• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.747-756
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• 2010

With the recent recession, studies on the economy are actively being conducted throughout the industry. Based on the Small Business data registered in the Credit Guarantee Fund, we estimated the survival probability in the context of the survival analysis. We also analyzed the survival time for the construction and the other industries which are distinguished depending on the types of business and assets in the Small Business. The survival probability was estimated by using the life-table and the difference between the survival probabilities for the different types of business was described via the method of the Log-rank test and the Wilcoxon test. We found that the small business with over one billion asset has the highest survival probability and that with less than 1000 million asset showed the similar survival probability. In terms of types of business Wholesale and Retail trade industry and Services were relatively high in the survival probability than Light, Heavy, and the construction industries. Especially the construction industry showed the lowest survival probability. Most of the Small Business tend to increase in the hazard rate over time.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.13
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• pp.1013-1032
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• 2000

At present, the scale of Electronic Commerce through internet has been rapidly increasing due to the development of information & communication technology, and aggregated to 2.4 billion dollar in America last year (1998). The market scale of worldwide electronic commerce is also presumed to be about 130 billion dollar in 2000, and to occupy more than 20% of the whole world trade in world 2020. Since the right of trademark, despite of being effective only in registered nations on the principle of territorialism, is unified on the cyber space of internet without domestic barrier or local limitation which make it easier to conduct the distribution of information rapidly through the address-internet domain name, those are very important that the systematic dispute-solving plan on problems such as decision of its Act and international jurisdiction to be established, in an effort to prevent the newly emerging dispute instances such as trademark infringement and improper competitiveness. In addition, it is natural that on the threshold of the electronic commerce age which formed with an unified area without the worldwide specific regulation, each country including us makes haste with the enactment of "electronic commerce Act" aiming at coming into force in 1999, in keeping with getting through "non-tariff law on electronic commerce" by U. S. parliament on May, 1998. In view of the properties of electronic commerce transactions through internet, there are the large curtailment of distributive channel, surmounting of restrictions on transaction area, space and time and the easy feedback with consumer and the cheap-required capital, from which the problems may arise - registration of trademark, the trademark infringement of domain name and the protection of prestigious trademark. Therefore, it is necessary to take the counter-measure, with a view of reviewing the infringement of trademark and domain name and the instances of each national precedent and to preventing the disputes. The improvement of the persistent system should be needed to propel the harmonious protection of those holding trademark right's credit and demanders' expectant profit by way of the righteous use of trademark.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.85-92
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• 2015

Recently more and more shortened of corporation's sustainable longevity at the enterprise, and enterprise environment is also changing drastically. In this study, we wanted to obtain a solution that enable to continue the company's corporate longevity through critical factor analysis of the Japan Shinise. In the analysis results of Japan corporation as Doraya, Deicoko, Shinise longevity, we can explain about critical factors like that credit, tradition, customization, products development, changes of management methods and finding a global new markets. Also, In this study, analyzed a significance of critical factors for focusing on each cases and theories using Analytic Hierarchy Process(AHP), and did prediction and analysis about critical longevity factors. However, it need to collect sufficient data and a lots of variables for input. because the sample may be it insufficient. Results of the study, will be expected to be a useful guide for analysis of longevity factors at the company in the future.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.45-59
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• 2022

Purpose - This study investigates the performance of investment strategies incorporating estimated stock market cycle based on a lead-lag relationship between business cycle and stock market cycle, thereby deriving empirical implications on risk management. Design/methodology/approach - The data period ranges from June 1953 to September 2022 and de-trended short rate, term spread, credit spread, stock market volatility are considered as major input variables to estimate business cycle and stock market cycle by applying probit model. Based on the estimated stock market cycle, two types of strategies are constructed and their performance relative to the benchmark is empirically examined. Findings Two types of strategies based on stock market cycle are considered: The first strategy is to long(short) on stocks when stock market stage is expected to be an expansion(a recession), and the second one is to long on stocks(bonds) when expecting an expansion(a recession). The empirical results show that the strategies based on stock market cycle outperforms a simple buy and hold strategy in both in-sample and out-of-sample investigation. Also the out-of-sample evidence suggests that the second strategy which is in line with asset allocation is more profitable than the first one. Research implications or Originality The strategies considered in this study are based on the estimated stock market cycle which only depends on a few easily available financial variables, thereby making easier to establish such a strategy. It implies that investors enhance investment performance by constructing a relatively simple trading strategies if they set their position on stocks or choose which asset class to buy conditioning on stock market cycle.

