• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Environmental and Resource Economics Review
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• v.16 no.4
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• pp.763-779
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• 2007

The combined heat-and-power (CHP) plant is recently suggested as an effective resolution in response to recent rising oil prices and the Kyoto Protocol. This research provides a model for economic appraisal to evaluate CHP investment. Real option model is developed to incorporate a case where the investment is irreversible and underlying revenue is stochastic. The analysis shows that power plant capacity more than 40 Gcal makes CHP investment profitable while the results may vary 10 modest level with respect to investment cost, heat sales price and discount rate.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.547-553
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• 2022

This study analyzed the changes in the operational productivity of fourteen Korean container lines from 2019 to 2021 using MP I(Malmquist Productivity Index). The results indicated that the operational productivity of the shipping companies has increased by 38.4% annually, representing the TCI (Technical Change Index) increasing by 58.3% and the TECI (Technical Efficiency Change Index) decreasing by 12.6%. The increase in the operational productivity of the container shipping lines was mainly attributed to the high rise in ocean freight rates rather than an increase in fleet size or ship technical efficiency. However, the deep-sea shipping lines (i.e. HMM and SM lines) experienced increases in both the TCI and TECI, which was not the case for other shipping lines(i.e. Intra-Asian short-sea shipping lines). The intra-Asian short-sea shipping lines enhance their productivity due to the TCI but failed to appreciate the cost savings of the increased fleet effects due to the low SECI(Scale Efficiency Change Index) values.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.785-789
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• 2006

유역 수자원의 효율적인 관리 및 배분을 위해서는 세밀한 강우-유출관계의 규명이 무엇보다 중요하다. 이를 위해서는 먼저 하천 유출지점의 정확한 유량정보가 획득되어야 하며, 장기간에 걸쳐 신뢰성 있는 유량자료의 확보는 더욱 중요한 사항이다. 본 연구에서는 하천에서 관측된 유량자료를 장기간(1983년${\sim}$2004년)에 걸친 유출성분으로 분리하는 기법을 활용하여 제어지점의 유출량을 검증하였다. 유량자료를 출구지점의 관측유량$(Q_{ob})$을 회귀수$({\alpha}Q_e)$, 상류유입량$(Q_{up})$ 및 관측강우-유출량$({\beta}Q_{Rain})$의 성분으로 구분하여 산정하는 방식으로 유출량을 추정하였다. 여기서, 회귀수$({\alpha}Q_e)$란 유역 및 하도내 용수이용량의 회귀수, 상류유입량$(Q_{up})$은 상류 유출 제어지점의 관측유량으로 대청댐 방류량, 관측강우-유출량$({\beta}Q_{Rain})$은 유역내 강우에 의한 자연유출량이다. 여기서 사용된 수문기초자료는 대청댐 방류량, 대전 및 청주권 취수량, 강우에 의한 자연유출량, 공주관측유량 등으로 각 성분별로 생성된 일자료를 이용하여 공주지점의 월별, 분기별, 년도별 유출량을 산정하였다. 이 결과는 금강유역에 이미 구축되어있는 SSARR모형을 기반으로 한 RRFS(Rainfall Runoff Forecasting System, 유출예측 시스템)의 결과 및 관측치와 비교되었다. 계산결과 RRFS에 의한 유출량과 대청-공주구간의 유출성분분리에 의한 유출량은 관측값과 전반적으로 근사함을 확인하였으며, 검증지점의 정확한 유출율을 산정할 수 있다면, 관측자료의 연속성 및 신뢰도를 파악하는 척도를 제공할 수 있을 것으로 판단된다.측결과 있는 대상유역에 대한 적용이 요구된다.-Moment 방법에 의해 추정된 매개변수를 사용한 Power 분포를 적용하였으며 이들 분포의 적합도를 PPCC Test를 사용하여 평가해봄으로써 낙동강 유역에서의 저수시의 유출량 추정에 대한 Power 분포의 적용성을 판단해 보았다. 뿐만 아니라 이와 관련된 수문요소기술을 확보할 수 있을 것이다.역의 물순환 과정을 보다 명확히 규명하고자 노력하였다.으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에 있어서 시장수익률을 평균적으로 초과할 수 있는 거래전략은 존재하므로 이러한 전략을 개발 및 활용할 수 있으며, 특히, 한국주식시장에 적합한 거래전략은 반전거래전략이고, 이 전략의 유용성은 투자자가 설정한 투자기간보다 더욱 긴

