• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.1
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• pp.9-17
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• 2009

Twenty years have passed since the adoption of natural recreation forests and each forest has its own characteristics. However, there is hardly any classification among the natural recreation forests. The purpose of this study is to classify the forests by considering the supplier's perspective as well as the user's perspective in order to provide fundamental materials for the operation of the natural recreation forests. A factor analysis was conducted to identify the common characteristics of the selected twelve variables by pre-selection and survey of experts. K-means cluster analysis was conducted among those factors to classify the natural recreation forests in Korea. Four factors were drawn after the factor analysis and the factors were named according to the variables and sizes as 'The use performance and visiting condition factor', 'Education and settlement factor', 'Internal activation factor' and 'Potential factor' In addition, the cluster analysis of an $85{\times}4$ matrix was conducted for the points of the drawn factors and the final classification consists of five groups. The results of this study may contribute to providing fundamental materials for the operation and management of natural recreation forests. Also, it may act as a reference when investigating the natural recreation forests of Korea. Proposing the classification natural recreation forests could be helpful in selecting the proper recreation forest in the future. Based on the established model, fundamental materials could be provided to improve the profitability of the natural recreation forests by effectively expanding the number of tourists, creating new natural recreation forests and proper maintenance and management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1654-1662
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• 2011

This paper investigates how does cash holdings have effect on investment-cash flow sensitivity in korea firms over the period 1981-2009. According to $\"{O}$.Arslan et al.(2006), I expect that financially constrained firms have more cash holdings. and financially constrained cash-rich firms are likely to have less investment-cash flow sensitivity especially in the financial crisis period. Using financial constraint classification variables(firm size, dividend, cash holdings), we divide whole sample firms into financially constrained firms and financially unconstrained firms, and then I compare investment-cash flow sensitivity in pre-financial crisis(1981-1996), financial crisis(1997-1998) and after-financial crisis(1999-2009) period. This paper's findings are as follows: First, under no financial constraint classification conditions, cash-poor firms exhibit greater investment-cash flow sensitivity than cash-rich firms do during 1981-2009 period except financial crisis period. These findings support the hypothesis that firms have more cash holdings less investment-cash flow sensitivity except in financial crisis period. In financial crisis period, cash holdings have no effect on investment-cash flow sensitivity. Second, this paper findings are somewhat different as $\"{O}$.Arslan et al.(2006)'s. Under the financial constraint classification conditions, financially unconstrained firms have more investment-cash flow sensitivity rather than constrained firms have. The reason is that both dividend and firm size are not a complete classification criteria variables. And there exists other possible determinants of investment-cash flow sensitivity. Finally, this paper find that there are common determinants of corporate cash holdings in all periods. This paper suggests that cash flow and market to book ratio are positive determinants of corporate cash holdings but short-term debt, investment and firm size are negative determinants of corporate cash holdings.

• Journal of Korean Academy of Nursing
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• v.39 no.3
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• pp.409-421
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• 2009

Purpose: In this research multi-level analysis was done to identify factors related to quality of services. Patient characteristics and organizational factors were considered. Methods: The data were collected from the Health Insurance Review and Assessment Service(HIRA) data base. The sample was selected from 17,234 patients who had been admitted between January 2007 and May 2008 to one of 253 long-term care hospitals located in Seoul, six other metropolitan cities or nine provinces The data were analyzed with SAS 9.1 using multi-level analysis. Results: The results indicated that individual level variables related to quality of service were age, cognitive ability, patient classification, and initial quality scores. The organizational level variables related to quality of service were ownership, number of beds, and turnover rate. The explanatory power of variables related to organizational level variances in quality of service was 23.72%. Conclusion: The results of this study indicate that differences in the quality of services were related to organizational factors. It is necessary to consider not only individual factors but also higher-level organizational factors such as nurse' welfare and facility standards if quality of service in long term care hospitals is to be improved.

