• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.6
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• pp.183-198
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• 2014

This study analyzed the effect of NPD(New Product Development) strategy and standardized NPD activity on NPD performance in KODAK companies. As a result of this study, companies with a specific NPD strategy that can lead and integrate NPD programs were 48.5% and companies without NPD strategy were 51.5% among KOSDAQ companies, which showed that companies without NPD programs were relatively higher than companies with NPD programs. According to result of NPD performance, success rate of new product showed 51.2% and success rate of new product revenue showed 44.87%, but respondents who evaluated NPD performance as "very successful" and "successful" were 53% based on the study of 77 various industries by Kuczmarski & Associates in America in 1993, and the companies in this study showed relatively below-average marks to the result of the study examined by USA PDMA in 1995 as compared to 59% of NPD success rate according to the 2nd study of best practice in 1995 by USA PDMA(Product Development & Management Association). As a result of testing the difference between NPD performances depending on whether company has NPD strategy or not, it showed a significant difference in success rate of NPD depending on NPD strategy and had a higher success rate of NPD as company has NPD strategy. Although NPD activity does not provide with documented process, companies which follow clearly recognized procedure until individual business for product development is completed were 39.6%, indicating that KOSDAQ companies still have fewer standardized NPD procedure than USA companies with 76% as compared to the result of 1990 PDMA in America. As a result of ANOVA test, NPD success rate showed the difference depending on the presence of officially documented process. As a result of Scheffe and Bonferroni test as post hoc test, companies with officially documented process, carrying out a series of business in a given section showed a higher NPD success rate by 18.385 at the 5% significance level than companies with individual business procedure without officially documented process. The difference of this research from the previous studies is that the findings of PDMA in America throughout the United States were applied to the domestic KOSDAQ companies. In addition, the existing studies related to NPD in Korea were conducted for some limited industries in the past, but this study was applied to various industries of KOSDAQ companies. The implications of this study suggest that it is necessary for KOSDAQ Industry Association or other related governmental departments to educate and guide the standardized process about NPD for increasing survival rate and reinforcing competitiveness of the companies.

• Journal of Korean Society of Transportation
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• v.35 no.4
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• pp.360-373
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• 2017

The BTO-a projects is the types, which has a demand risk among the type of PPP projects in Korea. When demand risk is realized, private investor encounters financial difficulties due to lower revenue than its expectation and the government may also have a problem in stable infrastructure operation. In this regards, the government has applied various risk sharing policies in response to demand risk. However, the amount of government's risk sharing is the government's contingent liabilities as a result of demand uncertainty, and it fails to be quantified by the conventional NPV method of expressing in the text of the concession agreement. The purpose of this study is to estimate the value of investment risk sharing by the government considering the demand risk in the profit sharing system (BTO-a) introduced in 2015 as one of the demand risk sharing policy. The investment risk sharing will take the form of options in finance. Private investors have the right to claim subsidies from the government when their revenue declines, while the government has the obligation to pay subsidies under certain conditions. In this study, we have established a methodology for estimating the value of investment risk sharing by using the Black - Scholes option pricing model and examined the appropriateness of the results through case studies. As a result of the analysis, the value of investment risk sharing is estimated to be 12 billion won, which is about 4% of the investment cost of the private investment. In other words, it can be seen that the government will invest 12 billion won in financial support by sharing the investment risk. The option value when assuming the traffic volume risk as a random variable from the case studies is derived as an average of 12.2 billion won and a standard deviation of 3.67 billion won. As a result of the cumulative distribution, the option value of the 90% probability interval will be determined within the range of 6.9 to 18.8 billion won. The method proposed in this study is expected to help government and private investors understand the better risk analysis and economic value of better for investment risk sharing under the uncertainty of future demand.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.4
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• pp.207-215
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• 2019

This study was conducted to establish spring sowing techniques in preparation for the impacts of climate change on sowing time and wintering rates of winter forage crops such as barley, oat and IRG. Oat showed the highest yield in 2017 which had relatively dry climate condition. And when sowing in late Febrnary 2017 yielding 9,408kg/ha were obtained, yielding 4,011kg/ha more than IRG's sown in the same period. In 2018 which had relatively wet climate condition, four barley species decreased in the production from the previous year. Oat also had decreased by 70% from 9,408kg/ha to 2,851kg/ha. On the other hand, IRG maintained the production in the mid-5,000kg/ha range. It was also found that IRG had the least variability due to external influences regardless of seeding period for 2 years. Mixed sowing with IRG and oat in 50:50 ratio was the highest dry matter, 6,584kg/ha, and IRG was 18.5% and Oat was 2.3 times higher than single planting.