• Environmental and Resource Economics Review
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• v.27 no.4
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• pp.613-637
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• 2018

Fuel cell power plant which has advantages as a distributed generation is influenced by high cost of investment and uncertainty of electricity price. This study suggests the model of real options which considers the irreversibility of investment in the fuel cell plant and the uncertainty of electricity price. Most models of real options assume the geometric Brownian motion for convenience, but this study develops the model for the feasibility analysis considering the mean reverting process of electricity price, with the closed form solution on the value of investment option. The result of the empirical analysis considering the data related to the fuel cell generation with the scale of 20MW and the domestic RPS circumstance represents that the investment is feasible without the uncertainty, and is not feasible with the uncertainty. This result implies that the political support as well as the improvement of profit system including revenue and cost are necessary for the activation of the fuel cell power plant.

• Journal of Environmental Policy
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• v.10 no.2
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• pp.45-60
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• 2011

An aim of this paper is to test four hypotheses on price volatility in the $CO_2$ emission markets focusing on European Climate Exchange(ECX) in the EU Emission Trading Schemes(EU ETS) and Chicago Climate Exchange(CCX). I expect that, due to an influx of market information, a differently designed exchange market would bring a different price volatility, and various types of emission permits in the same exchange market would result in the same effects on the price volatility. Major findings are that the price volatility is same regardless of the types of emission exchange markets and emission permits comparing the rate of returns. However, comparing the GARCH variance, the volatility between ECX EUAs and CCX-CFIs and the volatility between EUAs(CERs) futures and daily futures are different with the exception of the volatility between EUAs futures and CERs futures. In conclusion, the price volatility depends on the types of exchanges and the types of emission permits.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.457-461
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• 2006

비점원 농촌유역으로부터 강우시 영양물질(질소, 인)의 유출특성을 파악하기 위해 2002년부터 2005년까지 5개의 강우사상을 대상으로 $2{\sim}12$시간 간격으로 유량 및 수질을 측정하였다. 강우사상시 TN농도는 유량이 증가함에 따라 상승하여 최대농도를 보인 후, 유량감소에 따라 농도가 감소하는 경우와 초기농도보다 높은 농도로 유지되는 경우의 두 가지 경향을 보였다. TP농도는 유량의 증가에 따라 급격한 상승을 보였고, 최대 값 이후 농도가 낮아져 거의 초기농도에 도달하였다. 또한, 초기농도에 대한 최대농도값의 비는 TP가 TN보다 크게 나타났다. 농촌 소유역에서의 초기유출현상(first-flush)은 40%의 누적유출량을 나타낼 때 TP의 누적유출부하량은 $70{\sim}86%$를 기록하여, 도시유역(60%)과 광역논(50%)보다 크게 나타났는데, 이는 농촌 소유역이 경사가 크고 밭 등에서 강우로 인한 토양침식 등의 영향을 크게 받기 때문으로 사료된다. 4개의 강우사상에 대한 질소의 용존성 성분의 비(TN/TDN비)는 93.6%를 나타내 질소는 대부분 용존성 형태로 유출되는 것으로 나타났고, 인의 용존성 성분의 비(TP/TDP비)는 25.4%를 나타내 인의 대부분 입자성 형태로 유출되는 것으로 나타났다. 따라서, 비점원 농촌유역으로부터 TN부하를 저감시키기 위해서는 용존성 성분을 제공하는 비료의 시용량을 줄여야 하며, TP부하를 저감시키기 위해서는 강우시 입자성 인의 유출을 제어해야 한다. 이를 위해서는 비가 많이 오는 여름철에 나지(裸地)나 밭에 식생이나 멀칭(mulching) 등으로 토양침식을 방지하는 대책이나 하천변에 완충역(riparian buffer zone)을 설치하는 대책이 필요하다. 저수지 관리를 효과적으로 수행하기 위해서는 저수지 내부의 탁도 거동을 정확히 예측할 수 있어야 한다. 따라서 추후 동수역학 및 열역학에 기초한 3차원 수치모형 연구와 성층흐름에 정밀한 밀도류 실험연구 및 이에 대한 적용이 필요할 것으로 판단된다.함으로써 정보의 질적보장과 정보전환의 표준화방안을 제시하는 정보분석시스템이다.이용, 수자원의 지속적 확보기술의 특성에 따른 4개의 평가기준과 26개의 평가속성으로 이루어진 2단계 기술가치평가 모형을 구축하였으며 2개의 개별기술에 대한 시범적용을 실행하였다.하는 것으로 추정되었다.면으로의 월류량을 산정하고 유입된 지표유량에 대해서 배수시스템에서의 흐름해석을 수행하였다. 그리고, 침수해석을 위해서는 2차원 침수해석을 위한 DEM기반 침수해석모형을 개발하였고, 건물의 영향을 고려할 수 있도록 구성하였다. 본 연구결과 지표류 유출 해석의 물리적 특성을 잘 반영하며, 도시지역의 복잡한 배수시스템 해석모형과 지표범람 모형을 통합한 모형 개발로 인해 더욱 정교한 도시지역에서의 홍수 범람 해석을 실시할 수 있을 것으로 판단된다. 본 모형의 개발로 침수상황의 시간별 진행과정을 분석함으로써 도시홍수에 대한 침수위험 지점 파악 및 주민대피지도 구축 등에 활용될 수 있을 것으로 판단된다. 있을 것으로 판단되었다.4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월이하의 중단기가 적합함을 발견하였다. 이상의 행태적 측면과 투자성과측면의 실증결과를 통하여 한국주식시장에

