• Korean Journal of Construction Engineering and Management
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• v.13 no.5
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• pp.25-34
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• 2012

It has been five years since the Post-Construction Sale System of Housing was introduced. The purpose of this study is to identify objectives and effects of the Post-Construction Sale System of Housing and analyze change of profitability at different sales time from a supplier's point of view. Apartment buildings construction projects performed in Seoul are used for the case study. The present value of sales revenues, sensitivity and the present value of expected sales prices are analyzed. According to the findings, first, profits made from a Pre-construction sales system was 5.1%~6.2% higher than those from a Post-construction sales system. Among four plans of a Pre-construction sales system (A, B, C and D plan), sales revenue from the A plan, which takes a deposit at the time of starting construction, was the greatest. Second, increase of the rate of discount and decrease of sales revenues are in direct proportion. The bigger rate of discount leads actual reduction of sales revenues. Third, for the present value of sales revenues reflecting change in basic model construction cost, a Pre-construction sales system showed a little higher than that of a Post-construction sales system by approximately 2%. It should be known that this study suggests profitability of Pre-and Post-construction sales system by clearly measuring them in the supplier's point of view and calculates sales revenues, considering change of a sale price following change of sales time.

• Culinary science and hospitality research
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• v.17 no.5
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• pp.92-107
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• 2011

The purpose of this study was to understand the effect of the characteristics of coupons purchased through a social shopping site upon customer satisfaction and future behavior intention. Based on total 332 samples who had bought franchise restaurant coupons and used them before, this study reviewed reliability and fitness of the research model and verified total 4 hypotheses with AMOS and SPSS program. The hypothesized relationships among the models were tested simultaneously by using a structure equation model(SEM). The proposed model provided an adequate fit to the data, ${\chi}^2$=309.795(df=103, p<.001), CMIN/DF=3.008, RMR=.103, GFI=.912, NFI=.927, CFI=.950, RMSEA=.074. The result showed that the coupon proneness(${\beta}$=.645) and price sensitivity(${\beta}$=-.315) had a significant influence on restaurant satisfaction(p<.001) and only coupon proneness(${\beta}$=1.040) had a significant influence on coupon satisfaction(p<.001). Also, restaurant satisfaction had a positive significant influence on restaurant customers' revisit intention(${\beta}$=.603, p<.001) and coupon users' repurchase intention(${\beta}$=.335, p<.001). Furthermore, coupon satisfaction had a positive significant influence on coupon repurchase intention(${\beta}$=.353, p<.001) but had a negative significant influence on restaurant revisit intention(${\beta}$=-.263, p<.001). Limitations and future research directions were also discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.685-693
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• 2017

This study aims to effectively respond to urban local rainstorms by classifying the risk against flood damage for each use district. The risk classification is based on sensitivity analysis of the socio-economic damage caused by local rainstorms in Changwon city, Korea by a Fuzzy model using data, such as the districts that provide institutional bases for land use, land prices, which estimate the property values, and floor area ratios, which measures the density and areas of flood damage. The analysis result indicated that flood damage in five districts of Changwon (Masan happo-gu, Masan Hoewon-gu, Sungsan-gu, Euichang-gu, and Jinhae-gu) is highest in the order of commercial areas, residential areas, industrial areas, and forests, which was attributed to high land price and floor area ratio of commercial areas. On the other hand, specific analysis in Masan Hoewon-gu and Sungsan-gu was different from the previous result, indicating that the risk against flood damage may vary according to the districts depending on their local conditions. The analysis from this study can be applied to future urban planning and be used as a guideline to estimate the potential flood damage. Overall, this study is meaningful in that it proposes an effective management of land use as a new resolution to mitigate of urban flood damage within a broader perspective of climate change and urbanization.

• Journal of Climate Change Research
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• v.4 no.4
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• pp.371-384
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• 2013

The appearance of abnormal weather caused by climate change have both direct and indirect impact on the society. Especially, agriculture is brought up as a socially important interest having direct impact of climate change in growth and harvest of crops. This study aims to perform vulnerability assessment for the South Korea's two main imported grains, maize and wheat. The production vulnerability assessment of maize and wheat in USA and China to temperature variability, which has a great impact in production, is performed. First, grain cultivation period which affects productivity of main grain production country was selected based on the main cultivation period from several references and previous studies. Then, Intergovernmental Panel on Climate Change AR5 greenhouse gas scenario RCP(representative concentration pathways)8.5 scenarios was used to select the future climate that correspond to the cultivation period of maize and wheat for each producing country. According to the result of production vulnerability analysis using adaptation (temperature changing trend) and sensitivity(temperature variability), the productivity of wheat was higher in USA, while productivity of maize was higher in China. In the future, the result showed that productivity of all two grains will be favorable in USA. The result of production vulnerability assessment through this study can later be used as a preparation data for the coming fluctuation in grain price due to climate change.

