• Journal of Korean Society for Quality Management
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• v.36 no.1
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• pp.72-79
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• 2008

The policy for credit card approval/disapproval is based on the applier's personal and financial information. In this paper, we will analyze 2 credit card approval data with several classification methods. We identify which variables are important factors to decide the approval of credit card. Our main tool is an open-source statistical programming environment R which is freely available from http://www.r-project.org. It is getting popular recently because of its flexibility and a lot of packages (libraries) made by R-users in the world. We will use most widely used methods, LDNQDA, Logistic Regression, CART (Classification and Regression Trees), neural network, and SVM (Support Vector Machines) for comparisons.

• Journal of Information Management
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• v.43 no.3
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• pp.79-95
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• 2012

This study is designed for library classification of the tourism. Contents studies are summarized as follows. First, an analysis of the current status of classification and items by a key work 'tourism' in KDC, NDC, DDC, UDC, and LCC which are main library classification tables today indicates that they are too limited to travelling and tourism, tourism policy, and tourist attractions etc. Second, we divided areas studies newly based on the theoretical books in order to extract the classification items of the tourism field, and comparatively analyzed main library classification systems today. We divided basic categories of the classification items into four including tourism general, tourists, tourism attraction, tourism media. Third, a new classification was designed for library classification of the tourism field. Basically, the tourism field was assigned to the main four items and the classification items which were weighted or scattered were adjusted.

• Journal of Environmental Policy
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• v.3 no.2
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• pp.113-137
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• 2004

The objective of this study is to introduce the definitions and classification methods of wastes in international agreements and legislations, examine the concept of wastes and their classification systems in Korea, and finally analyze and compare the concept of wastes in different countries for finding better solutions and suggestions. The study summarizes the concept of wastes as introduced in the Basel Convention, OECD, EU, US, and UK. First, each of the member countries adapt to the same concepts of wastes as defined in their international agreements; second, the intention of the wastes holder and the conditions of the wastes are considered at the same time when defining the concepts. Upon close examination of the classification of wastes systems as introduced in the Basel Convention, OECD, EU, US, and UK, the wastes are classified into toxic and non-toxic wastes according to the existence of poisonous substances. Therefore, it is classified as a toxic waste when any toxic substance on its list is included in the waste, while others are considered as a non-toxic waste if they don't contain poisonous substances. Secondly, in the UK, the matter of toxic or non-toxic wastes are classified, not according to the existence of the poisonous substances, but based on the generation of sources. In Korea, the concepts of wastes are divided into the two categories - a concept as defined in actual legislations and a concept in its translation. The Korean classification of the wastes include Wastes Management Act, amended in 1995, which stipulates that toxic substances should be managed in a special way as the designated wastes. It appears that the Act utilizes the classification method that classifies the wastes according to the existence of poisonous substance. Korea's concepts of wastes should be changed after recognition of the concepts in international agreement (Basel Convention, EU) and other foreign laws(US, UK) that consider subjective and objective standards at the same time when they define the concepts. Also, the development of technology in recycling and reuse of the wastes can remove the current absolute notion of the wastes so that it also should not be passed over. Also, because a classification structure of wastes has a close relationship with a disposal structure, its classification system should be fixed gradually to come up with the development of wastes disposal technology and its policy.

• Health Policy and Management
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• v.13 no.1
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• pp.98-115
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• 2003

Concerns about growing health insurance expenditures became a national Issue in 2001 when the National Health Insurance went into a deficit. Increases in spending for ambulatory care shared the largest portion of the problem. Methods and systems to control the spending should be developed and a system to measure case mix of providers is one of core components of the control system. The objectives of this article is to examine the feasibility of applying Korean Diagnosis Related Groups (KDRGs) to classify health insurance claims for ambulatory care and to identify problem areas of the classification. A database of 11,586,270 claims for ambulatory care delivered during January 2002 was obtained for the study, and the final number of claims analyzed was 8,319,494 after KDRG numbers were assigned to the data and records with an error KDRG were excluded from the study. The unit of analysis was a claim and resource use was measured by the sum of charges incurred during a month at a department of a hospital of at a clinic. Within group variance was assessed by th coefficient of variation (CV), and the classification accuracy was evaluated by the variance reduction achieved by the KDRG classification. The analyses were performed on both all and non-outlier data, and on a subset of the database to examine the validity of study results. Data were assigned to 787 KDRGs among 1,244 KDRGs defined in the classification system. For non-outlier data, 77.4％ of KDRGs had a CV of charges from tertiary care hospitals less than 100％ and 95.43％ of KDRGs for data from clinics. The variance reduction achieved by the KDRG classification was 40.80％ for non-outlier claims from tertiary care hospitals, 51.98％ for general hospitals, 40.89% for hospitals, and 54.99% for clinics. Similar results were obtained from the analyses performed on a subset of the study database. The study results indicated that KDRGs developed for a classification of inpatient care could be used for ambulatory care, although there were areas where the classification should be refined. Its power to predict tile resource utilization showed a potential for its application to measure case mix of providers for monitoring and managing delivery of ambulatory care. The issue concerning the quality of diagnostic information contained in insurance claims remains to be improved, and significance of future studies for other classification systems based on visits or episodes is guaranteed.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.409-418
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• 2021

