• 통상정보연구
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• 제6권1호
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• pp.25-50
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• 2004

This study attempts to find out what kind of service quality is considered important by customers in using the Internet shopping mall and suggests the way to activate the customer relationship. The findings based on empirical analysis are shown here. First, empirical analysis of the contextual factors such as gender, education, and experience levels, shows that what customers perceive as most important in the product purchase is security in terms of the payment and personal information service. The second important service quality factor perceived by customers is responsiveness, particularly the rapidity and accuracy of response to their needs and wants. The customers also considered price, quality and diversity of the product as being important. Furthermore, there is no big difference among other service quality factors. Second, in the different gender context, there is no significant difference between the genders. However, the male group shows an even distribution of factors valued in the service quality, whereas female respondents placed stronger emphases on particular aspects of service, such as security, response, reliability and product quality. Third, in the context of different education level, the payment method between graduates and non-graduates has a significant difference. That is, the non-graduates prefer the credit card and saving through ATM, while the graduates use dual payment method using credit card and another payment method together. Therefore, the various payment methods should be considered according to the customer type, namely graduates or non-graduates. Fourth, in the context of different experience level, the result of the empirical analysis of the factors of the service quality shows no great difference between experienced and inexperienced customers. Both types of customer perceive security as the most important. To sum up, the service quality perceived by the customers of Internet shopping malls is empirically analyzed in different contexts such as gender, education, and experience. Then, the device for the customer relationship activation is suggested. It can be utilized as a guideline for the continuing diffusion of the Internet shopping mall, giving it a competitive advantage against other companies.

• 한국병원경영학회지
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• 제25권2호
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• pp.45-56
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• 2020

Purpose: The purpose of this study is to investigate medical care behaviors influencing accuracy of the payment based New diagnosis-related groups (DRG) compared to fee for service (FFS) in hospitalized patients with medical illness. Methodology: In order to estimate the difference in medical costs between New DRG and FFS depending on medical care behaviors, medical records and hospital claims data (n=4,232) were utilized, which were collected from a single public hospital during the first-half of 2018. Data were analyzed by descriptive statistics, t-test, chi-square test, and multivariate binary logistic regression. Findings: The average difference in medical costs between New DRG and FFS were KRW 506,711±13,945 with incentives and KRW -51,506±12,979 without incentives, respectively. Forty-four point two percent (44.2%, n=1,872) of total subjects were shown to have negative compensation in overall medical costs with New DRG compared to the costs with FFS. Medical care behaviors that affected on the negative compensation were the presence of severe bed sores on admission, medical consultations, death, operations, medications and laboratory or imaging tests with unit price over KRW 100,000, hospital-acquired complications or underlying comorbidities, elderly patients (≧65 years), and hospitalized for more than average inpatient days defined by New DRG (p<0.001). The difference in average medical cost between New DRG and FFS for a group with mild illness was KRW -11,900±10,544, whereas it was KRW -196,800±46,364 for a group with severe illness (p<0.0001). Practical Implications: These findings suggest that New DRG payment model without incentives may incompletely cover the variation of medical costs in real clinical practice. Therefore, policy makers need to consider that the current New DRG reimbursement should be focused and refined to improve accuracy of payment on medical care resources utilized in severe and complex medical conditions.

• 보건행정학회지
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• 제33권4호
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• pp.450-456
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• 2023

Background: This study aims to develop a "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions" for the National Health Insurance Service to enhance administrative efficiency in protecting and collecting contributions from livelihood-type defaulters. Additionally, it aims to establish customized collection management strategies based on individuals' ability to pay health insurance contributions. Methods: Firstly, to develop the "Predictive Model for the Possibility of Collection Delinquent Health Insurance Contributions," a series of processes including (1) analysis of defaulter characteristics, (2) model estimation and performance evaluation, and (3) model derivation will be conducted. Secondly, using the predictions from the model, individuals will be categorized into four types based on their payment ability and livelihood status, and collection strategies will be provided for each type. Results: Firstly, the regression equation of the prediction model is as follows: phat = exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction) / [1 + exp (0.4729 + 0.0392 × gender + 0.00894 × age + 0.000563 × total income - 0.2849 × low-income type enrollee - 0.2271 × delinquency frequency + 0.9714 × delinquency action + 0.0851 × reduction)]. The prediction performance is an accuracy of 86.0%, sensitivity of 87.0%, and specificity of 84.8%. Secondly, individuals were categorized into four types based on livelihood status and payment ability. Particularly, the "support needed group," which comprises those with low payment ability and low-income type enrollee, suggests enhancing contribution relief and support policies. On the other hand, the "high-risk group," which comprises those without livelihood type and low payment ability, suggests implementing stricter default handling to improve collection rates. Conclusion: Upon examining the regression equation of the prediction model, it is evident that individuals with lower income levels and a history of past defaults have a lower probability of payment. This implies that defaults occur among those without the ability to bear the burden of health insurance contributions, leading to long-term defaults. Social insurance operates on the principles of mandatory participation and burden based on the ability to pay. Therefore, it is necessary to develop policies that consider individuals' ability to pay, such as transitioning livelihood-type defaulters to medical assistance or reducing insurance contribution burdens.

