• 모자간호학회지
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• v.4 no.1
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• pp.24-32
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• 1994

Using data from the Korean National Health Survey conducted in the years 1989 and 1992, child and maternal ambulatory care utilization patterns were compared. Data from 3,002 families from the 1989 survey and 1,523 families from the 1992 survey which have a child 0-4 years old and mother in the same family were selected and used for the analysis. The results indicate that child medical utilization is closely accociated with maternal medical utilization, as measured by the number of visits to medical facilities. Maternal use appears to be a more powerful predictor of child use than any other family and maternal variables. These results confirm the result of the previous localized studies and suggest that intervention directed at the mother may be effective in ensuring equitable and efficient use of ambulatory services by childeren.

• Journal of the Korean Regional Science Association
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• v.31 no.4
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• pp.3-24
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• 2015

Crimes must be reduced not only because of the financial, physical, and emotional damages they bring to the victims but also because crimes increase social costs by elevating distrust in society and instilling fear. With the increasing number of crimes in Korea, finding other factors that affect the occurrence of crimes is needed beyond the current viewpoint for crime analysis. Social support factors can be candidates for studies on the social support effect on crime occurrence in their initial stage. In this study, we identified the effect of social support factors on crime occurrence or deterrence, none of which has been considered important until now, given the emergence of spatial econometrics. The resulting Moran's I values revealed the existence of a spatial autocorrelation in all three crimes: heinous crimes, theft, and violence. As shown in the analysis using spatial econometrics and ordinary least squares, social support from families is significant in reducing all crimes especially violence. Social support from the local government is significant in preventing only theft. The spatial econometrics model is only valid in heinous crimes. These different effects of social support factors and spatial factors on crime occurrences are caused by the different characteristics of crimes. Hence, policymakers should consider the social support effect when they establish policies related to social housing or welfare.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.147-156
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• 2016

This study analyzed the impact of changes in the construction business on construction company insolvency according to their size using the vector error correction model. First, this study applied EDF (Expected Default Frequency), which was calculated by KMV (Kealhofer, McQuown and Vasicek) model, as a variable to indicate the insolvency of construction companies. This study set 30 construction companies listed to KOSPI/KOSDAQ for estimating the EDF by size and construction companies were divided into two groups according to their size. To examine the construction business cycles, the amount of construction orders according to the type-residential, non-residential, and civil work- was used as a variable. The serial data was retrieved from TS2000 established by the Korea Listed Companies Association (KLCA), Statistics Korea. The analysis period was between the second quarter of 2001 and fourth quarter of 2015. As a result of calculating the EDF of construction companies by size, as it is generally known, the large-sized construction companies showed lower levels of insolvency than relatively smaller-sized construction companies. On the other hand, impulse response analysis based on VECM confirmed that the level of insolvency of large-scaled companies is more sensitive to business fluctuations than relatively smaller-sized construction companies, particularly changes in the residential construction market. Hence it is a major factor affecting the changes in insolvency of large-sized construction companies.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.3-11
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• 2013

The changes in construction business have impact on overall operation of construction companies. Poor business of construction companies following a s low industrial cycle could have broader implications and influences on the industry. Since a construction project involves various stakeholders including public organizations, financial institutions and households, a downturn in construction industry might lead to significant economic loss. In this regard, it is meaningful to examine the relationship between changes in construction business cycles and insolvency of construction companies. This study conducts an empirical analysis of the relationship between construction business cycles and how much they affect operation of construction companies. To this end, KMV model was used to estimate probability of bankruptcy, which represents business condition of a construction company. To examine construction business cycles, investment amount for different construction types-residential, non-residential, and construction work-was used as a variable. Based on the investment amount, VECM was applied and the analysis results suggested that construction companies should put priority on diversifying project portfolio. In addition, it was shown that once a construction company becomes unstable in business operation, it is hard to recover even when the market condition turns for the better. This suggests that, to improve business operation of a construction company, internal capacity-building is as important as the market condition and other external circumstances.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.237-246
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• 2014

In this study, it is estimated how many changes of macroeconomic variables are happened under the proposition of import substitution of mining products 1% using macroeconometric input-output model. For this, used macroeconometric input-output model is composed of 141 behavioral equations representing the macroeconomy structure. In general, macroeconometrics models are constructed mainly on the side of the expenditure then it is not easy to estimate the effects of the shocks occurred from industry level. To mitigate that, this study tries to construct a macroeconometric input-output model. Macroeconometrics model which is useful to estimate the effects of macroeconomic shocks, economic policy and more, in this study, is linked with input-output table through the NDI(national disposable income) derived from compensation of employee. And this paper presents the estimation results of import substitution effects of mining products on Korean economy. As a results, GDP is increased 0.00073%, gross labor employed 0.00029%, current balanace 0.00010% and unemployment rate is mitigated 0.00233%.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.5
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• pp.31-40
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• 2016

This paper is to set up the autoregressive distributed lag model in order to estimate factor elasticities of the service export in the medical and healthcare service industry and to analyze the determinants for its export performance during 1975-2015. The empirical results suggest that industrial markup, exchange rate, and interest rate have had more decisive effects on the industrial export performance in the medical and healthcare service industry, in particular, during the declining period in factor prices since the foreign currency crisis beginning in late 1997.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.291-305
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• 2017

