• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.461-463
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• 2023

MZ세대를 중심으로 자기관리를 열심히 하는 사람들이 증가함에 따라 화장의 기본이 되는 개인 피부톤(퍼스널 컬러)을 찾는 것이 중요시되고 있다. 현재 대다수 사람은 자신에게 어울리는 퍼스널 컬러를 찾기 위해 높은 비용을 지불하여 전문가를 이용하거나 객관적이고 정량화된 기준 없이 오랜 시간을 투자하여 스스로 퍼스널 컬러를 찾는 등 시간과 비용 측면에서의 한계점을 가지고 있다. 본 논문에서는 이를 보완하기 위해 이미지 기반 인공지능 기술(객체 탐지, 객체 분할, BeautyGAN)을 적용하여 데이터 기반의 정량적인 기준을 생성하고, 퍼스널 컬러에 알맞은 화장품 추천 웹 서비스를 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.963-964
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• 2023

추천 시스템은 사용자의 선호도를 정확히 파악하는 것이 중요하다. 이를 위해 사용자 데이터를 분석하여 추천을 제공하는 협업 필터링 알고리즘을 활용한다. 하지만 상품의 종류와 고객 수가 많아짐에 따라 사용자 선호도 정확도가 떨어지는 문제점이 있다. 이 문제를 해결하기 위해 제안된 방법은 모델 기반 협업 필터링이며, 이는 고객과 사용자의 정보를 직접적으로 추천하는 대신 모델을 학습시키는데 활용된다. 이에 논문은 추천시스템에서 자주 사용되는 모델 협업 필터링 기반 SVD 모델을 학습 전에 하이퍼파라미터를 조절하여 모델에 추정 정확도 값인 RMSE를 측정한다.

• Journal of Global Scholars of Marketing Science
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• v.20 no.3
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• pp.269-277
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• 2010

Previous studies have shown that the most important factor affecting customer loyalty in the service industry is service quality. However, on the subject of whether service quality has a direct or indirect effect on customer loyalty, scholars' views apparently vary. Some studies suggest that service quality has a direct and fundamental influence on customer loyalty (Bai and Liu, 2002). However, others have shown that service quality not only directly affects customer loyalty, it also has an indirect impact on customer loyalty by influencing customer satisfaction and perceived value (Cronin, Brady, and Hult, 2000). Currently, there are few domestic articles that specifically address the relationship between service quality and customer loyalty in the mobile communication industry. Moreover, research has studied customer loyalty as a whole variable, rather than breaking it down further into multiple dimensions. Based on this analysis, this paper summarizes previous study results, establishes an effect mechanism model among service quality, customer satisfaction, and customer loyalty in the mobile communication industry, and presents a statistical test on model assumptions by using customer investigation data from Heilongjiang Mobile Company. It provides theoretical guidance for mobile service management based on the discussion of the hypothesis test results. For data collection, the sample comprised mobile users in Harbin city, and the survey was taken by random sampling. Out of a total of 300 questionnaires, 276 (92.9%) were recovered. After excluding invalid questionnaires, 249 remained, for an effective rate of 82.6 percent for the study. Cronbach's ${\alpha}$ coefficient was adapted to assess the scale reliability, and validity testing was conducted on the questionnaire from three aspects: content validity, construct validity. and convergent validity. The study tested for goodness of fit mainly from the absolute and relative fit indexes. From the hypothesis testing results, overall, four assumptions have not been supported. The ultimate affective relationship of service quality, customer satisfaction, and customer loyalty is demonstrated in Figure 2. On the whole, the service quality of the communication industry not only has a direct positive significant effect on customer loyalty, it also has an indirect positive significant effect on customer loyalty through service quality; the affective mechanism and extent of customer loyalty are different, and are influenced by each dimension of service quality. This study used the questionnaires of existing literature from home and abroad and tested them in empirical research, with all questions adapted to seven-point Likert scales. With the SERVQUAL scale of Parasuraman, Zeithaml, and Berry (1988), or PZB, as a reference point, service quality was divided into five dimensions-tangibility, reliability, responsiveness, assurance, and empathy-and the questions were simplified down to nineteen. The measurement of customer satisfaction was based mainly on Fornell (1992) and Wang and Han (2003), ending up with four questions. Based on the study’s three indicators of price tolerance, first choice, and complaint reaction were used to measure attitudinal loyalty, while repurchase intention, recommendation, and reputation measured behavioral loyalty. The collection and collation of literature data produced a model of the relationship among service quality, customer satisfaction, and customer loyalty in mobile communications, and China Mobile in the city of Harbin in Heilongjiang province was used for conducting an empirical test of the model and obtaining some useful conclusions. First, service quality in mobile communication is formed by the five factors mentioned earlier: tangibility, reliability, responsiveness, assurance, and empathy. On the basis of PZB SERVQUAL, the study designed a measurement scale of service quality for the mobile communications industry, and obtained these five factors through exploratory factor analysis. The factors fit basically with the five elements, indicating the concept of five elements of service quality for the mobile communications industry. Second, service quality in mobile communications has both direct and indirect positive effects on attitudinal loyalty, with the indirect effect being produced through the intermediary variable, customer satisfaction. There are also both direct and indirect positive effects on behavioral loyalty, with the indirect effect produced through two intermediary variables: customer satisfaction and attitudinal loyalty. This shows that better service quality and higher customer satisfaction will activate the attitudinal to service providers more active and show loyalty to service providers much easier. In addition, the effect mechanism of all dimensions of service quality on all dimensions of customer loyalty is different. Third, customer satisfaction plays a significant intermediary role among service quality and attitudinal and behavioral loyalty, indicating that improving service quality can boost customer satisfaction and make it easier for satisfied customers to become loyal customers. Moreover, attitudinal loyalty plays a significant intermediary role between service quality and behavioral loyalty, indicating that only attitudinally and behaviorally loyal customers are truly loyal customers. The research conclusions have some indications for Chinese telecom operators and others to upgrade their service quality. Two limitations to the study are also mentioned. First, all data were collected in the Heilongjiang area, so there might be a common method bias that skews the results. Second, the discussion addresses the relationship between service quality and customer loyalty, setting customer satisfaction as mediator, but does not consider other factors, like customer value and consumer features, This research will be continued in the future.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.51-67
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• 2009

