Small and medium-sized company workers are ill-prepared for retirement due to low wages and poor working conditions, as result, are likely to get into poverty in retirement. The purpose of this study is to conduct a case study on the current status of financial and non-financial retirement preparation of the small and medium-sized company workers. The main findings are as follows. First, the small and medium-sized company workers show the anxiety about retirement. Many pre-retirees worry that their retirement savings may not generate enough income in retirement, and the level of benefits paid in public pension is inadequate. Second, they are preparing for retirement in the areas of finance, health, working after retirement and social activity. Third, they are realistic and practical in retirement decisions makings. they are considering household budget downsizing, cutting education costs, the low-waged job choice and cash flow preference in retirement. The safety and reality in preparation for retirement are top considerations. In conclusion, this case study shows that pre-retirees of small and medium-sized companies are seeking diverse retirement solutions. We need to design integrated and practical retirement planning programs to support their specific retirement needs.
Shipping companies earn profits through cargo transportation, and therefore, investment decisions to purchase ships are more important than anything else. Nevertheless, the cash flow discount method was mainly used in the economic analysis method, which assumes that all situations are static. This study shows that the real option model is useful in the economic analysis of ship investment. This economic analysis took into account the irreversibility of investment and uncertainty of benefits. In particular, this study used a binary option price determination model among real options. In addition, the simulation was conducted using actual investment data of A shipping company. As a result of the analysis, the investment value of used ships according to the net present value method was analyzed as negative (-), but the investment value in the real option model reflecting the flexibility of decision-making was evaluated as having positive (+) economic feasibility. It was analyzed that economic feasibility is affected by profit volatility and discount rate. Therefore, this study is expected to help shipping companies make more flexible decisions by using the real option model along with the existing net present value method when making ship investment decisions.
While the Forward Freight Agreement (FFA) has emerged as an effective hedging tool since early 1990, the basis risk and cash flow distortions have been addressed as obstacles to the active use of FFAs. This research analyses the basis risk of FFAs and provides a feasible suggestion to reduce it. Basis risk is divided into timing basis, route basis, size basis, and low liquidity basis. The timing basis is defined as the difference between the physical hire, fixed on the specific contract date and the FFA settlement price, calculated by averaging spot rates for a certain period. Timing basis is considered the worst in eroding the effectiveness of FFAs. This paper suggests a change of hire payment criterion from contract date to 15-day moving average, as a means of mitigating the basis risk, and analyzed the effectiveness through historical simulation. The result revealed that the change is effective in mitigating the timing basis. This study delivers a meaningful implication to shipping practice in that the change of hire payment criterion mitigates the basis risk and eventually activates the use of FFAs in the future.
In the context of today's business environment, not only is the nation or company's credit rating considered very important in our recent society, but it is also becoming important in international transactions. Likewise, at this point of time when the importance and reliability of credit evaluation are becoming important at home and abroad, this study analyzes financial ratios related to corporate profitability, safety, activity, financial growth, and profit growth to study the impact of financial indicators on enterprise value and corporate taxes on credit evaluation. To proceed with this, the financial ratio of 465 companies of KOSPI securities listed in 2017 was calculated and the impact of enterprise value and corporate taxes on credit evaluation was analyzed. Especially, this further study tried to derive a reliable and consistent conclusion by analyzing the financial data of KOSPI securities listed companies for eight years from 2011, which is the first year of K-IFRS introduction, to 2018. Research has shown that the significance levels among variables that show the profitability, safety, activity, financial growth, and profit growth of each financial ratio were significant at the 99% level, except for the profit growth. Validation of the research hypothesis found that while the profitability of KOSPI-listed companies significantly affects corporate value and income tax, indicators such as safety ratio and growth ratio do not significantly affect corporate value and income tax. Activity ratio resulted in significant effects on the value of enterprise value but not significant impacts on income taxes. In addition, it was found that the enterprise value has a significant effect on the company's credit and corporate income taxes, and that corporate income taxes also have a significant effect on the corporate credit evaluation, and this also shows that there is a mediating function of corporate tax. And as a result of further study, when looking at the financial ratio for eight years from 2011 to 2018, it was found that two variables, KARA and LTAX, are significant at a 1% significant level to KISC, whereas LEVE variables is not significant to KISC. The limitation of this study is that credit rating score and financial score cannot be said to be reliable indicators that investors in the capital market can normally obtain, compared to ranking criteria for corporate bonds or corporate bills directly related to capital procurement costs of enterprise. Above all, it is necessary to develop credit rating score and financial score reflecting financial indicators such as business cash flow or net assets market value and non-financial indicators such as industry growth potential or production efficiency.