The land cover map is a very important data that is used as a basis for decision-making for land policy and environmental policy. The land cover map is mapped using remote sensing data, and the classification results may vary depending on the acquisition time of the data used even for the same area. In this study, to overcome the classification accuracy limit of single-period data, multi-series satellite images were used to learn the difference in the spectral reflectance characteristics of the land surface according to seasons on a U-Net model, one of the deep learning algorithms, to improve classification accuracy. In addition, the degree of improvement in classification accuracy is compared by comparing the accuracy of single-period data. Seoul, which consists of various land covers including 30% of green space and the Han River within the area, was set as the research target and quarterly Sentinel-2 satellite images for 2020 were aquired. The U-Net model was trained using the sub-class land cover map mapped by the Korean Ministry of Environment. As a result of learning and classifying the model into single-period, double-series, triple-series, and quadruple-series through the learned U-Net model, it showed an accuracy of 81%, 82% and 79%, which exceeds the standard for securing land cover classification accuracy of 75%, except for a single-period. Through this, it was confirmed that classification accuracy can be improved through multi-series classification.

• Health Policy and Management
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• v.26 no.2
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• pp.95-106
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• 2016

A new manual of System of Health Accounts (SHA) 2011, was published jointly by the Organization for Economic Cooperation and Development (OECD), Eurostat, and World Health Organization in 2011. This offers more complete coverage than the previous version, SHA 1.0, within the functional classification in areas such as prevention and a precise approach for tracking financing in the health care sector using the new classification of financing schemes. This paper aims to demonstrate current health expenditure (CHE) and National Health Accounts of the years 1970-2014 constructed according to the SHA2011. Data sources for public financing include budget and settlement documents of the government, various statistics from the National Health Insurance, and others. In the case of private financing, an estimation of total revenue by provider groups is made from the Economic Census data and the household income and expenditure survey, Korean healthcare panel study, etc. are used to allocate those totals into functional classifications. CHE was 105 trillion won in 2014, which accounts for 7.1% of Korea's gross domestic product. It was a big increase of 7.7 trillion won, 7.9%, from the previous year. Public share (government and compulsory schemes) accounting for 56.5% of the CHE in 2014 was still much lower than the OECD average of about 73%. With these estimates, it is possible to compare health expenditures of Korea and other countries better. Awareness and appreciation of the need and gains from applying SHA2011 for the health expenditure classification are expected to increase as OECD health expenditure figures get more frequently quoted among health policy makers.

• Health Policy and Management
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• v.11 no.1
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• pp.1-18
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• 2001

The purpose of the present study was to assess the agreement of survival probability estimated by International Classification of Diseases l0th Edition(ICD-10) based International Classification of Diseases based Injury Severity Score(ICISS) with professional panel's judgment on preventable death. ICISS has a promise as an alternative to Trauma and Injury Severity Score(TRISS) which have served as a standard measure of trauma severity, but requires more validation studies. Furthermore as original version of ICISS was based ICD-9CM, it is necessary to test its performance employing ICD-10 which has been used in Korea and is expected to replace ICD-9 in many countries sooner or later. Methods : For 1997 and 1998 131 trauma deaths and 1,785 blunt trauma inpatients from 6 emergency medical centers were randomly sampled and reviewed. Trauma deaths were reviewed by professional panels with hospital records and survival probability of trauma inpatients was assessed using ICD-10 based ICISS. For trauma mortality degree of agreement between ICISS survival probability with judgment of professional panel on preventable death was assessed and correlation between W-score and preventable death rate by each emergency medical center was assessed. Results : Overall agreement rate of ICISS survival probability with preventable death judged by professional panel was 66.4%(kappa statistic 0.36). Spearman's correlation coefficient between W-score and preventable death rate by each emergency medical center was -0.77(p=0.07) and Pearson's correlation coefficient between them was -0.90(p=0.01). Conclusions : The agreement rate of ICD-10 based ICISS survival probability with of professional panel's judgment on preventable death was similar to TRISS. The W-scores of emergency medical centers derived from ICD-10 based ICISS were highly correlated with preventable death rates of them with marginal statistical significance.

