 customers from Vietnam. The study analyzes 7 factors affecting the intention and recommendation to use the mobile banking applications of customers from Vietnam, including (i) Perceived risk; (ii) Perceived ease of use; (iii) Perceived usefulness; (iv) Attitude; (v) Perceived trust; (vi) Social image; and (vii) Innovativeness. Besides, the study also analyzes 4 variables that reflect the customer's demographics, including gender, age, education, and occupation, and 6 variables describing the behavior of customers using mobile banking applications. The study findings indicate that the following factors (i) Innovativeness; (ii) Attitude; (iii) Perceived risk; (iv) Perceived ease of use, and (v) Perceived trust have the most significant impact on customers' behavior of using mobile banking applications in emerging markets such as Vietnam in the context of prolonged pandemic and continuous lockdown in many provinces and cities. The study is also of great value to studies on behavior changes among customers using mobile banking applications after the COVID-19 pandemic in Vietnam. The study will provide additional empirical evidence useful to bank administrators in motivating customers to use mobile banking applications, helping develop a digital economy in Vietnam.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.5
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• pp.903-913
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• 2015

The Korea Agency of Education, Promotion and Information Service in Food, Agriculture, Forestry and Fisheries launched a public data portal service in January 2015. The service provides customized information for consumers through an agri-food recommendation system built-in portal service. The recommendation system has fallowing characteristics. First, the system can increase recommendation accuracy by using a wide variety of agri-food related data, including SNS opinion mining, consumer's purchase data, climate data, and wholesale price data. Second, the system uses segmentation method based on consumer's lifestyle and megatrends factors to overcome the cold start problem. Third, the system recommends agri-foods to users reflecting various preference contextual factors by using recommendation algorithm, dirichlet-multinomial distribution. In addition, the system provides diverse information related to recommended agri-foods to increase interest in agri-food of service users.

• Korean Journal of Human Ecology
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• v.21 no.6
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• pp.1111-1128
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• 2012

Many social commerce companies are being established and the market for social commerce is also developing quickly. In this study, the utilization, satisfaction, repurchase and recommendation intentions of social commerce consumption were studied, followed by an analysis of different factors that influence repurchase and recommendation intentions. The results of this study are as follows: first, the satisfaction of social commerce products was in the mid-range, with results being consistent across the range of social commerce companies. Secondly, there was a correlation between satisfaction associated with social commerce and repurchase and recommendation intention. Thirdly, there was a correlation between the level of satisfaction and demographic characteristics. Based on the research findings, suggestions are presented for improving consumer policy and education.

• The Korean Journal of Health Service Management
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• v.4 no.1
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• pp.1-10
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• 2010

The purpose of this study is to investigate the effects of provider and consumer characteristics, and patient trust on relational commitment among healthcare customers of an university hospital, and to suggest some implications for improving customer relation management of hospitals. Data were collected from 250 patients of an university hospital located in Ulsan using structured self-administered questionnaire. Major result of the analysis is as follows: First, study variables are significantly varied by age and income among socio-economic factors. Second, assurance, and empathy among provider characteristics and customer satisfaction and reputation among consumer characteristics are found to be significant affecting factors on patient trust. Third, trust affects significantly both on re-visit and recommendation among relationship commitment, while reputation affects on re-visit and customer satisfaction and reputation affect on recommendation. Above results imply that relationship management strategy for enhancing patient trust is crucial to improve competitiveness of hospitals in turbulent competition environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.149-155
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• 2023

Profiling-based recommendation services provide the convenience of easily accessing specialized content for individuals on the user side and provide an important profit model on the corporate side. Despite the utility of these recommendation services, the issues such as personal information infringement and restrictions on consumer options are emerging, and certain regulatory movements for profiling recommendation services are actively underway. Under the circumstance, there are concerns that the introduction of regulations without a close review of regulatory effectiveness and side effects will weaken the competitiveness of domestic companies in the global market. This study systematically analyzed how companies providing profiling-based recommendation services perceive the corresponding regulations.