• Title/Summary/Keyword: Valuation model

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Evidence-Based Benefit-Risk Assessment of Medication (근거에 기반한 의약품의 유익성-위해성 평가)

  • Lee, Eui-Kyung
    • The Journal of Health Technology Assessment
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    • v.1 no.1
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    • pp.22-26
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    • 2013
  • Objectives: Balancing benefits and risks through the drug life cycle has been discussed for many decades. The objective of this study was to review the processes and tools currently proposed for benefit-risk assessment of medicinal drugs. It aimed to establish scientific and efficient drug safety management system based on the synthetic analysis of benefit-risk evidence. Methods: We conducted a review of exiting literatures published by regulatory agencies or initiatives. Not only quantitative methodologies but also qualitative method were compared to understand their key characteristics for the benefit and risk assessment of drugs. Results: Recently, benefit-risk assessments have more structured approaches to decision making as part of regulatory science. Regulatory agencies such as European Medicines Agency, FDA have prepared plans to apply benefit-risk assessment to regulatory decision making. Also many initiatives such as IMI (Innovative Medicine Initiative) have conducted research and published reports about benefit-risk assessment. For benefit-risk assessment, four kinds of methods are necessary. Frameworks such as BRAT (Benefit Risk Action Team) framework, PrOACT-URL provide guidance for the whole process of decision-making. Metrics are measurements of risk benefit. The estimation techniques are methods to synthesis and combine evidences from various sources. The utility survey techniques are necessary to explicit preferences of various outcome from stakeholders. Conclusion: There is the lack of widely accepted, validated model for benefit-risk assessment. Nor there is an agreement among academia, industry, and government on methods for the quantitative valuation. It is also limited by available evidence and underlying assumptions. Nevertheless, benefit-risk assessment is fundamental to improve transparency, consistency and predictability for decision making through the structured systematic approaches.

A Study on the Diffusion Strategies of Wood Culture Using Analytic Hierarchy Process (AHP)

  • Jiyoon YANG;Myungsun YANG;Yeonjung HAN;Myungkil KIM;Won Joung HWANG
    • Journal of the Korean Wood Science and Technology
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    • v.51 no.6
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    • pp.555-568
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    • 2023
  • The diffusion strategies of wood culture were established using the analytic hierarchy process, to prepare a diffusion plan of wood culture and wood utilization in response to climate change due to global warming. 'Standardization of wood culture', 'Valuation of wood culture', and 'Habituation of wood culture' were set as three major implementation strategies and priorities were evaluated. As a result, it was analyzed in the following order: 'Development of systematic education programs for each age group for rational and efficient use of eco-friendly wood materials and development of wood education standard guidelines linked to the curriculum', 'Preparation of scientific basis data on human compatibility and eco-friendliness of wood to ensure the reliability of wood and wood products', and 'Establishment of monitoring and improvement plan through the designation as a model school'. Through this, it was determined that an educational environment, changes in public attitudes through publicity, and expanding opportunities to use wood and wood products were necessary for wood culture diffusion. The results of this study can be used as basic data to derive the diffusion strategies of wood culture and establish a roadmap and policy implementation strategy to revitalize wood culture.

Estimation in a Model for Determining the Amount of Carbon in Soil and Measurement of the Influences of the Specific Factors (농경지 토양탄소량 결정모형 추정 및 요인별 영향력 계측)