Developing an agile recommender system for nomadic users has been regarded as a promising application in mobile and ubiquitous settings. To increase the quality of personalized recommendation in terms of accuracy and elapsed time, estimating future context of the user in a correct way is highly crucial. Traditionally, time series analysis and Makovian process have been adopted for such forecasting. However, these methods are not adequate in predicting context data, only because most of context data are represented as nominal scale. To resolve these limitations, the alignment-prediction algorithm has been suggested for context prediction, especially for future context from the low-level context. Recently, an ontological approach has been proposed for guided context prediction without context history. However, due to variety of context information, acquiring sufficient context prediction knowledge a priori is not easy in most of service domains. Hence, the purpose of this paper is to propose a novel context prediction methodology, which does not require a priori knowledge, and to increase accuracy and decrease elapsed time for service response. To do so, we have newly developed pattern-based context prediction approach. First of ail, a set of individual rules is derived from each context attribute using context history. Then a pattern consisted of results from reasoning individual rules, is developed for pattern learning. If at least one context property matches, say R, then regard the pattern as right. If the pattern is new, add right pattern, set the value of mismatched properties = 0, freq = 1 and w(R, 1). Otherwise, increase the frequency of the matched right pattern by 1 and then set w(R,freq). After finishing training, if the frequency is greater than a threshold value, then save the right pattern in knowledge base. On the other hand, if at least one context property matches, say W, then regard the pattern as wrong. If the pattern is new, modify the result into wrong answer, add right pattern, and set frequency to 1 and w(W, 1). Or, increase the matched wrong pattern's frequency by 1 and then set w(W, freq). After finishing training, if the frequency value is greater than a threshold level, then save the wrong pattern on the knowledge basis. Then, context prediction is performed with combinatorial rules as follows: first, identify current context. Second, find matched patterns from right patterns. If there is no pattern matched, then find a matching pattern from wrong patterns. If a matching pattern is not found, then choose one context property whose predictability is higher than that of any other properties. To show the feasibility of the methodology proposed in this paper, we collected actual context history from the travelers who had visited the largest amusement park in Korea. As a result, 400 context records were collected in 2009. Then we randomly selected 70% of the records as training data. The rest were selected as testing data. To examine the performance of the methodology, prediction accuracy and elapsed time were chosen as measures. We compared the performance with case-based reasoning and voting methods. Through a simulation test, we conclude that our methodology is clearly better than CBR and voting methods in terms of accuracy and elapsed time. This shows that the methodology is relatively valid and scalable. As a second round of the experiment, we compared a full model to a partial model. A full model indicates that right and wrong patterns are used for reasoning the future context. On the other hand, a partial model means that the reasoning is performed only with right patterns, which is generally adopted in the legacy alignment-prediction method. It turned out that a full model is better than a partial model in terms of the accuracy while partial model is better when considering elapsed time. As a last experiment, we took into our consideration potential privacy problems that might arise among the users. To mediate such concern, we excluded such context properties as date of tour and user profiles such as gender and age. The outcome shows that preserving privacy is endurable. Contributions of this paper are as follows: First, academically, we have improved sequential matching methods to predict accuracy and service time by considering individual rules of each context property and learning from wrong patterns. Second, the proposed method is found to be quite effective for privacy preserving applications, which are frequently required by B2C context-aware services; the privacy preserving system applying the proposed method successfully can also decrease elapsed time. Hence, the method is very practical in establishing privacy preserving context-aware services. Our future research issues taking into account some limitations in this paper can be summarized as follows. First, user acceptance or usability will be tested with actual users in order to prove the value of the prototype system. Second, we will apply the proposed method to more general application domains as this paper focused on tourism in amusement park.

