• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.6 no.3
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• pp.179-187
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• 2008

After Canada has struggled with a radioactive waste problem over for 20 years, the Canadian government finally found out that its approach by far has been lack of social acceptance, and needed a program such as public and stakeholder engagement (PSE) which involves the public in decision-making process. Therefore, the government made a special law, called Nuclear Fuel Waste Act (NFWA), to search for an appropriate nuclear waste management approach. NFWA laid out three possible approaches which were already prepared in advance by a nuclear expert group, and required Nuclear Waste Management Organization (NWMO) to be established to report a recommendation as to which of the proposed approaches should be adopted. However, NFWA allowed NWMO to consider additional management approach if the other three were not acceptable enough. Thus, NWMO studied and created a fourth management approach after it had undertaken an comparison of the benefits, risks and costs of each management approach: Adaptive Phased Management. This approach was intended to enable the implementers to accept any technological advancement or changes even in the middle of the implementation of the plan. The Canadian PSE case well shows that technological R&D are deeply connected with social acceptance. Even though the developments and technological advancement are carried out by the scientists and experts, but it is important to collect the public opinion by involving them to the decision-making process in order to achieve objective validity on the R&D programs. Moreover, in an effort to ensure the principles such as fairness, public health and safety, security, and adoptability, NWMO tried to make those abstract ideas more specific and help the public understand the meaning of each concept more in detail. Also, they utilized a variety of communication methods from face-to-face meeting to e-dialogue to encourage people to participate in the program as much as possible. Given the fact that Korea has been also having a hard time in dealing with spent nuclear fuel management, all of these efforts that Canada has made with a PSE program would give good lessons and implications to the Korean case. In conclusion, as a deliberative participation program, PSE could be a possible breakthrough approach for the Korean spent nuclear fuel management.

• The Korean Society of Law and Medicine
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• v.18 no.1
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• pp.297-341
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• 2017

We searched out court rulings on medical affairs through court library search sites and specialized articles on medically relevant judgments sentenced in 2016. And we selected and analyzed the judgements of the court we considered important as follows. In relation to the medical civil judgements, (1) In the case of applying surgery for female infertility during cesarean section operation but it has not been done, we expressed the regret for the lack of judgment in the process of entering the medical contract, introducing the rights infringed and the scope of compensation, (2) We pointed out that the ruling on the medical malpractice estimation goes out of limit of negligence estimation doctrine, and that the court asked very high degree duty of the traditional Korean medicine doctors to cooperate with Western medicine doctors. (3) In the case of admitting hospital's 100% responsibility, we pointed out the court overlooked the uncertainty and good intention of the medical practice. (4) Additionally, We introduced the cases admitted the hospital's responsibility in the accident related to the psychiatric patients in closed ward. Relating to a medical criminal ruling, we analyzed the supreme court decision about whether the dentist's Botox injection on the patient's face is a medical practice within the scope of the license from the viewpoint whether it is within the possible range of the word. And, concerning decisions on healthcare administration, (1) we analyzed the case about when medical personnel operate multiple medical institutions, whether it is possible to get back medical care costs under the National Health Insurance Law, (2) We commented on the ruling regarding explanation obligation in terms of object, degree, subject of explanation as a prerequisite for permissible arbitrary uninsured benefits. Finally, we reviewed the decision of the Constitutional Court about the Article 24 of the Mental Health Law, which it had allowed for a mental patient to be hospitalized forcibly by the consent of two guardians and a diagnosis of a psychiatrist. Also we indicated the problems of the revised Mental Health Law.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.31-57
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• 1991