• Journal of Distribution Science
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• v.9 no.2
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• pp.111-122
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• 2011

The purpose of this study is to survey the successful cases of small and medium Business Systematization Cognition by examining their entrepreneurial characteristics and analysing the factors affecting their success. To that end, previous studies on the association types of small businesses were studied. A research model was developed, and research hypotheses for an empirical analysis were established upon it. Suh et al. (2010) insist on the importance of Small Business Systematization in Korea but also show that small business performance is suffering: they are too small to stand alone. That is why association is so crucial for them: they must stand together. Unfortunately, association is difficult, as they have few specific links and little motivation. Even in franchising networks, association tends to be initiated by big franchisers, not small ones. In that sense, association among small businesses is crucial for their long-term survival. With this in mind, this study examines how they think and feel about the issue of 'Industrial Classification', how important Industrial Classification is to their business success, and what kinds of problems it raises in the markets. This study seeks the different cognitions among the association types of small businesses from the perspectives of participation motivation, systematization expectation, policy demand level, and management performance. We assume that different industrial classification types of small businesses will have different cognitions concerning these factors. There are four basic industrial classification types of small businesses: retail sales, restaurant, service, and manufacturing. To date, most of the studies in this area have focused on collecting data on the external environments of small businesses or performing statistical analyses on their status. In this study, we surveyed 4 market areas in Busan, Masan, and Changwon in Korea, where business associations consist of merchants, shop owners, and traders. We surveyed 330 shops and merchants by sending a questionnaire or visiting. Finally, 268 questionnaires were collected and used for the analysis. An ANOVA, T-test, and regression analyses were conducted to test the research hypotheses. The results demonstrate that there are differences in cognition depending upon the industrial classification type. Restaurants generally have a higher cognition concerning job offer problems and a lower cognition concerning their competitiveness. Restaurants also depend more on systematization expectation than do the other industrial classification types. On the policy demand level, restaurants have a higher cognition. This study identifies several factors that are contributing to management performance through differences in cognition that depend upon association type: systematization expectation and policy demand level have positive effects on management performance; participation motivation has a negative effect on management performance. We confirm also that the image factors of different cognitions are linked to an awareness of the value of systematization and that these factors show sequential and continual patterns in the course of generating performances. In conclusion, this study carries significant implications in its classifying of small businesses into the four different associational types (retail sales, restaurant, services, and manufacturing). We believe our study to be the first one to conduct an empirical survey in this subject area. More studies in this area will likely use our research frameworks. The data show that regionally based industrial classification associations such as those in rural cities or less developed areas tend to suffer more problems than those in urban areas. Moreover, restaurants suffer more problems than the norm. Most of the problems raised in this study concern the act of 'associating itself'. Most associations have serious difficulties in associating. On the other hand, the area where they have the least policy demand is that of service types. This study contributes to the argument that associating, rather than financial assistance or management consulting, promotes the start-up and managerial performance of small businesses. This study also has some limitations. The main limitation is the number of questionnaires. We could not survey all the industrial classification types across the country because of budget and time limitations. If we had, we could have produced many more useful results and enhanced the precision of our analysis. The history of systemization is very short and the number of industrial classification associations is relatively low in Korea. We should keep in mind, though, that this is very crucial to systemization entrepreneurs starting their businesses, as it can heavily affect their chances of success. Being strongly associated with each other might be critical to the business success of industrial classification members. Thus, the government needs to put more effort and resources into supporting the drive of industrial classification members to become more strongly associated.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.51-68
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• 2014

Today's public sector information is considered an important national asset that has social and economic value. Hence, developed countries are competitively promoting various policies to actively promote access to public sector information and the use of such information for private purposes. The Korean government is also boosting the Government 3.0 policy as a new governmental management paradigm that supports the creative economy. Despite these governmental efforts, since open public sector information is only classified from the supplier's perspective, it is difficult to have access to information for private application from the consumer's perspective and expand private applications because of the problems in identifying the information source. In this study, the concept of data from the user's perspective for the activation of private applications was defined by focusing on public sector information obtained by affiliated organizations of the Ministry of Science, ICT and Future Planning(MSIP). The new classification system was designed by analyzing the classification system of conventional open services of public sector information through investigation.