• ETRI Journal
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• 제23권2호
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• pp.61-70
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• 2001

In this paper, we propose an efficient method for personal identification by analyzing iris patterns that have a high level of stability and distinctiveness. To improve the efficiency and accuracy of the proposed system, we present a new approach to making a feature vector compact and efficient by using wavelet transform, and two straightforward but efficient mechanisms for a competitive learning method such as a weight vector initialization and the winner selection. With all of these novel mechanisms, the experimental results showed that the proposed system could be used for personal identification in an efficient and effective manner.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2001년도 학술대회지
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• pp.353-358
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• 2001

외환위기 이후 주택건설업체의 유동성확보가 중요한 이슈로 부각되고 있다. 이는 정확한 현금흐름 예측을 전제로 하고 있으나, 현재까지는 기업금융이 보편화되어 있어서 현금흐름 예측관리 시스템이 발달하지 못한 실정이다. 정확한 현금흐름 예측을 위해서는 사업성 검토시에 고려하는 손익변화 예측중심의 현금흐름에 보다 실제적인 현금흐름의 특성을 적용한 모델이 필요하다. 본 논문에서는 이러한 문제를 해결하기 위해서 사업성 검토시 고려되는 현금흐름에 분양계약자의 선납 및 연체와 연관된 분양대금 납부패턴을 분석해 현금수입 예측의 기초 모델을 제시하고, 선납과 연체로 인한 최종 현금손실을 분석해 그 모델에 적용하였다. 또한 현금지출의 정확한 예측을 위해서 사업성 검토 시 사용되는 공사비 예상 지출액을 공정율 기준에서 원가투입율 기준으로 변경하고, 공사대금의 어음지급 비율 및 기간의 변동에 따른 현금지출 변화를 보여주는 현금지출 모델을 제시하였다. 본 ·논문에서 제시하는 모델로 기존보다 현실성 높은 현금흐름 예측이 가능할 것으로 기대되며, 자금조달 시점과 자금집행 시점을 보다 정확히 파악할 수 있어 자금집행의 효율성을 높이는 기반을 제공할 것으로 기대된다.

• 보건행정학회지
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• 제16권1호
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• pp.17-40
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• 2006

With the prospect of rapidly growing health insurance expenditures, particularly spending for ambulatory care, the introduction of a case-based payment method is discussed as an alternative to the current fee-for-service based method. A system to measure case mixes of providers is a core component of such payment systems. The objective of this study were to develop a classification system for ambulatory care, Korean Ambulatory Patient Group (KAPG) based on the U.S. APG version 2.0 and to evaluate the classification accuracy of the system. A database of 64,258,386 records was constructed from insurance claims submitted to the Health Insurance Review Agency (HIRA) during three months from August 2002. A total of 41,347,307 records with a single visit was used for the development and 7% random sample of the database was used for the evaluation. Additional groups were defined to include both physician and hospital fees in the classification, age splits were added to classify the entire population as well as the population older than 65, and the definition of medical groups used by the HIRA was adopted. The variance reduction in charges achieved by KAPGs was computed to evaluate the accuracy of classification. A total of 474 KAPGs was defined compare to 290 groups in the U.S. APG. The variance reduction for charges of all visits ranged from 20% to 37% depending on the type of provider, and ranged from 22% to 42% for non-outliers, that were better than those achieved by the system currently used by the .HIRA for its internal review purpose. Although further study is required to improve the classification for complicated care in larger hospitals, the results indicated that KAPGs could be used for better management of costs for ambulatory care.

• 농촌계획
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• 제23권1호
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• pp.21-29
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• 2017

The purpose of this study is to analyze the accuracy of cultivated crop database in agricultural farm business using UAV(Unmanned Aerial Vehicle) and field survey over Daesso-myeon, Umsung-gun, Chungbuk. When comparing with agricultural farm business and cadastral maps, Daeso-myeon crop field shows 29.8%(2,030 parcels out of 6,822 parcels) is either mismatched or missing. It covers almost 19.3%($3.4km^2$ of $17.6km^2$) of total farmland. In order to solve these problems, it is necessary to prepare a multifaceted plan including cadastral map. Comparative analysis of the cultivated crop registered in the agricultural farm business and the field survey agreed only in 3,622 parcels in total 6,822 parcels whereas 3200 parcels disagree. Among these disagreed parcels 2,030(29.8%) have been confirmed as unregistered farm business entity. Accuracy of cultivated crop registered in agricultural farm business agreed in 75.6% cases. Especially the paddy field registration is more accurate that other crops. These discrepancies can lead to false payment in agricultural farm business. For exploration and analysis of regional resources, UAV images can be used together with farm business management database and cadastral map to get a clearer grasp over on-site resources and conditions.