대전은 전국에서 R&D투자가 많은 지역으로 이는 출연연 및 출연연 출신 연구원의 기술창업의 증가로 나타나는 현상으로 볼 수 있다. R&D가 많이 투자됨에 따라 이에 따른 효율성에 대한 분석들이 많이 이루어지고 있으며, 주로 R&D 투자가 대한 지역내총생산, 기업의 생산성 등에 미치는 영향 즉 R&D투자의 효율성 분석을 많이 하고 있다. 본고에서는 지역 R&D투자가 기업의 생산성에 어느 정도 영향을 미치는 지를 분석하였다. 특히 지역특화(전략)산업 분야별로 분석하여 지역 R&D 투자의 효율적 배분을 위한 전략방안을 제시하고자 한다. 이러한 분석을 위해서 생산성에 대한 대리변수로 종업원 1인당 매출액 종업원 1인당 부가가치를 종속변수로 설정하였고, 독립변수로 연구개발비, 종업원 1인당 영업이익, 종업원 1인당 자본집약도 등의 변수를 다중회귀모형으로 실증분석 하였다. 분석결과 R&D투자가 매출액과 부가가치에 유의한 영향을 미치지만, 연구개발비가 매출액이나 부가가치 등 생산성 증가에 결정적인 요인으로 나타나지 않았다. 산업별 분석결과 정보통신, 바이오산업보다 부품소재 산업에서 결정계수가 높게 나왔다. 또한 조절회귀모형을 설정하여 조절효과를 분석한 결과 R&D투자는 매출액에 영향을 미치지만, 부가가치는 조절효과가 발생하지 않았다. 이는 지역 R&D투자의 효율적 배분 측면에서 투자의 활성화를 이루고 연구개발 투자가 실질적으로 기업의 생산성 증가에 기여할 수 있도록 견인해야 할 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.208-208
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• 2020

지구온난화와 하천환경의 변화로 수질 오염이 심각해지고 녹조 현상 등의 피해가 증가하고 있다. 특히, 기후변화로 인해 온도와 강우량의 변동성이 동시에 증가하고 있어 하천의 수환경 관리측면에서 어려움이 증가하고 있다. 최근 하천 개발 사업으로 인한 인공 구조물 축조로 하천의 오염도 변화는 중요한 논점으로 대두되었으며, 그에 따라 정확한 수질 전망이 요구되고 있다. 녹조평가에 있어 주요 대리변수(proxy variable)로 chlorophyll-a(Chl-a)가 사용되고 있지만, Chl-a는 규조류와 남조류(cyanobacteria) 모두에서 발견되는 지표로서, 녹조의 유해성을 Chl-a 수질 지표만을 사용하여 판단하기에는 한계가 있다. Chl-a뿐만 아니라 수질에 대한 유량, 온도, 영양염류 등의 영향 또한 기존 연구에서 밝혀진 바 있다. 하지만 기존의 물리기반의 결정론적모형은 수질의 추계학적(stochastic) 특성을 반영하는데 제한적이며, 다양한 수문기상학적 조건을 고려한 시나리오 기반의 분석을 수행하는데 한계가 있다. 따라서 본 연구에서는 특정 지점의 보 건설 이후 수문기상 자료를 이용하여 유해 남조류 개체수와 관계있는 수문기상학적 요인을 평가하고 최종적으로 Bayesian Poisson Regression 기반의 중·장기 녹조 예측 모형을 개발하였으며, 해설결과에 대한 불확실성 정보도 제공할 수 있도록 하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.471-471
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• 2022

도시화로 인한 하천 건천화가 심각해짐에 따라 생태계 종 다양성 감소와 서식처 파괴 등 다양한 생태학적 문제가 발생한다. 건강한 하천 생태계를 유지하기 위해서는 유량 감소로 인한 수생태계 건강성 회복을 위해서는 어류 종에 따른 적합한 생태 유량을 산정해야 한다. 특히 발전방류로 인한 유량 변화는 하류에 서식하는 어류에 직접적인 영향을 미치므로 댐 방류량에 의한 서식처 면적 변화에 대한 연구가 필요하다. 이에 본 연구에서는 1) 낙동강 상류 구담교 유역을 대상으로 안동댐과 임하댐 유입량을 활용한 BBM (Building Block Methodology)을 구축하고, 2) 대상 하천의 River2D 모형을 구축하여, 3) 대표·대리 어종에 대한 자연유황과 BBM에 따른 가중가용면적(Weighted Usable Area, WUA)을 산정하였다. 2006년 ~ 2020년 자료를 기반으로, 시나리오1은 실측 유량을 활용하였으며, 시나리오2는 전체기간, 홍수년, 갈수년 그리고 평수년으로 구분하여 댐 유입량을 기반으로 산정한 BBM을 활용하였다. 시나리오 분석 결과, 가중가용면적이 감소하는 일부 기간도 존재하였으나, 전반적으로 BBM을 반영한 시나리오 2에서 서식처 면적이 증가하는 것으로 나타났다. 대표 어종 피라미의 경우 최대 약 18% 가중가용면적이 감소하는 기간이 존재하였으나, 최대 79%의 서식처 향상 효과가 나타났다. 대리어종 모래무지의 경우 마찬가지로 최대 약 18%의 서식처 감소 효과가 나타나는 기간이 존재하였으나, 최대 78%의 서식처 향상 효과가 나타나는 것으로 나타났다. 따라서 자연유황을 모방하여 댐 방류 패턴을 변경하는 것이 하류에 서식하는 어류의 서식처 개선에 더 효과적인 것으로 판단된다. 다만 서식처에 영향을 주는 물리적 요인(댐 방류량 등) 외에도 생물·화학적 요인이 존재하므로, 향후 다양한 요인을 고려한 연구를 통해 효과적인 서식처 개선 방안을 모색할 수 있을 것으로 기대된다.