Journal of the Korean Society for Library and Information Science
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v.4
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pp.43-71
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1975
Operations research has developed rapidly since its origins in World War II. Practitioners of O. R. have contributed to almost every aspect of government and business. More recently, a number of operations researchers have turned their attention to library and information systems, and the author believes that significant research has resulted. It is the purpose of this essay to introduce the library audience to some of these accomplishments, to present some of the author's hypotheses on the subject of library management to which he belives O. R. has great potential, and to suggest some future research directions. Some problem areas in librianship where O. R. may play a part have been discussed and are summarized below. (1) Library location. It is usually necessary to make balance between accessibility and cost In location problems. Many mathematical methods are available for identifying the optimal locations once the balance between these two criteria has been decided. The major difficulties lie in relating cost to size and in taking future change into account when discriminating possible solutions. (2) Planning new facilities. Standard approaches to using mathematical models for simple investment decisions are well established. If the problem is one of choosing the most economical way of achieving a certain objective, one may compare th althenatives by using one of the discounted cash flow techniques. In other situations it may be necessary to use of cost-benefit approach. (3) Allocating library resources. In order to allocate the resources to best advantage the librarian needs to know how the effectiveness of the services he offers depends on the way he puts his resources. The O. R. approach to the problems is to construct a model representing effectiveness as a mathematical function of levels of different inputs(e.g., numbers of people in different jobs, acquisitions of different types, physical resources). (4) Long term planning. Resource allocation problems are generally concerned with up to one and a half years ahead. The longer term certainly offers both greater freedom of action and greater uncertainty. Thus it is difficult to generalize about long term planning problems. In other fields, however, O. R. has made a significant contribution to long range planning and it is likely to have one to make in librarianship as well. (5) Public relations. It is generally accepted that actual and potential users are too ignorant both of the range of library services provided and of how to make use of them. How should services be brought to the attention of potential users? The answer seems to lie in obtaining empirical evidence by controlled experiments in which a group of libraries participated. (6) Acquisition policy. In comparing alternative policies for acquisition of materials one needs to know the implications of each service which depends on the stock. Second is the relative importance to be ascribed to each service for each class of user. By reducing the level of the first, formal models will allow the librarian to concentrate his attention upon the value judgements which will be necessary for the second. (7) Loan policy. The approach to choosing between loan policies is much the same as the previous approach. (8) Manpower planning. For large library systems one should consider constructing models which will permit the skills necessary in the future with predictions of the skills that will be available, so as to allow informed decisions. (9) Management information system for libraries. A great deal of data can be available in libraries as a by-product of all recording activities. It is particularly tempting when procedures are computerized to make summary statistics available as a management information system. The values of information to particular decisions that may have to be taken future is best assessed in terms of a model of the relevant problem. (10) Management gaming. One of the most common uses of a management game is as a means of developing staff's to take decisions. The value of such exercises depends upon the validity of the computerized model. If the model were sufficiently simple to take the form of a mathematical equation, decision-makers would probably able to learn adequately from a graph. More complex situations require simulation models. (11) Diagnostics tools. Libraries are sufficiently complex systems that it would be useful to have available simple means of telling whether performance could be regarded as satisfactory which, if it could not, would also provide pointers to what was wrong. (12) Data banks. It would appear to be worth considering establishing a bank for certain types of data. It certain items on questionnaires were to take a standard form, a greater pool of data would de available for various analysis. (13) Effectiveness measures. The meaning of a library performance measure is not readily interpreted. Each measure must itself be assessed in relation to the corresponding measures for earlier periods of time and a standard measure that may be a corresponding measure in another library, the 'norm', the 'best practice', or user expectations.
Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.
Since 2011, DCF(Discounted Cash Flow) method has been used initiatively for valuating R&D technology assets in the agricultural food industry and recently technology valuation based on royalties comparison among technology transfer transactions has been also carried out in parallel when evaluating the technology assets such as new seed development technologies. Since the DCF method which has been known until now has many input variables to be estimated, sophisticated estimation has been demanded at the time of technology valuation. In addition, considering more similar trading cases when applying sales transaction comparison or industry norm method based on information of technology transfer royalty, it is an important issue that should be taken into account in the same way in the Agri-Food industry. The main input variables used for technology valuation in the Agri-Food industry are life cycle of technology asset, the financial information related to the Agri-Food industry, discount rate, and technology contribution rate. The latest infrastructure building and data updating related to technology valuation has been carried out on a regular basis in the evaluation organization of the Agri-Food segment. This study verifies the key variables that give the most important impact on the results for the existing technology valuation in the Agri-Food industry and clarifies the difference between the existing valuation result and the outcome by referring the support information that is derived through the latest input information applied in DCF method. In addition, while presenting the scheme to complement fragment information which the latest input data just influence result of technology valuation, we tried to perform comparative analysis between the existing valuation results and the evaluated outcome after the latest of reference data for making a decision the input values to be estimated in DCF. To perform these analyzes, it was first selected the representative cases evaluated past in the Agri-Food industry, applied a sensitivity analysis for input variables based on these selected cases, and then executed a simulation analysis utilizing the key input variables derived from sensitivity analysis. The results of this study is to provide the information which there are the need for modernization of the data related to the input variables that are utilized during valuating technology assets in the Agri-Food sector and for building the infrastructure of the key input variables in DCF. Therefore it is expected to provide more fruitful information about the results of valuation.
