• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.386-394
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• 2011

Recently it is difficult to draw an improvement for customer satisfaction because the ratio of satisfied customers increases in customer satisfaction survey. In addition, the effectiveness of practical application of customer satisfaction survey decreases due to its constitution limitation on its data analysis. In order to solve these problems, it is necessary to develop a novel research to identify the strategy meanings and find dissatisfied factors of satisfied customers using the satisfied customers' reclassification. This study focuses on the satisfied customer segmentation based on Latent Class Analysis (LCA). The case study with high-speed internet service customers show that the satisfied customers are divided into three subgroups using LCA and we draw meaning results such as satisfaction and dissatisfaction factors through analyzing each group. This study is expected to play the role as the groundwork for the revitalization of customer satisfaction survey as well as improving customer satisfaction management.

• Journal of Korean Academy of Nursing
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• v.49 no.6
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• pp.701-712
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• 2019

Purpose: Despite the high drinking rates and the complexity of drinking behaviors in adolescents, insufficient attention has been paid to their drinking patterns. Therefore, we aimed to identify patterns of adolescent drinking behaviors and factors predicting the distinct subgroups of adolescent drinking behaviors. Methods: We analyzed nationally representative secondary data obtained in 2017. Our final sample included 24,417 Korean adolescents who had consumed at least one glass of alcohol in their lifetime. To investigate patterns of drinking behaviors, we conducted a latent class analysis using nine alcohol-related characteristics, including alcohol consumption levels, solitary drinking, timing of drinking initiation, and negative consequences of drinking. Furthermore, we investigated differences in demographics, mental health status, and characteristics of substance use across the latent classes identified in our study. To do so, we used the PROC LCA with COVARIATES statement in the SAS software. Results: We identified three latent classes of drinking behaviors: current non-drinkers (CND), binge drinkers (BD), and problem drinkers (PD). Compared to the CND class, both BD and PD classes were strongly associated with higher academic year, lower academic performance, higher levels of stress, suicidal ideation, lifetime conventional or electronic cigarette use, and lifetime use of other drugs. Conclusion: Health professionals should develop and implement intervention strategies targeting individual subgroups of drinking behaviors to obtain better outcomes. In particular, health professionals should consider different characteristics across subgroups of adolescent drinking behaviors when developing the interventions, such as poor mental health status and other substance use among binge and problem drinkers.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.3
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• pp.237-254
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• 2021

Objectives: This study aims to classify the latent profiles in the exposure to hazard factors of salaried employees and test the determinants. Methods: Latent profile analysis(LPA) was conducted using data from the fifth Korean Working Conditions Survey(KWCS). 30,050 of salaried employees were the subjects of this study. After classifying the employees, multinomial logistic regression was used to test the determinants. Results: Salaried employees were classified with three latent profiles based on the exposure to the hazard factors. Employees included in class 1(32.8%) tend to experience low level of physical hazard factors, moderate level of psychological hazard factors, and high level of office work hazard factors. Employees included in class 2(61.8%) tend to be exposed to the moderate to high level of physical hazard factors, moderate to low level of psychological hazard factors, and low level of office work hazard factors. Employees included in class 3(5.4%) tend to experience high level of psychological and physical hazard factors, and moderate level of office work hazard factors. After classification, the demographic, health-, and employment-related variables were tested. Conclusions: This study clarified the features of each class, and proved that employees in class 3 are quite hazardous in that they are exposed to physical and psychological hazard factors much more frequently than other employees. Thus, this study can be used in predicting the high-risk employees and taking preemptive measures for preventing industrial accidents.

• Korean Journal of Childcare and Education
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• v.16 no.1
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• pp.115-143
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• 2020

Objective: The purpose of this study was to examine underlying types of developmental trajectories of adaptation to child care among infants and toddlers. This study also aimed to identify latent classes in their child care adaptation types in order to find predictors that account for individual differences. Methods: Participants were 420 mothers of infants and toddlers and 123 teachers. The levels of child care adaptation of participating infants and toddlers were rated monthly from early April to June, 2019. The collected data were analyzed using growth mixture modeling, latent class analysis and multinominal logistic analysis. Results: The results of growth trajectories of child care adaptation showed there were two to four latent groups by dimension of child care adaptation. Also, the groups of individual dimensions of child care adaptation were classified into three latent classes, which were 'complying and positive group', 'negative group', and 'individualized group. Multinominal logistic analysis revealed that children's age, gender, and temperament differentiated the three latent classes of adaptation to child care. Conclusion/Implications: The results show individual characteristics that infants and toddlers possess should be prudently considered in order for successful adaptation to child care.

