• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.2
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• pp.113-127
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• 2012

From the end of 1st quarter of 2012, Korean mandatory firms had started releasing financial reports conforming to the K-IFRS(Korean adopted International Financial Reporting Standards). Major characteristics of IFRS, such as 'principles based' features, consolidated reporting, 'fair value' measurement, increased pressure for non-financial disclosures have resulted in brief and various disclosure practices regarding the main body of each statements and vast amount of note description requirements. Meanwhile, a host of previous studies on IFRS disclosures have incorporated regulatory and/or 'compete information' perspectives, mainly focusing on suggesting further enforcement of strengthened requirements and providing guidelines for specific treatments. Thus, as an extension of prior findings and suggestions this study had explored to conduct an integrative approach embracing views of the reporting entities and the users of financial information. In spite of all the state-driven efforts for faithful representation and comparability of corporate financial reports, an overhaul of disclosure practices of fiscal year 2010 and 2011 had revealed numerous cases of insufficiency and discordance in terms of mandatory norms and market expectations. As to the causes of such shortcomings, this study identified several factors from the corporate side and the users of the information; some inherent aspects of IFRS, industry/corporate-specific context, expenditures related to internalizing IFRS system, reduced time frame for presentation. lack of clarity and details to meet the quality of information - understandability, comparability etc. - commonly requested by the user group. In order to improve current disclosure practices, dual approach had been suggested; Firstly, to encourage and facilitate implementation, (1) further segmentation and differentiation of mandates among companies, (2) redefining the scope and depth of note descriptions, (3) diversification and coordination of reporting periods, (4) providing support for equipping disclosure systems and granting incentives for best practices had been discussed. Secondly, as for the hard measures, (5) regularizing active involvement of corporate and user group delegations in the establishment and amendment process of K-IFRS (6) enforcing detailed and standardized disclosure on reporting entities had been recommended.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.31
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• pp.27-56
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• 2006

Today's financial institutions usually take environmental issues seriously into consideration as they could not evade lender liability in an increasing number of cases. On the international scene, a brand-new concept of the "Equator Principles" in the New Millenium has driven more and more international banks to adopt these Principles in project financing. Sustainable development has been a key word in understanding new trends of the governments, financial institutions, corporations and civic groups in the 21st century. The Equator Principles are a set of voluntary environmental and social guidelines for sustainable finance. These Principles commit bank officers to avoid financial support to projects that fail to meet these guidelines. The Principles were conceived in 2002 on an initiative of the International Finance Corporation(IFC), and launched in June 2003. Since then, dozens of major banks, accounting for up to 80 percent of project loan market, have adopted the Principles. Accordingly, the Principles have become the de facto standard for all banks and investors on how to deal with potential social and environmental issues of projects to be financed. Compliance with the Equator Principles facilitates for endorsing banks to participate in the syndicated loan and help them to manage the risks associated with large-scale projects. The Equator Principles call for financial institutions to provide loans to projects under the following circumstances: - The risk of the project is categorized in accordance with internal guidelines based upon the environmental and social screening criteria of the IFC. - For Category A and B projects, borrowers or sponsors are required to conduct a Social and Environmental Assessment, the preparation of which must meet certain requirements and satisfactorily address key social and environmental issues. - The Social and Environmental Assessment report should address baseline social and environmental conditions, requirements under host country laws and regulations, sustainable development, and, as appropriate, IFC's Environmental, Health and Safety Guidelines, etc. - Based on the Social and Environmental Assessment, Equator banks then make agreements with borrowers on how they mitigate, monitor and manage the risks through a Social and Environmental Management System. Compliance with the plan is included in the covenant clause of loan agreements. If the borrower doesn't comply with the agreed terms, the bank will take corrective actions. The Equator Principles are not a mere declaration of cautious banks but a full commitment of lenders. A violation of the Principles in the process of project financing, which led to an unexpected damage to the affected community, would not give rise to any specific legal remedies other than ordinary lawsuits. So it is more effective for banks to ensure consistent implementation of the Principles and to have them take responsible measures to solve social and environmental issues. Public interests have recently mounted up with respect to environmental issues on the occasion of the Supreme Court's decision (2006Du330) on the fiercely debated reclamation project at Saemangeum. The majority Justices said that the expected environmental damages like probable pollution of water and soil were not believed so serious and that the Administration should continue to implement the project seeking ways to make it more environment friendly. In this case, though the Category A Saemangeum Project was carried out by a government agency, the Supreme Court behaved itself as a signal giver to approve or stop the environment-related project like an Equator bank in project financing. At present, there is no Equator bank in Korea in contrast to three big banks in Japan. Also Korean contractors, which are aggressively bidding for Category A-type projects in South East Asia and Mideast, might find themselves in a disadvantageous position because they are generally ignorant of the environmental assessment associated with project financing. In this regard, Korean banks and overseas project contractors should care for the revised Equator Principles and the latest developments in project financing more seriously. It's because its scope has expanded to the capital cost of US$10 million or more across all industry sectors regardless of developing countries or not. It should be noted that, for a Korean bank, being an Equator bank is more or less burdensome in a short-term period, but it must be conducive to minimizing risks and building up good reputation in the long run.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.279-309
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• 2009