This study examines the negative relationship between accounting conservatism and excess executive compensation and examines whether their relationship increases as managerial incentive compensation intensity increases. For this purpose, a total of 2,755 company-years were selected for the analysis of the companies listed on the Korea Stock Exchange from December 2012 to 2016 as the final sample. The results of this study are as follows. First, there is a statistically significant negative relationship between accounting conservatism and manager overpayment. This implies that managers' incentives to distort future cash flow estimates by over booking assets or accounting profits in order to maximize their compensation when manager compensation is linked to firm performance. In this sense, accounting conservatism can reduce opportunistic behavior by restricting managerial accounting choices, which can be interpreted as a reduction in overpayment to managers. Second, we found that the relationship between accounting conservatism and excess executive compensation increases with the incentive compensation for accounting performance. The higher the managerial incentive compensation intensity of accounting performance is, the more likely it is that the manager has the incentive to make earnings adjustments. Therefore, the high level of incentive compensation for accounting performance means that the ex post settling up problem due to over-compensation can become serious. In this case, the higher the managerial incentive compensation intensity for accounting performance, the greater the role and utility of conservatism in manager compensation contracts. This study is based on the fact that it presents empirical evidence on the usefulness of accounting conservatism in managerial compensation contracts theoretically presented by Watts (2003) and the additional basis that conservatism can be used as a useful tool for investment decision.
An economic study of vegetation control to increase production of Songyi (Korean name far pine mushroom, matsutake, Tracholoma matsutake (S. Ito & Imai) Sing.) in red pine (Panes densiflora) stands in Korea was undertaken. In Korea, Songyi grows only in red pine stands. Harvest of this mushroom provides a significant income source to rural people in Korea yielding exports of US$20 million to US$80 million per year. However, hypogeous Songyi colonies and the mushroom production are declining, partly because shade tolerant species are succeeding the shade intolerant red pine. Past research says that it is possible to deep Songyi production increasing by controlling under-story vegetation. But few people are wilting to invest in the necessary control. Our analysis found that the economics of vegetation control appear to be quite favorable, showing an internal rate of return (IRR) of 20.7 percent in 15 years. However, positive returns do not occur for at least eight years and even then, the returns may not appear to the landowner to be a result of vegetation control efforts only because the mushroom production has been greatly variable depending on weather conditions. In a sensitivity analysis, it was found that the number of circular mushroom colonies was critically important for the cash flow. Results of this analysis are also sensitive to assumptions about annual growth length(0.16m radial growth=1.0m/circular length growth) of Songyi colony. However, the primary goal of vegetation control should be to keep the young colonies growing. Further research in the behavior of hypogeous Songyi colonies after vegetation control would help to improve our confidence in the results.
Journal of the Korea Academia-Industrial cooperation Society
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v.8
no.6
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pp.1634-1647
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2007
"To invest or not to invest?" Most business leaders are frequently faced with this question on new and ongoing projects. The challenge lies in deciding what projects to choose, expand, contract, defer, or abandon. The project valuation tools used in this process are vital to making the right decisions. Traditional tools such as discounted cash flow (DCF)/net present value (NPV) assume a "fixed" path ahead, but real world projects face uncertainties, forcing us to change the path often. Comparing to other traditional valuation methods, the real options approach captures the flexibility inherent to investment decisions. The use of real options has gained wide acceptance among practitioners in a number of several industries during the last few decades. Even though the options are present in all types of business decisions, it is still not considered as a proper method of valuation in some industries. Mining has been comparably slow to adopt new valuation techniques over the years. The reason fur this is not entirely clear. One possible reason is the level and types of risks in mining. Not only are these risks high, but they are also more numerous and involve natural risks compared with other industries. That is why the purpose of this study is to deal with a more practical approach to project valuation, known as real options analysis in mining industry. This paper provides a case study approach to the copper mining industry using a real options analysis. It shows how companies can minimize investment risks, exercise flexibility in decision making and maximize returns.
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