• Journal of Information Technology Services
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• v.15 no.2
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• pp.51-63
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• 2016

In this study, we conducted a comparative analysis of R&D investment efficiency and operational efficiency of IT firms using Data Envelopment Analysis (DEA). We categorized thirteen sample firms into two groups-IT manufacturing and IT service-after an extensive literature review on IT industry classification. We adopted an output-oriented two-stage DEA model suggested by Banker et al. (1984) with total asset and R&D investment as input variables. Then, we constructed investment efficiency and operational efficiency by using Return on Equity (ROE) and Return on Asset (ROA) as intervening variables and operating income and Earnings Per Share (EPS) as output variables. The outcome of the analysis is summarized as follows. First of all, IT manufacturing firms were more efficient (57% on average) than IT service firms. To be specific, IT service firms showed decreasing returns to scale (DRS) with diseconomy of scale. In contrast, IT service firms showed higher operational efficiency (81.5% on average) than IT manufacturing firms. Also, we conducted a Mann-Whitney U test to compare the output of IT service firms and IT manufacturing firms. Lastly, we found a negative correlation ($R^2$ = -.754) between R&D investment efficiency and operational efficiency which infers the trade-off between two constructs

• Journal of the Korea Society of Computer and Information
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• v.21 no.4
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• pp.63-71
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• 2016

This paper is about applying efficient data mining method which improves the score calculation and proper building performance of credit ranking score system. The main idea of this data mining technique is accomplishing such objectives by applying Correlation based Feature Selection which could also be used to verify the properness of existing rank scores quickly. This study selected 2047 manufacturing companies on KOSPI market during the period of 2009 to 2013, which have their own credit rank scores given by NICE information service agency. Regarding the relevant financial variables, total 80 variables were collected from KIS-Value and DART (Data Analysis, Retrieval and Transfer System). If correlation based feature selection could select more important variables, then required information and cost would be reduced significantly. Through analysis, this study show that the proposed correlation based feature selection method improves selection and classification process of credit rank system so that the accuracy and credibility would be increased while the cost for building system would be decreased.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.383-396
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• 2017

The model in our approach assumes that computer responses are a realization of a Gaussian processes superimposed on a regression model called a Gaussian process regression model (GPRM). Selecting a subset of variables or building a good reduced model in classical regression is an important process to identify variables influential to responses and for further analysis such as prediction or classification. One reason to select some variables in the prediction aspect is to prevent the over-fitting or under-fitting to data. The same reasoning and approach can be applicable to GPRM. However, only a few works on the variable selection in GPRM were done. In this paper, we propose a new algorithm to build a good prediction model among some GPRMs. It is a post-work of the algorithm that includes the Welch method suggested by previous researchers. The proposed algorithms select some non-zero regression coefficients (${\beta}^{\prime}s$) using forward and backward methods along with the Lasso guided approach. During this process, the fixed were covariance parameters (${\theta}^{\prime}s$) that were pre-selected by the Welch algorithm. We illustrated the superiority of our proposed models over the Welch method and non-selection models using four test functions and one real data example. Future extensions are also discussed.

• Journal of Families and Better Life
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• v.6 no.1
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• pp.205-221
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• 1988

The purpose of this study is to classify several variable which were assumed to have relationship with the college students behavior of Hyo, to see their possible correlation with demographic characteristics, and to proved some useful data for their possible correlation with demographic characteristics. and to provide some useful data for their sound value system. The data for this study was obtained form the survey of the 477 students who reside in the city of Seoul by using questionnaire methods. The frequency of variables was statistically analyzed to see the general character of the samples and factor analysis was made for classification of the college student's behavior of Hyo. In order to study th characteristic of demographic variables, t-test and ANOVA were conducted The major findings of this study can be summarized as follows. 1) As the result of factor analysis about behavior of Hyo, six factors (Which Eigen value was above 1.0) out of 64 questions were extracted : 'respect' familiarity' 'family consciousness' 'serve' self-preservation, establishmence of them-selves in life' and 'self-reliance' were selected. 2)In general, it can be said that the college students' behavior of Hyo varies by demographic variables. 3) By surveying the level of actualizing Hyo of the college students' all of factors ranged from 'the middle' to 'the high level'. The result confirmed that students fulfilled the behavior of Hyo to their parents in all items.