• Journal of Electrochemical Science and Technology
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• v.13 no.1
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• pp.148-158
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• 2022

The electrochemical CO₂ reduction (ECR) to produce value-added fuels and chemicals using clean energy sources (like solar and wind) is a promising technology to neutralize the carbon cycle and reproduce the fuels. Presently, the ECR has been the most attractive route to produce carbon-building blocks that have growing global production and high market demand. The electrochemical CO₂ reduction could be extensively implemented if it produces valuable products at those costs which are financially competitive with the present market prices. Herein, the electrochemical conversion of CO₂ obtained from flue gases of a power plant to produce diesel and formic acid using a consistent techno-economic approach is presented. The first scenario analyzed the production of diesel fuel which was formed through Fischer-Tropsch processing of CO (obtained through electroreduction of CO₂) and hydrogen, while in the second scenario, direct electrochemical CO₂ reduction to formic acid was considered. As per the base case assumptions extracted from the previous outstanding research studies, both processes weren't competitive with the existing fuel prices, indicating that high electrochemical (EC) cell capital cost was the main limiting component. The diesel fuel production was predicted as the best route for the cost-effective production of fuels under conceivable optimistic case assumptions, and the formic acid was found to be costly in terms of stored energy contents and has a facile production mechanism at those costs which are financially competitive with its bulk market price. In both processes, the liquid product cost was greatly affected by the parameters affecting the EC cell capital expenses, such as cost concerning the electrode area, faradaic efficiency, and current density.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.1
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• pp.67-76
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• 2024

Objectives: Direct reading instruments (DRIs) are widely used by industrial hygienists and other experts for preliminary survey and identifying source locations in many industrial fields. Photoionization detectors (PIDs), which are a form of hand-held portable DRIs, have been used for a variety of airborne vaporized chemicals, especially evaporated hydrocarbon solvents. The benefits of PIDs are high sensitivity between each chemical, competitive price, and portability. With the goal of increasing the accuracy of logged PID concentrations, previous studies have performed tests for the assessment of single chemical compounds, not mixtures. The purpose of this preliminary study was to measure mixtures with a PID and charcoal tube at the same time and compare the accuracy between them. Methods: A chamber test was implemented with different mixtures of hydrocarbon chemicals (acetone, isopropyl alcohol, toluene, m-xylene) and levels in the range of 14 to 864 ppm. Three PIDs and charcoal tubes were connected to the chamber and measured the chemical mixtures simultaneously. A comparison of accuracy and the PID group of concentrations with manufacture correction factor (M_CF) and field correction factor (F_CF) applied was performed. Results: The accuracy of the PID concentrations data-logged from the PID did not meet the accuracy criteria except for the mixture level B and C logged from PID No. 2, which was 18% of all tests for meeting accuracy criteria. The mean and standard deviation (SD) of concentration (ppm) of the charcoal tube followed by each mixtures' level were 10.37±0.26, 155.33±5.28, 300.80±11.65, and 774.93±22.65, respectively. When applying F_CF into the PID concentrations, the accuracy increased by nearly 82%. However, in the case of M_CF, none met the accuracy criterion. Between the PID there were differences of logged concentrations. Conclusions: In this preliminary study, the concentration of a logged PID with F_CF applied was a better way to increase accuracy compared to applying M_CF. We suggest that additional research is necessary to consider environmental factors such as temperature and humidity.

• Journal of Preventive Medicine and Public Health
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• v.36 no.4
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• pp.339-348
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• 2003

Objective : To quantify the economic value of the Sirolimus fluting Stent ($CYPHER^{TM}$) in treating acute coronary heart disease (CMD), and to assist in determining an adequate level of reimbursement for $CYPHER^{TM}$ in Korea. Methods : A decision-analytical model, developed by the Belgium Health Economics Disease Management group, was used to investigate the incremental cost-effectiveness of $CYPHER^{TM}$ versus conventional stenting. The time horizon was five years. The probabilities for clinical events at each node of the decision model were obtained from the results of large, randomized, controlled clinical trials. The initial care and follow-up direct medical costs were analyzed. The initial costs consisted of those for the initial procedure and hospitalization, The follow-vp costs included those for routine follow-up treatments, adverse reactions, revascularization and death. Defending on the perspective of the analysis, the costs were defined as insurance covered or total medical costs (=sum of insurance covered and uncovered medical costs). The cost data were obtained from the administrative data of 449 patients that received conventional stenting from five participating Korean hospitals during June 2002. Sensitivity analyses were peformed for discount rates of 3, 5 and 7%. Since the major clinical advantage of $CYPHER^{TM}$ over conventional stenting was the reduction in the revascularization rates, the economic value of $CYPHER^{TM}$, in relation to the direct medical costs of revascularization, were evaluated. If the incremental cost of $CYPHER^{TM}$ per revascularization avoided, compared to conventional stenting, was no higher than that of a revascularization itself, $CYPHER^{TM}$ would be considered as being cost-effective. Therefore, the maximum acceptable level for the reimbursement price of $CYPHER^{TM}$ making the incremental cost-effectiveness ratio equal to the cost of a revascularization was identified. Results : The average weighted initial insurance covered and total medical costs of conventional stenting were about 6,275,000 and 8,058,000 Won, respectively. The average weighted sum of the initial and 5-year follow-up insurance covered and total medical costs of conventional stenting were about 13,659,000 and 17,353,000 Won, respectively. The estimated maximum level of reimbursement price of $CYPHER^{TM}$ from the perspectives of the insurer and society were $4,126,897{\sim}4,325,161$ and $4,939,939{\sim}5,078,181$ Won, respectively. Conclusion : By evaluating the economic value of $CYPHER^{TM}$, as an alternative to conventional stenting, the results of this study are expected to provide a scientific basis for determining the acceptable level of reimbursement for $CYPHER^{TM}$.