Greenhouse gas emissions should be precisely forecast to reduce the emissions from industrial production processes. This study calculated the direct and indirect $CO_2$ emission intensities of 401 industries using the Input-Output tables 2003 and statistical data on the amount of energy use. This study had some limitations in drawing study findings because overseas data were used given the lack of domestic data. Other limiting factors included the oil distribution problems in the oil refinery sector, re-review of carbon neutral, and insufficient consideration of waste treatment. Nonetheless, this study is very meaningful since the direct and indirect $CO_2$ emission intensities of 401 industries were calculated. Specifically, this study considered from the zero-waste perspective the effects of waste, which attract interest worldwide since coke gas and gas from the steel industry are obtained as byproducts for the first time in Korea. According to the results of the analysis of $CO_2$ emission intensity per industry, typical industries whose indirect $CO_2$ emission intensity is high include crude steel making, Remicon, steel wire rods & track rail, cast iron, and iron reinforcing rods & bar steel. These industries produce products using the raw materials produced in the industrial sector whose $CO_2$ emission intensity is high. The representative industries whose direct $CO_2$ emission intensity is high include cement, pig iron, lime & plaster products, andcoal-based compounds. These industries extract raw ore from nature and refine them into raw materials that are useful in other industries. The findings in this study can be effectively used for the following case: estimation of target $CO_2$ emission reduction level reflecting each industrial sector's characteristics, calculation of potential emission reduction of each policy to reduce $CO_2$ emissions, identification of a firm's $CO_2$ emission level, and setting of the target level of emission reduction. Moreover, the findings in this study can be utilized widely in fields such as System of integrated Environmental and Economic Accounting(SEEA) and Material Flow Analysis(MFA) as the current topic of research in Korea.

• Management & Information Systems Review
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• v.38 no.4
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• pp.61-78
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• 2019

When calculating gains from transfers of assets inherited or donated, the value recognized at the market price as of the date of inheritance or acquisition is recognized as the actual transaction value at the time of acquisition. However, Precedents for the appeal for review by the NTS, the request for adjudgment by the Tax Tribunal(TT) and the request of examination by the Board of Audit and Inspection of Korea(BAI) and the cases of the lawsuit have not shown a consistent results on how much such a the actual transaction value will be measured. This study investigates the operating state of the current tax appeal system using the statistical data of the TT, NTS, and BAI and cases of the lawsuit from 2008 to 2017, and suggests the Improvement of Capital Gains Tax Act on the transfer of inherited and donated property. As a result, total number of requested cases has diminished because cases of the pre-assessment review and the reconsideration appeal by the NTS have decreased steadily over the past decade, while the cases of the lawsuit and the administrative trials(the request for adjudgment by the TT, the appeal for review by the NTS, and the request of examination by the BAI) have been steadily increasing. Also This study found that more than 40% of the complainants proceeded with the cases of the lawsuit proceedings in disagreement with the disposition of tax dissatisfaction under the administrative trials. In addition, Even though the retrospective appraisal price is not recognized as the market price due to the strict interpretation of the tax regulations, it can be seen that it is interpreted as a more expanded concept in the application of the market price than the government office or the tax judge. Therefore, according to the precedents of the cases lawsuit, it is necessary to establish a regulation on the recognition of retroactive appraisal value.

