• Proceedings of the KSR Conference
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• 2001.05a
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• pp.44-51
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• 2001

To account for uncertainties involved in an economic analysis of project, sensitivity analysis are usually being done in Korea. Though useful for policy analysis, but it larks explicit consideration of probability of occurring certain events considered in the sensitivity analysis. Risk analysis otherwise can explicitly account for the probability of certain event which has dire impact on project viability, such as cost, discount rate, and size of benefit. This paper reports experience of applying risk analysis method for economic evaluation of railroad investment. Probability distribution of event has paramount impact on the risk analysis results, while not many prior researches dealt with these issues. Probability distribution of rolling stock cost and operating cost, in addition to those cost variables, are developed considering railway demand in this study. Case study results are reported. Issues in applying risk analysis are reported in addition to further research direction.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• Korean System Dynamics Review
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• v.12 no.4
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• pp.157-175
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• 2011

The purpose of this paper is to find out the effects of the gambler's fallacy bias on the supply chain. For this study, the simulation was based on a casual structure of the Beer Distribution Game from Sterman(2000)'s Business Dynamics and designed into 2 different models : the first model carries the exact same structure as the reference mentioned above and for the second model, the comparison model is used reflecting gambler's fallacy bias. Each model has 2 different demand patterns. The 4 cases of models was tested with 1,000 different random number seeds. The results for the simulation are following : In the aspect of the inventory and out of stock, the basic model resulted better than the comparison. However, in the bullwhip effect, the comparison model has less than the basic in terms of the level demand pattern. But there was no significant difference in the cycle demand.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.36-43
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• 2013

Many retailer store managers are experiencing the situation where some customers balk at purchasing products if the stock is low. In this paper, we extend the single period newsvendor model in an environment of customer balking behavior occurring at double threshold inventory levels assuming the chance of sales during balking is a discrete function of inventory level. Our analysis is based on the assumption that only the mean and the variance of demand are known, without assuming any specific distributional form. We derive the explicit general expression of optimal order quantity with unknown distribution of demand with double threshold inventory levels of customer balking. Then, we illustrate the concepts developed here through simple numerical examples and conclude the future research topics under balking situation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.451-458
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• 2021

The objective of this research is to analyze the effect of bad credit and liquidity on bank performance with the mediation of capital adequacy. Data were provided by banking institutions listed on the Indonesia Stock Exchange from the period of 2011-2019. The analysis technique was PLS-SEM supported by an application named WarpPLS 6.0. The results of the research show that the effect of bad credit and liquidity on bank performance is not significant. A high level of bad credit is associated with a low level of bank performance. Bank earnings decline along with low profitability. This relationship is not significant because banks can still cover some proportions of bad credit through capital availability. Capital adequacy as an intervening variable has mediated partially the effect of bad credit and liquidity on bank performance. Besides, capital adequacy has a strong effect on credit distribution. Agency theory says that the owner of the fund (the savers of saving account, current account, deposit account) is called principal while the bank as the trusted institution to manage the fund is called an agent. If customers fulfill their duty, then bad credit never happens.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1431-1436
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• 2018

We study the scaling of the price fluctuation in the Korean housing market. From the numerical analysis, we show that the normalized return distribution of the housing price, P(r), has a fat-tail and is well approximated by a power-law, $P(r){\sim}r^{-({\alpha}+1)}$, with ${\alpha}{\simeq}3$ for the whole data set. However, if we divide the data into groups based on the trading patterns, then the value of ${\alpha}$ for positive tail and negative tail can be different depending on the trading patterns. We also find that the autocorrelation function of the housing price decays much slower than that of the stock exchange markets, which shows a unique feature of the housing market distinguished from the other financial systems.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.5 no.2
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• pp.1-8
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• 2002