• Journal of Distribution Research
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• v.16 no.5
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• pp.171-192
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• 2011

This paper focuses on the retail industry of industrial share of the GDP, productivity of distribution industry and input-out analysis between Korea and Japan, also results are summarized as follows. First, the share of GDP in agriculture, forestry and fisheries of the both countries is falling. That of manufacture increases in South Korea, while Japan is falling. While distribution industry shows vice versa. Employed population by industry is falling both countries also. The relative labor productivity shows that agriculture, forestry and fisheries, retail industry needs more labor, while manufacture has been met for both countries. Second, compare to Japan, the retail industry of Korea has been increased since 1990. Likewise, overall productivity of distribution industry in Korea has been increased while almost that of Japan has declined. Third, production inducement effects of Japan are greater than that of Korea. On the other hand, import inducement effects show vice versa. Fourth, as shown from the final demand of distribution industry and the rate of dependence on production inducement, we can see that the “increase in stocks” increases while gross government fixed capital formation shows vice versa. Korea's private consumption expenditure increases while Japan shows versa. South Korea's government consumption expenditure and exports are rising, on the other hand, that of Japan is declining. Fifth, the rate of dependence on distribution industry and import inducement shows the same tendency from both countries. As we can see from the private consumption expenditure, government consumption expenditure, gross government fixed capital formation, gross private fixed capital formation, increase in stocks, the rate of dependence on import inducement is more effective than the rate of dependence on production inducement. While the exports are comparatively ineffective. Sixth, the degrees of influence of retail industry are similar between Korea and Japan, while sensitivity of the Korean industry has been weakened. In this sense, strong policies are needed to boost the industry. Seventh, the investments in the retail industry of Korea showed the public-led trend, while Japan showed private sector-led investment trend. The investment trend of Korea's retail industry will be switched into private sector-led investment step by step in the future. This finding will be an important clue to set the policy direction of Korea distribution industry. Finally, both Korea and Japan are still in need of employment in retail industry. Not addressed in this paper, such as value-added-induced effects, employment inducement effect, will be remaining challenges in the following paper.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.4
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• pp.304-309
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• 2015

To evaluate the degree of contamination caused by oil spill accident in the sea, the in-situ sensors which are based on the scientific method are needed in the real site. The sensors which are based on the fluorescence detection theory can provide the useful data, such as the concentration of oil. However these kinds of sensors commonly are composed of the ultraviolet (UV) light source such as UV mercury lamp, the multiple excitation/emission filters and the optical sensor which is mainly photomultiplier tube (PMT) type. Therefore, the size of the total sensing platform is large not suitable to be handled in the oil spill field and also the total price of it is extremely expensive. To overcome these drawbacks, we designed the fluorimeter for the oil spill detection which has compact size and cost effectiveness. Before the detail design process, we conducted the experiments to measure the excitation and emission spectrum of oils using five different kinds of crude oils and three different kinds of processed oils. And the fluorescence spectrometer were used to analyze the excitation and emission spectrum of oil samples. We have compared the spectrum results and drawn the each common spectrum regions of excitation and emission. In the experiments, we can see that the average gap between maximum excitation and emission peak wavelengths is near 50 nm for the every case. In the experiment which were fixed by the excitation wavelength of 365 nm and 405 nm, we can find out that the intensity of emission was weaker than that of 280 nm and 325 nm. So, if the light sources having the wavelength of 365 nm or 405 nm are used in the design process of fluorimeter, the optical sensor needs to have the sensitivity which can cover the weak light intensity. Through the results which were derived by the experiment, we can define the important factors which can be useful to select the effective wavelengths of light source, photo detector and filters.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.