• Asia-Pacific Journal of Business
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• v.13 no.4
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• pp.91-107
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• 2022

Purpose - This study quantitatively examines the level of financial inclusion of a microfinance institution in each region and how this is changing recently, and examines the level of financial inclusion by region and various financial characteristic factors related to it. It was empirically verified what kind of significant impact actually has on the institution's major management performance indicators (stability, profitability, efficiency, and public interest). Design/methodology/approach - It was confirmed that the institution's financial inclusion index declined rapidly after 2015 as a whole, although there were some differences by region depending on regional characteristics. However, considering the fact that the number of branches per 100,000 adult population is steadily increasing nationwide, it was found that, contrary to what is known, the simple decrease in the number of branches of the institution was not the main cause. Findings - The analysis results of this study show that the institution's efforts for financial inclusion have a positive impact on profitability, stability, efficiency, and public interest, and that the institution pursues profitability, efficiency, stability, and public interest. showed that some trade-offs exist. In other words, overall, it was analyzed that profitability of the institution has a positive effect on efficiency, and efficiency has a positive effect on stability and public interest. Research implications or Originality - Since the institution's efforts to improve its profitability do not have a negative impact on its stability and public interest, it is judged that it is important to take a strategic stance, so excessive loan supply that exceeds the scope of the institution's own control needs to be avoided as much as possible. More detailed financial supply strategies and business management capabilities that enhance the asset soundness and management efficiency of safes need to be demonstrated.

• KDI Journal of Economic Policy
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• v.13 no.2
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• pp.141-161
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• 1991

Resale price maintenance has long been employed in book distribution, perhaps longer than for any other product. Another unusual practice in the book trade that has proven to be quite durable in spite of its substantial cost in real resources is the returns policy. Publishers typically grant the right to return unsold books within a stipulated time for full credit against future orders. This paper investigates the functions and effects of resale price maintenance in the book trade, and argues that resale price maintenance and returns are substitute methods of providing the same economic function. Resale price maintenance can be used to compensate booksellers for initially stocking books with uncertain prospects and for providing a conduit through which manufacturers acquire information about consumer demand (market testing services). Permitting the return of unsold books for full credit places a floor under retail prices and transfers a considerable portion of the cost of introducing a new product line back to the publisher. Both reflect publishers' needs to have their books displayed. In the U.S. returns privileges were first proposed in 1913, roughly coincident with the Macy decision outlawing RPM. Publishers slowly granted return privileges, which become nearly universal by 1970. The decline in margins in recent years has been accompanied by an increase in returns as the return policy served to substitute for lost margins on successful titles as a methods of compensating full-line booksellers. In contrast, returns privileges are unusual in countries where price maintenance in books has been practiced. These observations are consistent with our analysis. In Korea, resale price maintenance of books is practiced under an exception to Korean antitrust law. The availability of effective price maintenance is likely to reduce the use of returns programs. Since consumers prefer to obtain books at outlets where they know the books are likely to be stocked rather than taking a chance on stores that carry a more limited line, it also provides a strong incentive for booksellers to expand. But the privilege of resale price maintenance should be confined to books which publishers want to be price maintained. Resale price maintenance and returns system differ in the transactions costs associated with inventory holding, and publishers' judgement on the comparative advantage of the two schemes should be honored. Publishers should also remain free to authorize sales at discount at any time not to impair the ability of booksellers to dispose of product variants that prove unpopular.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• International Commerce and Information Review
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• v.8 no.4
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• pp.105-121
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• 2006