• Information Systems Review
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• v.3 no.2
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• pp.349-368
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• 2001

The purpose of this research is to investigate economic factors that determine characteristics of B2B e-Marketplaces. From a previous research work, we classify B2B e-Marketplaces into four forms: MRO Hubs, Catalogue Hubs, Yield Managers, and Exchanges. This classification is based upon "What businesses buy" and "How businesses buy." In an attempt to identify economic factors that determine e-Marketplace forms, we employ three economic factors: buyer/seller relationships, features of products traded, and characteristics of industries or markets. Through extensive literature reviews, we have selected six variables which can be used to explain reasons for different e-Marketplace forms: asset specificity and information asymmetry for the buyer/seller relationship, standardization and price variability for the product features, entry barrier and market volatility for the market characteristics. This research conducts six in-depth case studies to explain that "Why different forms of e-Marketplace emerge?" The research framework intends to provide link between e-Marketplace forms and six economic variables. Six case studies are based on interviews with CEO or team managers of e-Marketplace firms. This study has found six economic variables, explaining well reasons for different e-Marketplace forms. Research findings are summarized as propositions so that survey-type research can be conducted with a large number of samples in the future.

• Health Policy and Management
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• v.30 no.1
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• pp.62-71
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• 2020

Background: The purpose of this study is to analyze the current status and factors of elderly patients' hospitalization for hip replacement, knee replacement, and general spine surgery. Methods: National health insurance data in 2018 was provided by the National Health Insurance Service. We used multiple regression to analyze factors associated with the medical utilization of hip replacement, knee replacement, and general spine surgery in elderly patients over 65 years old. The dependent variables are the length of stay and total health expenditure. The independent variables are the demographic-social factors (sex, age, region, insurance type, income level) and surgery-related factors (institution type, location of the hospital, surgery classification). Results: The most common factor affecting surgery was the location of medical institutions. Compared with the medical institutions located in metropolitan, the length of stay in rural medical institutions was higher and total health expenditure was lower. The lower quartile of income, the higher the length of stay and total health expenditure. In addition, the variables of age, type of health insurance, and type of medical institution were statistically significant. Conclusion: In this study, we confirmed the effect of sociodemographic factors and medical institution factors on the Healthcare Utilization of spinal and joint surgery.

• Journal of the Korean Home Economics Association
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• v.30 no.3
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• pp.223-239
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• 1992

The purpose of this study is to classify the home management behaviors of urban housewives and to find out variables which influence them. Following are the results. 1. The home management behavior of urban housewives are classified into six types. Thouse expense and convenience oriented type, using the information and family centered type, tradition and steady oriented type, improving life type, conservative and thrifty type and the self-faithfulness and change adaption type. 2. Follows are the variables which have influenced on home management behaviors of urban housewives. \circled1 The level of education of housewives, perceived level of economical resources, income and evaluation level of life have influenced on expense and convenience oriented type. \circled2 The duration of marriage, the level of education of husband, the satisfaction of housework and communication interaction have influenced on using the information and family centered type. \circled3 The satisfaction of housework, the perceived level of economical resources, the level of education of husband and the age of housewives have influenced on the tradition and steady oriented type. \circled4 The perceived level of family resources and the communication interaction have influenced on the improving life type. \circled5 The communication interaction and the income have influenced on conservative and thrifty type. \circled6 The perceived level of economical resources, the satisfication of housework, the communication interaction, the level of education of housewives, the age of housewives and the number of children have influenced on the self-faithfulness and change-adaption type.