In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.
The purpose of this study is to present practical improvement plans for policy fund support in national policy banks through an analysis of the efficiency of policy fund support. It targets small and medium-sized enterprises(SMEs) that received policy funding from national policy banks in '17 and '18 consecutively. As for the analysis method, characteristic analysis and corresponding sample T-test was performed. The analysis results are as follows. First, as a result of analyzing the characteristics of small and medium-sized enterprises, most of the financial funds were concentrated on the manufacturing industry. By region, the western region of Gyeonggi Province, by credit rating, was A grade, technology grade was T5, and the use of funds was mostly concentrated on facility funds. Second, as a result of efficiency analysis, profitability had a positive effect on total capital return, stability had a positive effect on interest compensation ratio, and activity had a positive effect on total capital turnover. In conclusion, it is expected to provide practical improvement plans to support policy funds to influence the growth and distribution of funds appropriate to the needs of SMEs.
Due to its role in maintaining the health of scientific societies, research ethics (or integrity) is notably receiving attention by academia, governments and even individuals who are not engaged in scientific researches. In this paper, I will introduce some valuable papers dealt with plagiarism as a representative research misconduct. In general, researcher's results that will soon be published must meet the crucial scientific criteria: originality, accuracy, reproducibility, precision and research ethics. The definition of plagiarism is "appropriation of another person's ideas, processes, results, or words without giving appropriate credit." Compared to fabrication and falcification, plagiarism is often considered as a minor misconduct. With intentionality, however, plagiarism can be corresponding to 'theft of intellectual product'. The context of plagiarism is not restricted to the stage of publication. It can be extended to prior stages of proposing (i.e. preparing the research proposal) and performing (executing the research), and reviewing (writing the review papers). Duplicate publication is regarded as a self-plagiarism in broad interpretation of plagiarism. To avoid dangers of plagiarism, earnest efforts from all members of scientific community are needed. First of all, researchers should keep 'transparency' and 'integrity' in their scientific works. Editorial board members and reviewers should keep fairness and well-deserved qualification. Government and research foundations must be willing to provide sufficient financial and policy support to the scientific societies; Up-graded editorial services, making good use of plagiarism detection tools, and thorough instruction on how to write a honest scientific paper will contribute to building up a healthy basis for scientific communities.
Agricultural risks are exacerbated by a variety of factors ranging from climatevariability and change, frequent natural disasters, uncertainties in yields and prices, weakrural infrastructure, imperfect markets and lack of financial services including limited spanand design of risk mitigation instruments such as credit and insurance. Indian agriculture has little more than half (53%) of its area still rainfed and this makes it highly sensitive to vagaries of climate causing unstable output. Besides adverse climatic factors, there are man-made disasters such as fire, sale of spurious seeds, adulteration of pesticides and fertilizers etc., and all these severely affect farmers through loss in production and farm income, and are beyond the control of farmers. Hence, crop insurance' is considered to be the promising tool to insulate the farmers from risks faced by them and to sustain them in the agri-business. This paper critically evaluates the performance of recent crop insurance scheme viz., Pradhan Mantri Fasal Bhima Yojana (PMFBY) and its comparative performance with earlier agricultural insurance schemes implemented in the country. It is heartening that, the comparative performance of PMFBY with earlier schemes revealed that, the Government has definitely taken a leap forward in covering more number of farmers and bringing more area under crop insurance with the execution of this new scheme and on this front, it deserves the appreciation in fulfilling the objective for bringing more number of farmers under insurance cover. The use of mobile based technology, reduced number of Crop Cutting Experiments (CCEs) and smart CCEs, digitization of land record and linking them to farmers' account for faster assessment/settlement of claims are some of the steps that contributed for effective implementation of this new crop insurance scheme. However, inadequate claim payments, errors in loss/yield assessment, delayed claim payment, no direct linkage between insurance companies and farmers are the major shortcomings of this scheme. This calls for revamping the crop insurance program in India from time to time in tune with the dynamic changes in climatic factors on one hand and to provide a safety-net for farmers to mitigate losses arising from climatic shocks on the other. The future research avenues include: insuring the revenue of the farmer (Price × Yield) as in USA and more and more tenant farmers should be brought under insurance by doling out discounts for group coverage of farmers like in Philippines where 20 per cent discount in premium is given for a group of 5-10 farmers, 30 per cent for a group of 10-20 and 40 per cent for a group of >20 farmers.
Journal of the Korean Data and Information Science Society
/
v.23
no.2
/
pp.257-269
/
2012
Global crisis expedites the change in the environment of industry and puts small size enterprises in danger of mass bankruptcy. Because of this, domestic small size enterprises is an urgent need of restructuring. 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 which are distinguished depending on the types of business in the small business. Financial variables were also conducted using COX regression analysis of small businesses by types of business. 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. In addition, we found that construction industry, the bigger BIS (bank of international settlements capital ratio) and current ratio are, the smaller default-rate is. But the bigger borrowing bond is, the bigger default-rate is. In the light industry, the bigger BIS and ROA (return on assets) are, the smaller a default-rate is. In the wholesale and retail trade industry, the bigger bis and current ratio are, the smaller a default-rate is. In the heavy industry, the bigger BIS, ROA, current ratio are, the smaller default-rate is. Finally, in the services industry, the bigger current ratio is, the smaller a default-rate is.