• 보건행정학회지
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• 제23권1호
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• pp.35-43
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• 2013

Background: Diagnosis procedure combination (DPC) has recently been introduced in Korea as a demonstration project and it has aimed the improvement of accuracy in bundled payment instead of Diagnosis related group (DRG). The purpose of this study is to investigate that the model of end-stage liver disease (MELD) score as the severity classification of liver diseases is adequate for improving reimbursement of DPC. Methods: The subjects of this study were 329 patients of liver disease (Korean DRG ver. 3.2 H603) who had discharged from National Health Insurance Corporation Ilsan Hospital which is target hospital of DPC demonstration project, between January 1, 2007 and July 31, 2010. We tested the cost differences by severity classifications which were DRG severity classification and clinical severity classification-MELD score. We used a multiple regression model to find the impacts of severity on total medical cost controlling for demographic factor and characteristics of medical services. The within group homogeneity of cost were measured by calculating the coefficient of variation and extremal quotient. Results: This study investigates the relationship between medical costs and other variables especially severity classifications of liver disease. Length of stay has strong effect on medical costs and other characteristics of patients or episode also effect on medical costs. MELD score for severity classification explained the variation of costs more than DRG severity classification. Conclusion: The accuracy of DRG based payment might be improved by using various clinical data collected by clinical situations but it should have objectivity with considering availability. Adequate compensation for severity should be considered mainly in DRG based payment. Disease specific severity classification would be an alternative like MELD score for liver diseases.

• 무역학회지
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• 제48권1호
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• pp.243-261
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• 2023

본 연구는 화물운송 플랫폼에 대한 차주들의 니즈(Needs)를 실증분석하여 서비스 개선과 이용 활성화를 위한 발전 방향을 모색하는 것에 목적을 두고 있다. 연구의 방법은 O2O 서비스 플랫폼과 국내 화물운송 플랫폼에 관한 선행연구를 실시하고, 이를 바탕으로 IPA를 이용한 화물운송 플랫폼 선정 요인분석을 진행하였다. 분석 결과는 중요도의 경우, 공정한 운임의 제시(4.22), 불공정거래 방지 대책(4.21), 운송대금 결제기한 정확성(4.21), 운송구간 정보제공 정확성(4.16), 빠른 상호작용(4.13), 애플리케이션 시스템 품질(4.12), 사용 용이성(4.12), 이용자 맞춤형 서비스(4.05), 정산업무 지원기능(4.05), 운송구간의 다양성(3.96), 브랜드 이미지(3.89), 부가서비스(3.80) 순으로 나타났다. 만족도의 경우, 사용 용이성(3.72), 정산업무 지원기능(3.70), 운송구간 정보제공 정확성(3.68), 애플리케이션 시스템 품질(3.67), 브랜드 이미지(3.89), 부가서비스(3.89), 이용자 맞춤형 서비스(3.59), 운송구간의 다양성(3.52), 빠른 상호작용(3.46), 운송대금 결제기한 정확성(3.45), 불공정거래 방지 대책(3.41), 공정한 운임의 제시(3.36) 순으로 나타났다. 만족도 분석 결과를 보면, 가장 높은 순위를 보인 요인들은 사용 용이성, 정산업무 지원기능, 정보제공 정확성 등 화물운송 플랫폼 품질과 관련된 요인들로 확인이 되었다. 최근 국내 화물운송 플랫폼 기업들의 경쟁이 치열해지면서 플랫폼 품질의 질적 향상이 된 것으로 분석된다. 반대로, 낮은 만족도를 보인 요인들은 공정한 운임의 제시, 불공정거래 방지 대책 등이었다. 해당 요인들은 중요도에서 가장 높은 순위를 나타낸 요인들이었는데, 반대로 만족도 분석에서는 가장 낮은 순위를 보였으므로 가장 시급하게 개선되어야 할 요인들로 분석된다. 본 연구는 실증분석이 미약한 국내 화물운송 플랫폼에 대한 선정 요소를 추출하고, 이를 바탕으로 화물운송 플랫폼 서비스 전략을 제시하였는데 연구의 의의가 있으며, 향후 국내 화물운송 플랫폼 관련연구 및 서비스 전략 수립시 유용하게 이용될 수 있을 것으로 기대된다.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2008년도 추계 공동 국제학술대회
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• pp.164-169
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• 2008

The increasing late-payment rate of credit card customers caused by a recent economic downturn are incurring not only reduced profit of department stores but also significant loss. Under this pressure, the objective of credit forecasting is extended from presumption of good or bad customers to contribution to revenue growth. As a method of managing defaults of department store credit card, this study classifies credit delinquents into some clusters, analyzes repaying patterns of customers in each cluster, and develops credit forecasting system to manage delinquents of department store credit card using data of Korean D department store's delinquents. The model presented by this study uses Kohonen network, a kind of artificial neural network of data mining techniques to cluster credit delinquents into groups. Logistic regression model is also used to predict repayment rate of customers of each cluster per period. The accuracy of presented system for the whole clusters is 92.3%.