• Korea Journal of Hospital Management
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• v.9 no.2
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• pp.46-75
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• 2004

This research anticipated on acknowledging the inpatients factors in choosing which hospital for the geriatric hospital and general hospital they would prefer to go to the analization of different factors in patients satisfaction, and the relation between satisfactory standards and the patients intentions on recommendation or re-visiting the hospital. The statistical data was based upon the 359 question and answer papers that were done by inpatients that were hospitalized in two geriatric hospitals and two general hospitals, and the methods used for analyzing were frequency, t-test, factor analysis, and hierarchical multiple regression. The results are as follows. 1. The factors on choosing hospitals between geriatric hospital and general hospitals were different. The priority for the geriatrics was kindness, and then considerate nursing, and the reliance of treatment. The patients of general hospitals looked first for reliance of treatment, reputation and history of the hospital, and the kindness of the staff. The kindness of the staff, good nursing, and easy procedures were the primary factors of choosing geriatric hospital. 2. The four primary factors in choosing which hospital patients would go to were the predominance of the facilities, kindness and convenience, the reliance and proximity of medical treatment, and recommendation. The patients in the geriatric hospital first looked for kindness and convenience, second the reliance and proximity of medical treatment, third predominance of facilities, and last recommendation. The general hospitals main priority was the reliance and proximity of medical care, second predominance of facilities, kindness and hospitality, and last recommendation. 3. The satisfaction rate was higher in the geriatric hospital compared to general hospitals, but the satisfactory of factors were very similar. Patients in the geriatric hospital were pleased with the hospital staffs kindness, quick nursing and the improvement of inconvenient matters, and clear diagnosis of the doctors. The general hospital patients were satisfied with the hospital staffs clear explanation and accurate diagnosis 4. The analysis in the satisfactory factors turned out to be the environment of the hospital, kindness of the staff, and convenience. Both the patients of the geriatric hospital and general hospitals were very pleased with the kindness of the hospital staff. Ranking second and third was convenience and service for the geriatric hospital, and environment of the hospital and convenience for the general hospital. 5. According to a rank of multiple recurrent analysis of the patients satisfaction and the intention of re-visiting in addition to intention of solicitation, in the case of a geriatric hospital, when the intention of re-visiting is the dependent variable, the first stage shows that the less insurance the patient has, the higher was the intention of re-visiting. In the second stage, the more satisfied the patient is of the staffs kindness, the higher was the intention of re-visiting. Further more, when the intention of solicitation is the dependent variable, the first stage shows that not all the independent variables were significant, but the second stage shows that the more satisfied the patient is of the staffs kindness and the hospital along with the medical treatment expenses, the higher was the intention of solicitation. 6. In the first stage of a rank of multiple recurrent analysis of the satisfaction of the general hospital and the intention of re-visiting, not all the variables were significant, but in the second stage, all the satisfaction by factors were significant. Moreover, when the intention of solicitation was the dependent variable, the first stage shows not all the variables were significant, but in the second stage, all the satisfaction by factors were significant. That is to say, in the case of a general hospital, the satisfaction of the hospital and the medical treatment expenses were high, and the more satisfied the patient is of the hospitals environment and the staffs kindness, the intention of re-visiting and the intention of solicitation was higher.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.