• Journal of the Korea Society of Computer and Information
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• v.28 no.3
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• pp.137-148
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• 2023

The purpose of this study is to classify the potential types of mental health of mothers of multicultural youth by applying Latent Profile Analysis, analyze the influence of predictors, and find out how differences in potential types affect parental efficacy. To this end, panel data for the 9th year (2019) of the Multicultural Youth Panel Survey (MAPS) were used. As a result of the analysis, first, the mental health types of mothers of multicultural adolescents were analyzed in the order of 'middle risk type of mental health'(class3) > 'high risk type of self-esteem'(class1) > 'high risk type of mental health'(class4) > 'cultural adaptation and daily life stress'(class2). Second, compared to the "class 1" group, the lower the family economy level of multicultural youth mothers, the lower the educational background of multicultural youth fathers (husbands) graduate from middle school, the lower the level of Korean, and the lower the level of communication with children, the higher the odds of belonging to the 'mental health medium risk' group (Ods). Third, compared to the 'middle risk type of mental health'(class3) and 'high risk type of mental health'(class4), the 'high risk type of self-esteem'(class1) group was found to have a significant positive (+) effect on parental efficacy.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.335-346
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• 2015

The electronic commerce site (EC site) has become an important marketing channel where consumers can purchase many kinds of products; their access logs, including purchase records and browsing histories, are saved in the EC sites' databases. These log data can be utilized for the purpose of web marketing. The customers who purchase many product items are good customers, whereas the other customers, who do not purchase many items, must not be good customers even if they browse many items. If the attributes of good customers and those of other customers are clarified, such information is valuable as input for making a new marketing strategy. Regarding the product items, the characteristics of good items that are bought by many users are valuable information. It is necessary to construct a method to efficiently analyze such characteristics. This paper proposes a new latent class model to analyze both purchasing and browsing histories to make latent item and user clusters. By applying the proposal, an example of data analysis on an EC site is demonstrated. Through the clusters obtained by the proposed latent class model and the classification rule by the decision tree model, new findings are extracted from the data of purchasing and browsing histories.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.324-333
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• 2018

The aim of this study was to investigate the latent classes and predictors of chronic diseases such as hypertension, dyslipidemia, arthritis, thyroid disease, depression, atopy, allergy, and diabetes. The subjects of this study were Korean citizens who participated in the Korea National Health and Nutrition Examination Survey in 2014. Stratified cluster sampling method was used with a sample size of 7,550. Latent hierarchy analysis was applied to this data. Four classes were identified. Class 1 consisted of participants with hypertension and diabetes. Class 2 consisted of participants with atopy and allergies. Class 3 consisted of participants with dyslipidemia, arthritis, thyroid disease, and depression. Class 4 consisted of participants without any chronic diseases. In comparing Class 1 to Class 4, age, physical activity, self-management, obesity, and presence of high cholesterol were found to be significant. In comparing Class 2 to Class 4, gender, age, and education level were significant. When Class 3 was compared to Class 4, gender, age, pain and discomfort, as well as high cholesterol were found to be significant. Diabetes and hypertension should be treated as comorbid conditions, applying integrated treatments involving effective drug treatment, diet, and physical activity programs. Atopy was found to be strongly correlated with allergies. Thyroid disease was found to coexist with dyslipidemia and arthritis, along with having a strong correlation to depression. Age-appropriate preventive measures can help reduce the risk of chronic diseases.

• The Mathematical Education
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• v.63 no.1
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• pp.19-33
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• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• Research in Community and Public Health Nursing
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• v.33 no.1
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• pp.74-83
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• 2022

Purpose: The purpose of this study was to identify latent classes of health-related quality of life trajectories in middle-aged women and investigate predictors for latent classes. Methods: This study utilized data from the 2^nd, the 4^th to the 7^th Korean Longitudinal Survey of Women & Families. The subjects included 1,351 women aged 40~45 years. The data was analyzed using latent class growth analysis and logistic regression. Results: Two trajectories were identified for health-related quality of life in middle-aged women; 'persistently good' and 'increasing' groups. Predictors for the 'increasing' group were lower economic status, higher depression, and lower perceived health status. Conclusion: This study showed that characteristics of the individual, symptom status, and health perceptions were associated with health-related quality of life in middle-aged women. It is necessary to provide effective intervention for latent classes of health-related quality of life trajectories based on physical, mental, and social factors.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.435-445
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• 2007

This paper addresses for the first time the use of complete data information criteria in unsupervised learning of the Naive-Bayes model. A Monte Carlo study sets a large experimental design to assess these criteria, unusual in the Bayesian network literature. The simulation results show that complete data information criteria underperforms the Bayesian information criterion (BIC) for these Bayesian networks.