The aim of this study was to generate systemic data for the aquatic plant distribution according to water depth and crossing slope in the shoreline. The results of this study were as follows; 1. Anxiety to 0 near area Bidens frondosa, Scirpus tabernaemontani, Carex dispalata etc. total class 21 observe, and Phragmites communis, Iris pseudoacorus etc. class 6 of anxiety 0-70cm extent examined. Class 21 of anxiety observed all such as Bidens frondosa, Scirpus tabernaemontani, Carex dispalata in near area to 0, and Phragmites communis, Iris pseudoacorus etc. class 6 of anxiety 0-70cm extent examined. Anxiety 70-100cm extent Nymphoides indica, Ttapa japonica etc.. class 2 appeared to line Zizania latifolia, Typha angustata back 2 papers, 130cm and examined that Nelumbo nucifera was limit anxiety state 230cm. 2. Aquatic plants of Phragmites communis, Zizania latifolia, Typha angustata etc. range mainly to gentle gradient of slant 10 degree low and distribution pattern was ranging by Zizania latifolia, Typha angustata, Phragmites communis period of ten days from deepwater place. Nelumbo nucifera was forming become independent stock keeping away invasion of plant that ability to breed was different because was prosperous. Slant 10 bores was growing near sleep in been strange steep slope earth and distribution of emerged plant appeared punily and emerged plant and swampy land plant were ranged extensively in gentle gradient of 10 degree low. 3. On lake surrounding plant when wish to do distribution of natural conditions reference need to. That is, gentle gradient and distribution form of steep slope earth are different, and same pitch must consider enough this because appear as distribution, distribution according to that some plant species were growing was different.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1263-1274
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• 2013

VaR (value at risk), which represents the expectation of the worst loss that may occur over a period of time within a given level of confidence, is currently used by various financial institutions for the purpose of risk management. In the majority of previous studies, the probability of return has been modeled with normal distribution. Recently Chen et al. (2010) measured VaR with asymmetric Laplacian distribution. However, it is difficult to estimate the mode, the skewness, and the degree of variance that determine the shape of an asymmetric Laplacian distribution with limited data in the real-world market. In this paper, we show that the VaR estimated with (symmetric) Laplacian distribution model provides more accuracy than those with normal distribution model or asymmetric Laplacian distribution model with real world stock market data and with various statistical measures.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.37-51
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• 2015

Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

• Journal of Distribution Science
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• v.16 no.2
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• pp.83-88
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• 2018

Purpose - For distribution corporate, the method of recognizing sales revenue may be different depending on the type of distribution transaction. Until the change in accounting standards for revenue recognition was made in 2002, the distribution corporate recognized the full amount of sales of goods regardless of the type of transaction. However, in accordance with accounting standards for revenue recognition, which began to be applied in 2003, distribution corporate differ in sales revenue recognition by transaction type. The Purpose of this study is to analyze the impact of sales revenue on the corporate value after the change of the revenue recognition accounting standards. Research design, data, and methodology - We selected a comprehensive wholesale and retail corporate listed on Korea Exchange. The research model extends the Ohlson(1995) model and regresses whether sales revenue affecting the corporate value is discriminatory value relevance between the corporate affected by changes in accounting standards for revenue recognition and those not. Results - The results of the analysis are as follows. First, The average value of stock price, net asset per share, and earnings per share are all higher than those before the change of accounting standards for revenue recognition. However, the average value of sales per share is lower than that before the change of accounting standards for revenue recognition. Second, the relationship between corporate value and net asset per share, earnings per share and sales per share, the coefficient of net asset per share, earnings per share and sales per share are all statistically significant positive value. Therefore, in explaining corporate value, besides net asset per share and earnings per share, sales per share provides additional information. And the coefficient of interaction variable between accounting standard change and sales per share is a statistically significant positive value. This result indicating that after the change of the revenue recognition accounting standards the usefulness of sales revenue has increased. Conclusions - The change in accounting standards for revenue recognition led to a decrease in distribution corporate sales revenue but the higher the relevance of the corporate value of the sales revenue information. These results shows that the change of accounting standards that reflects the transaction type of retailers was a revision to increase the value relevance of sales revenue in valuation of corporate value.