• Journal of the Korean Society of School Health
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• v.2 no.1
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• pp.91-107
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• 1989

This study was designed to evaluate current level of school health practice in Chonbuk province and to analyze the relationship between school health practice and variables. All the subjects in this study were 140 schools themselves in Chonbuk province. Survey data was collected through the interviewed checklists from the widly accepted school health responsibilities of administration and practice and the direct observation by the interviewer. It was conducted from 1st of Nov. to 17 th of Dec, 1988. The major findings of this study are as follows: A. Level of school health practice was relatively low in score (Mean=64.5). $\cdot$ Healthful School Living -76.14 $\cdot$ School Health Service -71.29 $\cdot$ School Health Instruction -47.98 B. Strengths and Weakness field in School Health Practice. 1. Healthful School Living: Strengths: Waste disposal, Seating, Playground. Weakness: School site, Safety control. 2. School Health Service : Strenths : Health Appraisal, Follow up and Counseling. Weakness: Dental Health, Prevention and Control of Communicable Disease, Facilities and Equipment of Health Clinic. 3. School Health Instruction : Strength : None, Weakness : Program Organization, Curriculum Planning and Evaluation, Curriculum Content, Instructional Aids. C. Significance between degree of School Health Practice and Variables. 1. Healthful School Living : (1) Toilet : Area (p<0.001), No.of Class (p<0.001), School Nurse (p<0.05) (2) Water Supply : School Nurse (p<0.05) (3) Safety Control : School Nurse (p<0.05) 2. School Health Service : (1) Health Appraisal : School Nurse (p<0.05) (2) Follow up and Counseling : School Nurse (p<0.001) (3) Dental Health : Area (p<0.05), Level of School (p<0.05) (4) Prevention and Control of Communicable Disease : Level of School (p<0.001), School Nurse (p<0.05) (5) Emergency Care : Area (p<0.001), No. of Class (p<0.001), School Nurse(p<0.001) (6) Facilities and Equipment of Clinic : Level of School (p<0.001), No.of Class (p<0.001), School Nurse (p<0.001) 3. School Health Instruction: (1) Program Organization : No. of Class (p<0.05), School Nurse (p<0.001) (2) Curriculum Planning land Evaluation : School Nurse (p<0.001) (3) Instructional Aids : Level of School (p<0.001), School Nurse (p<0.05) Recommendation for the Improvement of School Health Practice are as follows : A. There should be further study to strengthen the school health practice, especially in the field of school health instruction. B. It is strictly required to employ and utilize school nurse at each school level not only for the school health service but also for the school health in struction. C. There should be much considerations about adequate size and easily accessible distance in school site.

• Journal of Distribution Science
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• v.12 no.11
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• pp.67-76
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• 2014