This study is related with the judgements of our country's supremcourt against the transaction of Letter of Credit which is beneficiary's fraudulent trade deal. In this case I think to analyse the judgements and to present the basic grounds on which the judgements were established. In Letter of Credit transaction, there are the major parties, such as, beneficiary, issuing bank, or confirming bank and the other parties such as applicant, negotiating bank, advising bank and paying bank. Therefore, in this cases, the beneficiary, the French Weapons' Supplier who did not shipped the commodities, created the false Bill of Lading, let his dealing bank make payment against the documents presented by him and received the proceeds from the negotiating bank or collecting bank, thereafter was bankrupted and escaped. For the first time, even though the issuing bank conceived that the presented documents were inconsistent with the terms of L/C. it did not received the payment approval from the applicant against all the discrepancies, made the negotiating bank pay the proceeds to exporter and thereafter, delivered the documents to the applicant long after the time of the issuing bank's examination of documents. The applicant who received the documents from the issuing bank, instantly did not examine the documents and inform to the issuing bank whether he accepted the documents or not. Long time after, applicant tried to clear the goods through custom when he knew the bill of ladings were false and founded out the documents had the other discrepancies which he did not approved. As the results, the applicant, Korea Army Transportation Command claimed, that the issuing bank must refund his paid amount because issuing bank examined the documents unreasonably according to u.c.p 500 Act 13th, 14th. In spite of the applicant's claim, the issuing bank argued that it paid the proceeds of L/C reasonably after receiving the applicant's approval of an discrepancy of document, the delayed shipment, but for concerning the other discrepancies, the trivial ones, the applicant did not examined the document and noticed the discrepancies in reasonable time. Therefore the applicant sued the issuing bank for refunding it's paid proceeds of L/C. Originally, this cases were risen between Korea Exchange Bank and Korea Army Transportation Command. As result of analysing the case, the contents of the case case have had same procedure actually, but the lower courts, the district and high courts all judged the issuing bank was reasonable and did not make an error. As analysing these supreme court's judgements, the problem is that whether there are the applicant's liability of examining the documents and informing its discrepancies to the issuing bank or not, and if the applicant broke such a liabilities, it lost the right of claiming the repayment from issuing bank. Finally to say, such applicant's liabilities only must be existed in case the documents arrived to the issuing bank was delivered to the applicant within the time of the documents examination according to u.c.p 500 Act 14, d. i. But if any the documents were delivered to applicant after time of the documents examination, the applicant had not such liabilities because eventhough after those time the applicant would have informed to the issuing bank the discrepancies of documents, the issuing bank couldn't receive repayment of its paid proceeds of document from the negotiating bank. In the result after time of issuing bank's examination of documents, it is considered that there's no actual benefit to ask the applicant practice it's liability. Therefore finally to say. I concluded that the Suprem Court's judgement was much more reasonable. In the following, the judgements of the supreme court would be analysed more concretely, the basic reasons of the results be explained and the way of protecting such L/C transaction would be presented.

• International Commerce and Information Review
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• v.19 no.1
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• pp.43-63
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• 2017

I focused on LVTS compare with Fedwire to advance a research effects in this paper. The Fedwire Funds Service is generally used to make large-value, time-critical payments. The Federal Reserve Banks provide the Fedwire Funds Service, a real-time gross settlement system that enables participants to initiate funds transfer that are immediate, final, and irrevocable once processed. The Fedwire Funds Service is a credit transfer service. While, The LVTS(Large Value Transfer System) is the high value electronic wire system that facilitates the transfer of irrevocable payments in canadian dollars across the country. Through LVTS, funds can be transferred between participating financial institutions virtually instantaneously in a fully collateralized environment. Thus in this article, first of all, I considered features of payment system between LVTS and Fedwire. Second, I analyzed the governing structure and legal background. Third, I focused on the operational policy and risk aversion policy. Lastly, I suggested that the payment and banking system have to assume, with good reason, more efficiently accurately and securely operation together with conclusion.

• Management & Information Systems Review
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• v.28 no.3
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• pp.1-23
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• 2009

Prior bankruptcy studies have established that bankrupt firm's pre-filing financial ratios are different from those of healthy firms or of randomly selected going concerns. However, they may not be sufficiently different from the financial ratios of other firms in financial distress to allow the development of a ratio-based model that predicts bankruptcy with reasonable accuracy. As the result, in the multiple discriminant model, independent variables divided firms into bankrupt firms and healthy firms are retained earnings to total asset, receivable turnover, net income to sales, financial expenses, inventory turnover, owner's equity to total asset, cash flow to current liability, and current asset to current liability. Moreover four variables Retained earnings to total asset, net income to sales, total asset turnover, owner's equity to total asset indicate that these valuables classify bankrupt firms and distress firms. On the other hand, Owner's Equity to borrowed capital, Ordinary income to Net Sales, Operating Income to Total Asset, Total Asset Turnover and Inventory Turnover are selected to predict bankruptcy possibility in the Logistic regression model.