  • Suh, Jeong-Min;Cho, Jae-Hwan;Son, Beung-Gu;Kang, Jum-Soon;Hong, Chang-Oh;Kim, Woon-Won;Park, Jeong-Ho;Lim, Woo-Taik;Jin, Kyung-Ho
    • Journal of Environmental Science International
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    • v.23 no.11
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    • pp.1827-1833
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    • 2014
  • This study has been carried out to present the valuation system of soil carbon sequestration potentials of soil in accordance with the new climate change scenarios(RCP). For that, by analyzing variation of soil carbon of the each type of agricultural land use, it aims to develop technology to increase the amount of carbon emissions and sequestration. Among the factors which affects the estimation of determining the soil carbon model and influence power after the measurement on soil organic carbon, under the center of a causal relationship between the explanatory variables this study were investigated. Chemical fertilizers (NPK) decreased with increasing the amount of soil organic carbon and as with the first experimental results, when cultivating rice than pepper, the fact that soil organic carbon content increased has been found out. The higher the carbon dioxide concentration, the higher the amount of organic carbon in the soil and this result is reliable under a 10% significance level. On the other hand, soil organic carbon, humus carbon and hot water extractable carbon has been found out that was not affected the soils depth, sames as the result of the first year. The higher concentration of carbon dioxide, the higher carbon content of humus and hot water extractable carbon content. According to IPCC 2006 Guidelines and the new climate change scenario RCP 4.5 and the measurement results of the total amount of soil organic carbon to the crops due to abnormal climate weather, 1% increase in atmospheric carbon dioxide concentration was found to be small when compared to the growing rate of increasing 0.01058% of organic carbon in the soil.

A Study on Development of Assessment Model for Spatio-Temporal Changes in River Bed Using Numerical Models (수치모형을 이용한 하상변동 시공간 평가 기법 개발 연구)

  • Kim, Chul-Moon;Lee, Jeong-Ju;Choi, Su-Won;Ahn, Won-Sik
    • Journal of Korea Water Resources Association
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    • v.44 no.12
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    • pp.975-990
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    • 2011
  • In this study, to develop an assessment method for spatio-temporal riverbed changes, a 1-dimensional model (HEC-RAS) and a 2-dimensional model (CCHE2D) were built and applied. As for the analysis of a riverbed's long-term change in a real stream, three new assessment methods were developed, which are called the "Sediment section cumulative curve", "Sediment section moment", and "Sediment probability distribution function." These methods were used to assess the characteristics of riverbed changes using a consistent valuation standard and to understand changes in quantities intuitively. From the results of this study, sediment characteristics of cross sections can be detected effectively by applying the "Sediment section cumulative curve" method to determine whether there is any sedimentation or erosion in total emission. The amount of sedimentation or erosion occurring in the right or left banks, which divided by center column, could be presented as one criterion by applying the "Sediment section moment" method. This approach could be utilized as an indicator for sediment predictions. Spatio-temporal sediment variables can be presented quantitatively by determining the mean and uncertain boundaries through the "Sediment probability distribution function", and finally, the results can be illustrated for each cross section to provide intuitive recognition.

A Valuation for Gas Hydrate R&D Project Using Fuzzy Real Options Model (퍼지실물옵션모형을 이용한 가스하이드레이트 R&D 사업의 가치평가)

  • Yun, Ga-Hye;Heo, Eunnyeong
    • Environmental and Resource Economics Review
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    • v.18 no.2
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    • pp.217-239
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    • 2009
  • As gas hydrate is recently emerging as a new energy source to solve environmental and exhaustion problems caused by fossil energy, Korea is working on a gas hydrate development project under a 10-year plan from 2005 to 2014. Gas hydrate is expected to have a big effect on the economy and society of Korea, which is largely depending on energy imports besides water energy and atomic energy. However, it is uncertain whether the project will produce successful results. Thus, it is very important to improve its validity and to propose effective execution strategies by evaluating the value of the project in advance. Thus, this study intended to include new information, which had not been evaluated in existing methods, and to reduce biases or errors in value evaluation results by applying a fuzzy risk analysis to the real option model in order to evaluate the value of a gas hydrate development project. It is advantageous that the real option model based on the fuzzy risk analysis modelizes the vagueness and inexactness of intangible element judgment into an appropriate language scale so as to evaluate these elements clearly and integrate them with estimated financial performance results. The application of the fuzzy risk analysis makes it possible to conduct an analysis by dissolving a decision-making issue with complicated and various attributes into several simplified problems. With the continuing high oil prices and today's demand of clean energy, the necessity of energy resources and technology development projects keeps growing. Amid this situation, it is expected that these study results will contribute to proposing a guideline not only for gas hydrate projects but also for policy decision-making related to future energy industries.