• Journal of The Korean Society of Grassland and Forage Science
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• v.31 no.2
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• pp.151-158
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• 2011

This study was carried out in 2010 to investigate the utilization and nutritive value of native grasses, such as Phragmites communis and Miscanthus sinensis which might reduce the cost of feeding domestic cattle. The regions within the Civilian Control Line in Paju and Sihwa region in Ansan were surveyed. In Paju, the yearly silage production was 900 MT harvested from 90 ha (10 MT/ha). About 30~50% of these were sold out at the marketing price of 52,000~55,000 Won per roll (130~137.5 Won/kg). Regrown Miscanthus sinensis of 70 cm in length contained 9.6% of crude protein (CP), 82.4 of relative feed value (RFV), and 67.7% of in vitro dry matter digestibility (IVDMD). Regrown Phragmites communis of 70 cm in length contained 13.8% of CP, 84.3 of RFV, and 67.9% of IVDMD. As harvesting was delayed, the quality was decreased dramatically. In Ansan region, Phragmites communis plantation covers 100 ha. The silage production was 550 MT from the area of 50 ha (11 MT/ha) in 2009. And the marketing price was 50,000 Won per roll. But in 2010 only a small amount of grasses could have been baled due to frequent and much rainfall from spring to summer season. However, the good forage quality was observed from regrown Phragmites communis of 80 cm in length, 12.9% CP, 99.8 RFV and 66.6% IVDMD, while that of late matured grasses was very low, 2.2% CP, 52.9 RFV and 36.4% IVDMD, greatly lower than forage quality of rice straw. The quality of grasses at bloom stage of 150 cm in length was similar to that of rice straw, showing 4.5% CP, 59.9 RFV and 42.2% IVDMD. In conclusion, the overall quality of most native grasses in this survey were very poor. Therefore, we recommend that Phragmites communis and Miscanthus sinensis should be harvested during June or July to obtain better forage quality which is richer in forage values than rice straw. Production of high quality forage crops was also desirable for self sufficiency of forage.

• Journal of the Korea Institute of Building Construction
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• v.9 no.4
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• pp.119-129
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• 2009

Building construction trends have been changed dramatically in terms of size and mass. With the need to maximize land usage, there has been an increase in the construction of high-rise buildings. This affects not only the entire construction duration and cost, but also subsequent construction activities, such as work to increase underground facilities and in reclamation land area construction. These types of site conditions require soft ground reinforcement and the proper uplift water pressure treatment. In general, two kinds of methods have been used for uplift water pressure treatment systems. However, there have been some problems arising as the result of a lack of research and analysis on underground construction techniques, and a reliance on experiments over actual survey and analysis of site conditions. This paper focused on the problems of conventional selection procedure, by analyzing drawings and proposing a kind of modeling for a reasonable procedure. The results were applied to OO project as a sample construction case to be verified in this research. The initial plan in the case project was the Rock Anchor System. However, as there were terrible miscalculations of basic site conditions that had an extraordinary influence on the underground water level, such as the site's proximity to the Han-river, it was necessary to change the plan to include apermanent drainage system. This achieved a direct construction cost reduction \ 406,702,000 and a maximum sayings of 4% of operational cost, based on the 50-year building Life Cycle Cost.

• Korean Journal of Poultry Science
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• v.42 no.3
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• pp.223-230
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• 2015

Eggs are an important source of protein for the human diet. Consumers want fresher, more delicious and more sanitary eggs. In Korea, the Shell Egg Grading system (EGS) was employed in 2001. The portion of graded shell eggs has increased every year, but graded shell eggs account for only 6% of all eggs. The EGS should satisfy producers, distributors and consumers. However, the EGS does not have an official function because of many problems. Consumers cannot select various graded shell eggs in the market, and producers do not receive enough profit even though they produce top-quality graded shell eggs. There are few studies on the EGS, Therefore, this study was performed to improve the EGS. We surveyed the EGS, GP Centers and farmers. Large companies (farmers) are more satisfied than small companies with the EGS. There was a high tendency for the companies (farmers) that are not involved with the EGS to think that graded and ungraded shell eggs are similar, in contrast to the companies (farmers) connected to the EGS. We should have to change the grading system of grade shell eggs, establish of the cold chain system, change of the law for the school meals, minimize payment for the grading shell eggs for developing EGS. Based on this study, the egg industry can benefit through the improvement of the EGS.