The purpose of this study is to analyze an experience of field practice perceived by vocational teachers. Data for analysis were collected from 689 vocational teachers who participated in the training at the Center for in-service teacher education in the School of Agriculture and Life Sciences, Seoul National University and at the Center for in-service teacher education of Chungnam National University. After screening, 685 responses were used in the analysis. As a result, it turned out that only 112 vocational teachers(16.5%) participated in the field practice for more than 4 weeks when they were in pre-service education. However, vocational teachers seemed to perceive that experience of field practice was generally required in pre-service education(average 4.07). In-depth questionnaire was conducted on 143 respondents who replied that they participated in field practice program for more than 4 weeks and those who participated in the program for less than 4 weeks but completed the paperwork. Most of vocational teachers who participated in field practice were placed in small and medium sized enterprises, stayed at home or relatives' home and commuted by the bus or subway. In this research, 34.8% of the vocational teachers who participated in field practice received financial compensation and 80.3% of the teachers got credit recognition. The perception of satisfaction on field practice program was found to be moderate(average 3.51).
While most of countries today are opposing the issuance of private-led cryptocurrency, nevertheless they are actively jumping into the issuance of government-led digital currency such as CBDC. This article aims to find an answer to this dual attitude of countries. To achieve the purpose, this article finds out the characteristics of political power and economic interest that digital currency has and applies it to the international dimension of the Bretton Woods II System. Then come up to the conclusion that the answer can be found in the fact that the current dual attitude of countries is closely related to the crisis of the international monetary order. The Bretton Woods II System, which led the world economy through reckless monetary expansion based on credit currency, exposed its limitations through the 2008 global financial crisis and put countries into difficulties. In this situation, the cryptocurrency, which appeared by raising the issue of the monopoly power of the central authority in issuing currency, had no choice but to act as an opportunity to drive countries further and further into a corner. This article views CBDC as a national response to address these issues. In other words, countries maintain their monetary power by absorbing the challenge of private digital currency at the government level through CBDC, and use this as a stepping stone to reorganize the international monetary order in crisis with the intention to use it as a means to their advantage. That is what this article is trying to argue.
Bitcoin is a blockchain technology-based digital currency that has been recognized as a representative cryptocurrency and a financial investment asset. Due to its highly volatile nature, Bitcoin has gained a lot of attention from investors and the public. Based on this popularity, numerous studies have been conducted on price and trend prediction using machine learning and deep learning. This study employed LSTM (Long Short Term Memory) and CNN (Convolutional Neural Networks), which have shown potential for predictive performance in the finance domain, to enhance the classification accuracy in Bitcoin price trend prediction. XAI(eXplainable Artificial Intelligence) techniques were applied to the predictive model to enhance its explainability and interpretability by providing a comprehensive explanation of the model. In the empirical experiment, CNN was applied to technical indicators and Google trend data to build a Bitcoin price trend prediction model, and the CNN model using both technical indicators and Google trend data clearly outperformed the other models using neural networks, SVM, and LSTM. Then SHAP(Shapley Additive exPlanations) was applied to the predictive model to obtain explanations about the output values. Important prediction drivers in input variables were extracted through global interpretation, and the interpretation of the predictive model's decision process for each instance was suggested through local interpretation. The results show that our proposed research framework demonstrates both improved classification accuracy and explainability by using CNN, Google trend data, and SHAP.
This study estimates connectedness index among the US, China, Europe, Japan, and South Korea using monthly economic policy uncertainty (EPU) data from January 2000 to December 2023. The connectedness index allows us to analyze the effect of global economic uncertainty on domestic economic uncertainty. The EPU is used as a proxy for economic uncertainty. Inter-country connectedness index is computed from variance decomposition. The findings from forecast error variance decomposition show that three-fourths of total uncertainty comes from economic uncertainty in the own country and one-fourth of total uncertainty comes from economic uncertainty in the others. The analysis on net pairwise connectedness reveals that, even though the extent of the effect of economic uncertainty in one country from economic uncertainty in another country varies over time, economic uncertainty in South Korea, a small-open economy, is mainly affected by economic uncertainty in the others. The reverse situation rarely happens except in the specific occurrence such as the collapse of the credit bubble in 2003 and the subsequent years, the inter-Korean summit and North Korea-the US summit in 2018, and the period from the first outbreak of COVID-19 on the implementation of the government's severe regulation against COVID-19.
A frequent flyer program is a loyalty program offered by many airlines. Typically, airline customers enrolled in the program accumulate frequent flyer miles corresponding to the distance flown on that airline or its partners. There are other ways to accumulate miles. In recent years, more miles were awarded for using co-branded credit and debit cards than for air travel. Acquired miles can be redeemed for free air travel; for other goods or services, such as travel class upgrades, airport lounge access or priority bookings. The first modern frequent flyer program was created Texas International Airlines in 1979. This program was also adopted in Korean Air in 1984. Since then, the mileage programs have grown enormously. As of June 2009, the total member of two national airlines in Korea had been over thirty million. However, accumulated miles could be burden of airlines, because the korean corporations should record the annual financial report the accumulate mileage on a liability account by 'the international financial report standards(IFRS)' next year. The korean airlines need to minimize the accumulated miles, so that for instance Korean Airlines SKYPASS-miles expire 5 years after being earned. It means that miles earned on or after July 2008 will expire after five years if unredeemed. Thus, this paper attempt to analyze the unfairness of the mileage rules of korean airlines by examining a specific portion of the conditions relating to consumer protection, because many mileage users has difficulties using mileage programs and complained the amendment of the mileage rules. In conclusion, the contemporary mileage rules in Korea are rather unsatisfactory, because airlines is not only recognizing a mileage into a kind of benefit but also denying inheritance of mileage and the legal nature of mileage as a property right. It is necessary to amend relevant mileage rules in view of consumer protection, because air mileage is not simple benefit but a right of mileage user.
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