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Discount Presentation Framing & Bundle Evaluation: The Effects of Consumption Benefit and Perceived Uncertainty of Quality (묶음제품 가격 할인 제시 프레이밍 효과: 지각된 소비 혜택과 품질 불확실성의 영향을 중심으로)

  • Im, Meeja
    • Asia Marketing Journal
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    • v.14 no.1
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    • pp.53-81
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    • 2012
  • Constructing attractive bundle offers depends on more than an understanding of the distribution of consumer preferences. Consumers are also sensitive to the framing of price information in a bundle offer. In classical economic theory, consumers' utility should not change as long as the total price paid stays same. However, even when total prices are identical, consumers' preferences toward a bundle product could be different depending on the format of price presentation and the locus of price discount. A weighted additive model predicts that the impact of a price discount on the overall evaluation of the bundle will be greater when the discount is assigned to the more important product in the bundle(Yadav 1995). Meanwhile, a reference dependent model asserts that it is better to assign a price discount to a tie-in component that has a negative valuation at its current offer price than to a focal product that has a positive valuation at its current offer price(Janiszewski and Cunha 2004). This paper has expanded previous research regarding price discount presentation format, investigating the reasons for mixed results of prior research and presenting new mechanisms for price discount framing effect. Prior research has hypothesized that bundling is used to sell a tie-in component with an offer price above the consumer's reference price plus a focal product of the same offer price with reference price(e.g., Janiszewski and Cunha 2004). However, this study suggests that bundling strategy can be used for increasing product's attractiveness through the synergy between components even when offer prices of bundle components are the same with reference prices. In this context, this study employed various realistic bundle sets with same price between offer price and reference price in the experiment. Hamilton and Srivastava(2008) demonstrated that when evaluating different partitions of the same total price, consumers prefer partitions in which the price of the high-benefit component is higher. This study determined that their mechanism can be applied to price discount presentation formats. This study hypothesized that price discount framing effect depends not on the negative perception of tie-in component with offer price above reference price but rather on the consumers' perceived consumption benefit in bundle product. This research also hypothesized that preference for low-benefit discount mechanism is that perceived consumption benefit reduces price sensitivity. Furthermore, this study investigated how consumers' concern for quality in a price discount--a factor not considered in previous research--influences price discount framing. Yadav(1995)'s experiment used only one magazine bundle of relatively low quality uncertainty and could not show the influence of perceived uncertainty of quality. This study assumed that as perceived uncertainty of quality increases, the price sensitivity mechanism for assigning the discount to low-benefit will increase. Further, this research investigated the moderating effect of uncertainty of quality in price discount framing. The results of the experiment showed that when evaluating different partitions of the same total price and the same amount of discounts, the partition that discounts in the price of low benefit component is preferred to the partition that decreases the price of high benefit component. This implies that price discount framing effect depends on the perceived consumption benefit. The results also demonstrated that consumers are more price sensitive to low benefit component and less price sensitive to high benefit component. Furthermore, the results showed that the influence of price discount presentation format on the evaluation of bundle product varies with the perceived uncertainty of quality in high consumption benefit. As perceived uncertainty of quality gradually increases, the preference for discounts in the price of low consumption benefit decreases. Besides, the results demonstrate that as perceived uncertainty of quality gradually increases, the effect of price sensitivity in consumption benefit also increases. This paper integrated prior research by using a new mechanism of perceived consumption benefit and moderating effect of perceived quality uncertainty, thus providing a clearer explanation for price discount framing effect.

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Machine learning-based corporate default risk prediction model verification and policy recommendation: Focusing on improvement through stacking ensemble model (머신러닝 기반 기업부도위험 예측모델 검증 및 정책적 제언: 스태킹 앙상블 모델을 통한 개선을 중심으로)

  • Eom, Haneul;Kim, Jaeseong;Choi, Sangok
    • 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.