• The Korean Journal of Financial Management
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• v.23 no.2
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• pp.109-141
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• 2006

The central factor in the pecking order theory of financial structure is the asymmetric distribution of information between managers and less-informed outside investors. Myers and Majluf (1984) show that this asymmetry leads managers to prefer internal funds to external funds. Funds are raised through equity issues only after the capacity to issue debt has been exhausted. In contrast, according to static tradeoff theory, an optimum financial structure exists by the tradeoff between tax saving by debt and bankruptcy costs. This study examines the recent changes of Korean firms' financial structure and financing behavior and the determinants of financial structure. The sample of firms comes from the period of $1996{\sim}2004$, and the number of firms is 32,003. The major findings are as follows. First, in contrast with previous studies using US firms as sample, Korean firms have been using debt financing as their major financing instrument. Especially, the firms in the fund deficit situation relies much more on $long{\sim}term$ and $short{\sim}term$ debts rather than on equity issues. Second, as is the case with previous studies using US firms sample indicates, the financing deficit variable can not explain perfectly the net debt issue. However, compared with net equity issue variable, net debt issue variable is more closely related to the financing deficit variable. Third, when financing deficit variable is added to the current list of explanatory variables of financial structure determinants model, it has a significant and positive explanatory power. In addition, the coefficients of determinants are much improved. Thus, it is concluded that although pecking order theory is not perfect, it appears to be more useful compared to static tradeoff theory, at least in explaining the recent financing behavior of Korean manufacturing firms.

• Journal of Climate Change Research
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• v.2 no.4
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• pp.283-295
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• 2011

Many actions against climate change have been taken to reduce greenhouse gases (GHGs) emissions at home and abroad. As of 2007, the GHGs emitted from buildings accounted for about 23 % of Korea's total GHGs emission, which is the second largest GHG reduction potential following industry. In this study, we introduced Carbon Zero Building (CZB), which was constructed by the National Institute of Environmental Research to cut down GHGs from buildings in Korea, and evaluated the main applied technologies, the amount of energy load and reduced energy, and economic values for CZB to provide data that could be a basis in the future construction of this kind of carbon-neutral buildings. A total of 66 technologies were applied for this building in order to achieve carbon zero emissions. Applied technologies include 30 energy consumption reduction technologies, 18 energy efficiency technologies, and 5 eco-friendly technologies. Out of total annual energy load ($123.8kWh/m^2$), about 40% of energy load ($49kWh/m^2$) was reduced by using passive technologies such as super insulation and use of high efficiency equipments and the other 60% ($74.8kWh/m^2$) was reduced by using active technologies such as solar voltaic, solar thermal, and geothermal energy. The construction cost of CZB was 1.4 times higher than ordinary buildings. However, if active technologies are excluded, the construction cost is similar to that of ordinary buildings. It was estimated that we could save annually about 102 million won directly from energy saving and about 2.2 million won indirectly from additional saving by the reduction in GHGs and atmospheric pollutants. In terms of carbon, we could reduce 100 ton of $CO_2$ emissions per year. In our Life Cycle Cost (LCC) analysis, the Break Even Point (BEP) for the additional construction cost was estimated to be around 20.6 years.

• Journal of Korea Foundry Society
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• v.41 no.2
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• pp.144-152
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• 2021

Based on the analysis of the current state of the world's foundry industry, we looked at the international competitiveness of Korea's foundry industry for the past 20 years. Korea's total foundry production is 2.52 million tons, and the production per company (so-called productivity) is 2,831 tons, which is the eighth largest in the world and down one position for the case of total foundry production, while productivity remains its position compared to three years ago. Korea is the only one of the top 10 foundry to see a decline in production. Similar to the global situation, Korean products consist of 38% of grey csat iron, 31% of ductile cast iron, 15% of aluminum, and 9% of cast steel. In order to obtain statistics on Korea's foundry industry, the survey conducted a service project for approximately nine months from April 2020. Various statistical surveys and sample in-depth surveys by the Korean standard industry class were evaluated for various contents of the domestic casting industry. We also looked at the number of companies, the distribution by region, the number of workers and the percentage of foreigners, and the distribution of each job, as well as the R&D investment status according to the size of the enterprise. Together, sales, exports, sales and various profit ratios were analyzed to measure the earning power of foundry industry. In addition, the classification by grouping the foundry industry according to the process utilized by focusing on each company, and to determine the sales, exports, and yield status for each process was also investigated on the basis. Based on these data, the domestic foundry industry has presented a variety of offers for the following issues for sustainable growth; global ranking, marginal corporate restructuring, training of domestic technical people, differentiated support policies by company size and process.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.