• The Korean Journal of Financial Management
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• v.24 no.2
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• pp.1-40
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• 2007

We test a model of investment-cashflow-growth opportunities relationship in order to estimate the sensitivities to investments. In this study, we use a new proxy variable for the value of growth opportunities(hereafter "VGO"), which is based on the seminal papers of M&M(1958:1961:1963) and Lee(2006;2007). The empirical findings on the sensitivities of cashflow and growth opportunities are as follows. First, when the traditional proxy variables for the growth opportunities such as Tobin's Q, MBR and sales growth are included with the new proxy VGO in the estimation, their coefficients are turned out to be insignificant. Second, only the new proxy variable VGO shows a statistically significant positive sensitibity to investment, which can be regarded that the growth opportunities hold the positive influences to investments. Third, the Tobin's Q can be decomposed into three factors such as the value of growth opportunities(VGO), the value of asset-in-place and valuation errors. It turns out that only the VGO shows a statistically significant positive relationship with investment among others. This means that the new variable VGO is a good proxy variable for the growth opportunities in the investment-cashflow sensitivity analysis. In sum, thanks to the above findings in this study, we can say that it will not be proper to choose a proxy variable for the growth opportunities from the traditional set of proxies such as Tobin's Q, MBR, or sales growth rate.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.2 no.2
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• pp.93-120
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• 2007

To promote the commercialization of high technology based start-up company, it is essential to activate technology trading for the Innovative Small & Medium companies which eager to acquire technology competitiveness through technology trading and facilitate financial system which provide Small & Medium companies with technology commercialization money. This study focus on enhancing credibility of technology valuation solutions through the improvement of the existing technology valuation solutions. The existing technology valuation solutions in practice have deficiency in reasonable valuation because of subjective technology factor's calculation. And the commercialization risk of high technology based start-up companies cannot be fully reflected in the existing valuation solutions. The high risk of technology commercialization acts as a hurdle in the facilitation of providing money for the start-up companies. The improved new model will have more acceptable objectivity and reasonably reflect the commercialization risk of start-up companies. The new model has two distinctive features compared to existing solutions. The new model newly adopts commercialization success factor which reflects the risk of high technology based start-up company. And the new model excludes technology factor which is controversial among interested parties. The exclusion of technology factor will improve the objectivity of technology valuation and the adoption of commercialization success factor will solicit investor and capitalist who concern the high risk of technology based start-up companies. In conclusion, the improved new model is expected to activate technology trading and facilitate the money market through which high technology based start-up companies raise commercialization money.