Feasibility Study on Remodeling Project By Using Real Option Model : Focusing on Apartment House Remodeling (실물옵션을 활용한 공동주택 리모델링 사업성 평가에 관한 연구 - 아파트 리모델링 사례를 중심으로 -)

  • Yeon, JungHoon;Lee, Hyun-Soo;Park, Moonseo;Kim, Sooyoung;Ahn, Joseph
    • Korean Journal of Construction Engineering and Management
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    • v.15 no.1
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    • pp.39-50
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    • 2014
  • After the global financial crisis, domestic construction industry has gone through a rapid recession. This resulted in gradual market shift towards architectural remodeling. Architectural remodeling not only improves residential environment but it has many advantages such as increase of each unit's exclusive area, free space within the horizontal or extension of an annex building, and increase number of household through splitting the household of bigger pyeong, etc. However, in case of the Korean market for apartment remodeling, due to various regulations and problem with business promotion procedures, majority of business is slow despite the figure that remodeling volume is not that small. Also, feasibility study which decides to push ahead public house remodeling business will have a flaw using net present value's law; it has a flaw of not considering properties of each phase of remodeling business and future's uncertainty. Hence, this research will improve the problem of traditional value assessment method of net present value's law. It will also consider one of the real options such as binomial model in order to supplement NPV which is used in current feasibility study. This research was based on real successful cases of public house remodeling and it was possible for feasibility study which was more realistic and valid. This research provided foundation for development of Korean public house remodeling market. There is high anticipation of increasing the validity by improving the problems of current feasibility study and economic efficiency assessment.

An Analysis of Vocational High School Students Preference for Science and Its Causal Factors (실업계 고등학생의 과학선호도와 인과요인 분석)

  • Im, Sung-Min
    • Journal of The Korean Association For Science Education
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    • v.22 no.4
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    • pp.892-905
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    • 2002
  • There are an increasing emphasis on affective domain, for example interest or belief, in science education. But decreasing interest on learning science and tendency to avoid science-related job are serious problems of secondary science education, especially in case of vocational high school students. However there are few researches for vocational high school students. In this study, preference for science is assumed to be a multidimensional property that reveals ones' behavioral volition and valuation as well as emotional response upon learning science. To investigate vocational high school students' preference for science and its causal factors, a Likert style questionnaire was developed through factor analysis. Students' preference for science was analyzed by 3 categories, and its causal factors are investigated by path analysis using structural equation model.

The Study on the Selection of Suitable site for Palustrine Wetland Creation at Habitat Restoration Areas for Oriental stork(Ciconia boyciana) (황새서식처 복원지역에서의 소택지 조성 적지선정 연구)

  • Son, Jin-Kwan;Sung, Hyun-Chan;Kang, Bang-Hun
    • Journal of Wetlands Research
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    • v.13 no.1
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    • pp.95-104
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    • 2011
  • This study was implemented to select the suitable site for Palustrine Wetland at habitat restoration for Oriental stork, red species and top-level predator in ecosystem. The evaluation items was fitted by review the antecedent studies on the suitable site selection model and evaluation items of wetland. The study sites were setted in $5,884,800m^2$ area including Yesan-gun Dae-ree, in which Oriental stork' park will be located, through DEM(Digital Elevation Model) watershed analysis. The thematic map by valuation items with secure of water resource, soil, topography, distance between roads, houses, etc., land using, wildlife corridor, and type of water resource was prepared using GIS program. The sites with high evaluation score were selected as suitable creation sites for wetland through overlapping those maps. Total 8 sites with over 18 point were selected. The characteristics of selected sites show that the soil are consisted of clay, the connectivity is valued high with surface water, the slope are gentle, and the connectivity is good with surroundings ecosystem. The result of water quality analysis, which was implement to survey available water resources and develop the solution of problem of water environment, showed that water quality at Salmok reservoir and Bogang reservoir is generally good, but the water quality at stagnant water body rising out from groundwater is not good. This study has limit to select the suitable sites of wetland only by analyzing physiotherapy environment in study area. Hereafter, the study is need to examine closely enhancement effects of biological diversity through investigation of biotic environment.