• The Journal of Korean Philosophical History
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• no.52
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• pp.393-424
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• 2017

This study investigates the relationship between South Korean youths' Confucian values and sense of citizen ethics while presenting outlook on the sense of citizen ethics based on the theory of human nature. The purpose of this study, by doing so, is to present educational measures. For this purpose, empirical research method was applied in this study. In the empirical study, youths were surveyed and the answers were statistically analyzed and discussed with a view to achieve the study purpose. In the empirical research part of the study, Korean youths' awareness on Confucian values was examined along with its relationship with the sense of citizen ethics. The effect of Confucian values on sense of citizen ethics and their relationship were analyzed to evaluate the receptivity of youths on Confucian ideas and usefulness of sense of citizen ethics. This study investigated a total of final 311 sets of data from male and female students at middle and high schools located in Seoul, Gyeonggi, South Korea. First, to identify the youths' Confucian values and level of sense of citizen ethics, descriptive statistical analysis was conducted. As a result, the survey subjects were found to have, concerning the Confucian values, world view M=3.54, human relations view M=3.66, morality cultivation M=3.76, and social order M=3.45, higher than 3.0 to represent positive levels. The morality cultivation, in particular, was recorded the highest among all whereas the social order was relatively lower, which represents the degree of relying on Confucian values to establish social order. Second, the sub-variables of Confucian values were verified according to the personal characteristics of the surveyed youths and differences in their entire perception was investigated. As a result, according to gender, morality cultivation was found higher in female students (M=3.85) than in male students (M=3.64). According to the subjective economic level of their household, world view was found higher in upper class (M=3.98) than middle-low class (M=3.25) and low class (M=3.22) while human relations view was found higher in middle-upper class (M=3.79) than low class (M=3.46). As for the family type, morality cultivation was found higher in extended family (M=3.83) than nuclear family (M=3.62); and social order was higher in extended family (M=3.54) than nuclear family (M=3.36). Third, to verify the study theme of identifying the effects of youths' Confucian values on sense of citizen morality, hierarchical regression analysis was employed in this study, which used the multi-level model of multiple regression analysis. As a result, the Confucian values was found to have significant positive (+) correlations with the entire sense of citizen ethics in order of human relations view(${\beta}=.499$), world view(${\beta}=.412$), social order(${\beta}=.341$), and morality cultivation(${\beta}=.241$). Confucian value showed significant positive (+) correlations with autonomy in order of morality cultivation(${\beta}=.458$), human relations view(${\beta}=.454$), social order(${\beta}=.362$), and world view(${\beta}=.158$). Confucian values was found to have significant positive (+) correlations with community spirit in order of human relations view(${\beta}=.295$), social order(${\beta}=.281$), and morality cultivation(${\beta}=.232$). As shown in the findings above, youths' Confucian values was found to have significant positive (+) effects on the sense of citizen ethics. It is noted that the higher the Confucian values, the more positive the sense of citizen ethics would be. Consequentially, the Confucian values was identified to play an important role in the sense of citizen ethics in the modern society. Based on this analysis, this study presented specific measures - the necessity and possibility of education on sense of citizen ethics under the theory of human nature. To this end, this study proposed to find an optimal interface between the contemporary sense of citizen ethics and Confucian ethics through the respect for human life and nature, man of virtue as the ideal human model, and united society as a desirable society model.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.