Purpose - PB (Private Brand) refers to the product for which the distribution company plans the production independently, consigns the production to the manufacturer, or attaches the self-developed trademark and sells it. To reinforce competitiveness in such a market environment, diverse products development, systematic management activities, and marketing efforts to analyze and understand the consumers' behavior regarding PB products are emphasized. Therefore, this study aims to investigate the relationships among PB product attributes, consumption emotion, brand attitude, and brand loyalty in general supermarkets. First, PB product attributes were defined using the five categories of perceived price, store image, familiarity, perceived service, and perceived quality, based on preceding studies. This study examined the influence of PB product attributes on consumption. Further, this study examined the relation among consumption emotion, brand attitude, and brand loyalty. This study provides more detailed and concentrated strategic implications. Research design, data, and methodology - In this study, the research model was designed to examine the relation among PB product attributes, consumption emotion, brand attitude, and brand loyalty. For the data collection method, the questionnaire survey comprised multiple items for each component and the direct interview method was employed. To collect data, the questionnaire survey was conducted for customers who personally visited the general supermarket after verifying the PB product purchase experience. The questionnaire survey was performed for one month, May 2014. A total of 300 questionnaires were distributed and 240 questionnaires were used for the analysis, excluding the unanswered and insincere questionnaires. The data were analyzed using SPSS ver. 20.0. Results - First, PB product attributes had a significantly positive effect on consumption emotion. The PB product attributes perceived by the customer at the point of service contact are important to form the positive consumption emotion. Second, consumption emotion had a significantly positive effect on brand attitude. Third, the consumption emotion had a significantly positive effect on brand loyalty. Such consumption emotion is an important factor in causing the positive evaluation on the brand attitude perceived by the customer. Fourth, brand attitude had a significantly positive effect on brand loyalty. The consumption emotion was positively represented to invoke the relational continuance behavior. The relational continuance behavior accompanies the repetition of purchase, word of mouth, and recommendation activities, and influences trust regarding the brand, for which the customer maintains the transaction continuously. Conclusions - The PB product attributes perceived by the customer at the point of service contact are important factors to form the positive consumption emotion. Based on this result, the discount store service provider would prepare the measures that can make the customer recognize the positive value, and make more detailed efforts. Consumption emotion is an important factor to cause the positive evaluation on the brand attitude perceived by the customer. Based on this result, the general supermarket must make efforts to provide fun or convenience in the purchase process for consumers.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.131-138
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• 2015

One of the most conspicuous characteristics of a business model that pursues expanding customer relationship is that it tries to lock in customers by encouraging them to repeat purchase in the long-term with the help of "Follow" function in Social Networking Service (SNS), which enables producers to automatically register the customers as potentially important ones and to offer them customized marketing services. In the value chain of the agriculture sector, producers of agricultural products can use SNS functions to provide loyal customers with valuable information and experiences such as the real-time information of their farm and products, hidden stories about the whole process from seeding to harvesting, and the storage and cooking methods of their products. These activities help the producers invoke customers' desire to live in the farm and to grow the products themselves. They also raise the accessibility of the producers' websites as customers are able to share a variety of news and knowledge such as the release of new products. This means that the producers's websites are now functioning to enable the producers to perform sales and promotion related activities. It is a big leap from the traditional e-commerce business model where sales and promotion of a product were separated and could be connected only through outside links. This two-way, viral characteristics of marketing services using SNS facilitate customers to share product information and their purchase experience with each other, which leads to more effective and efficient communication within the customer community.

• Culinary science and hospitality research
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• v.18 no.5
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• pp.16-32
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• 2012

The purposes of this study were to understand how franchisor's influence strategies influenced franchisee's boundary spanning behaviors and how franchisor's entrepreneurship influenced franchisee's boundary spanning behaviors. This study also analyzed whether franchisor's entrepreneurship played a moderating role in the causal relationship between franchisor's influence strategies and franchisee's boundary spanning behaviors. Based on a total of 698 self-administered questionnaires obtained from franchisees(food-service unit owners or managers) in Korea, frequency analysis, exploratory factor analysis, reliability analysis and hierarchical regression analysis were conducted. The research findings showed results that firstly, promise (${\beta}$=0.292), threat (${\beta}$=-0.256), recommendation (${\beta}$=0.200), information exchange (${\beta}$=0.359), request(${\beta}$=-0.097) and legalistic plea(${\beta}$=-0.137) had a significant effect on franchisee's boundary spanning behaviors and secondly, franchisor's entrepreneurship had a significant positive effect on franchsee's boundary spanning behavior. In addition, the effects of franchisor's promise(${\beta}$=0.168) and threat(${\beta}$=-0.075) on franchisee's boundary spanning behaviors were found to be partially moderated by franchisor's entrepreneurship. Franchisees wanted franchisors to execute a high level of entrepreneurship and deliver a promise in an influence strategy. Limitations and future research directions were also discussed.