• Journal of Aquaculture
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• v.22 no.1
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• pp.42-50
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• 2009

Shrimp farming which is entirely conducted in outdoor ponds in the west coast of Korea has been suffered from mass mortality due to viral epizootics. Intensive indoor shrimp culture under limited water exchange can solve these problems of outdoor ponds including viral transmission from environment, pollution due to discharge of rearing water, low productivity and limited culture period. In this study, juvenile L. vannamei (B.W. 0.08-0.09 g) was stocked with $3,000-5,455/m^3$ in density in four raceway tanks (two $12.9\;m^2$, two $18\;m^2$ tanks) and cultured for 42 days with 2.7-3.4% of daily water exchange. Results from four tanks showed FCR of 0.79-1.29, survival of 38.2-48.0%, and yields of $2.49-4.22\;kg/m^3$ which is consistent with 12-20 and 8-14 times higher than those of commercial shrimp hatchery and outdoor pond in Korea, respectively. Concentrations of total ammonia nitrogen in all four tanks were 1.11-1.42 ppm in mean level and did not exceed 6.0 ppm (0.096 ppm of $NH_3$) which is still acceptable levels for shrimp growth. During the culture trial, concentration of $NO_2$-N rapidly increased from stocking, resulting in mean concentration of 18.45-22.07 ppm. It also exceeded 10 ppm over four weeks and maintained at 35-45 ppm for four days in all tanks, accounting for low survival of shrimp due to long-term exposure to high concentration of $NO_2$-N. Nevertheless, the results with survival rate over 38% from raceways which experienced the extreme $NO_2$-N levels suggests that under "biofloc system" white shrimp can acclimate to high $NO_2$-N concentration to some degree.

• Management & Information Systems Review
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• v.33 no.4
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• pp.1-19
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• 2014

This Study focuses on the university students' job attitude and cost of employment preparation. Nowadays, many university and college students spend a big money improving their employment preparation such as studying on foreign language, getting various kinds of certificates and tooth correction, clothing etc. for employment interview. This study investigated the cost of employment preparation and Job attitude of the 484 students of universities and colleges, the analysis of the collected data was conducted with SPSS 12.0 program by using frequency analysis, factor analysis, reliability assessment, correlation test, t-test, one way ANOVA. The university students paid more costs of employment preparation such as a language training abroad, a private training, and clothing than the college students. Also, Allied social science students paid more costs of the language training abroad, and clothing than allied computer science and allied design students. The female students paid more money than male students for tooth correction. The costs of language training abroad, private training and clothing are affected the students' socioeconomic background of a home. Regarding the job attitude of students, the university students are feeling more positive than the college students of the employment efficacy and cognition of the education environment. As result, the differences in the cost of employment preparation by the university type, faculty major course, their sex, and socioeconomic background of a home. The student's employment-efficacy and cognition of the education environment are also differences between the university and the college students. So, to improve the job attitude, developing their ability for employment preparation, educational programs should be arranged in school and continuous researches are needed.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.353-365
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• 2019

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R², and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

• 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 the Korean Institute of Traditional Landscape Architecture
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• v.39 no.3
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• pp.33-41
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• 2021

This study identified the scale that traditional landscape design has taken up by analyzing a total of 1037 services for design of cultural heritage that had been ordered by the government agencies from 2018 to 2020, and has drawn characteristics of traditional landscape design focusing on major cases. The results are as follows. First, the number of order cases for traditional landscape design has shown differences annually in the services of design of cultural heritage, but the design amount has been found to have the similar average annually, which confirmed that the same level has been maintained each year. It was found that the number of cases of traditional landscape design requiring responsibilities or participations of landscape engineers for 3 years in the entire design had a high proportion of approximately 26%. Second, the traditional landscape design has required professional knowledge and experiences of landscape engineers that could not be replaced by the business operator for design of cultural heritage consisting of architects. The expertise has been shown differently depending on types of construction. First, the topographical design for the work to build a foundation has required understanding of ground shapes and its elevations and professional knowledge on calculation of the amount of the earth work and the remains maintenance technique etc. The plantation design has required basic knowledge on growth characteristics of trees and the environment for growth and understanding of the vegetation landscape of the past. Meanwhile, the design for traditional pavement and traditional landscape structures and facilities has required the expertise on traditional materials that are different from the modern ones and their processing and construction methods. The understanding of changes to water paths and ecosystem, the principles of fluids, and characteristics of each type of fluid was essential for the design for the ecological landscape work including the maintenance of a water system such as rivers etc. As such, the traditional landscape design has a scale accounting for approximately one fourth of the entire cultural heritage design and requires the expertise differentiated from other fields. This improves the provisions of the current law on limiting the actual design, suggesting the need for the establishment of a traditional landscape design company so that all traditional landscape designs can be carried out by landscape engineers.