Korean firms of all sizes, from virtually every industry, have used and are using the term "excessive competition" to describe the state of their industry and to call for government interventions. Moreover, the Korean government has frequently responded to such calls in various ways favorable to the firms, such as controlling entry, curbing capacity investments, or allowing collusion. Despite such interventions' impact on the overall efficiency on the Korean economy as well as on the wealth distribution among diverse groups of economic agents, the term "excessive competition", the basis for the interventions, has so far escaped rigorous scrutiny. The objective of this paper is to clarify the notion of "excessive competition" and "over-investment" which usually accompanies "excessive competition", and to examine the circumstances under which they might occur. We first survey the cases where the terms are most widely used and proceed to examine those cases to determine if competition is indeed excessive, and if so, what causes "excessive competition". Our main concern deals with the case in which the firms must make investment decisions that involve large sunk costs while facing uncertain demand. In order to analyze this case, we developed a two period model of capacity precommitment and the ensuing competition. In the first period, oligopolistic firms make capacity investments that are irreversible. Demand is uncertain in period 1 and only the distribution is known. Thus, firms must make investment decisions under uncertainty. In the second period, demand is realized, and the firms compete with quantity under realized demand and capacity constraints. In the above setting, we find that there is "no over-investment," en ante, and there is "no excessive competition," ex post. As measured by the information available in period 1, expected return from investment of a firm is non-negative, overall industry capacity does not exceed the socially optimal level, and competition in the second period yields an outcome that gives each operating firm a non-negative second period profit. Thus, neither "excessive competition" nor "over-investment" is possible. This result will generally hold true if there is no externality and if the industry is not a natural monopoly. We also extend this result by examining a model in which the government is an active participant in the game with a well defined preference. Analysis of this model shows that over-investment arises if the government cannot credibly precommit itself to non-intervention when ex post idle capacity occurs, due to socio-political reasons. Firms invest in capacities that exceed socially optimal levels in this case because they correctly expect that the government will find it optimal for itself to intervene once over-investment and ensuing financial problems for the firms occur. Such planned over-investment and ensuing government intervention are the generic problems under the current system. These problems are expected to be repeated in many industries in years to come, causing a significant loss of welfare in the long run. As a remedy to this problem, we recommend a non-intervention policy by the government which creates and utilizes uncertainty. Based upon an argument which is essentially the same as that of Kreps and Wilson in the context of a chain-store game, we show that maintaining a consistent non-intervention policy will deter a planned over-investment by firms in the long run. We believe that the results obtained in this paper has a direct bearing on the public policies relating to many industries including the petrochemical industry that is currently in the center of heated debates.

• The Journal of the Korea Contents Association
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• v.16 no.1
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• pp.24-41
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• 2016

Study is about Bit Coin that is electronic cash that is received attention globally in recent. It is increasing domestically that uses bit coin for convenience of micro payment, and also bit coin is possible to exchange each countries' currency. In this point, we searched understanding degree and acceptance of bit coin. Also we applied transformed TAM(Technology Acceptance Model) to search factors that have an effect on consumers' intention to use it. In advance, we analyze features of bit coin, and extract factors through preceding researches for existing electronic cash, because studies for intention to use bit coin are weak in internal and external. First of results is that 'economic efficiency' which is a characteristic variable of bit coin influences 'intention to use,' a dependent variable through 'perceived usefulness,' a parameter. It was investigated that monetary and mental costs that was costed when we use bit coin were less than using other cash. Secondly, 'payment convenience' that is a characteristic variable affects 'intention to use', a dependent variable through 'perceived usefulness,' a parameter. It was measured that problems of inconvenience that include transaction process, cash management time shortage and exchange changes will be solved by using bit coin. Thirdly, 'reliability' that is a perceived risk variable of bit coin has a direct effect on 'intention to use,' a dependent variable. It was investigated that we could achieve purpose of payment because we weren't influenced by breakdown on system by processing distributed database in some computers. Fourthly, 'perceived usefulness,' a parameter of bit coin directly affects 'intention to use,' a dependent variable. Then consumers who want to use bit coin are fascinated bit coin for various usability. Moreover, we want to provide implications to all of finance corporations, companies related electronic cash and bit coin users based on these results.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.57-81
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• 2008

Knowledge is an essential strategic weapon for sustaining competitive advantage and is the key determinant for organizational growth. When knowledge is shared and disseminated throughout the organization, it increases an organization's value by providing the ability to respond to new and unusual situations. The growing importance of knowledge as a critical resource has forced executives to pay attention to their organizational knowledge. Organizations are increasingly undertaking knowledge management initiatives and making significant investments. Knowledge sourcing is considered as the first important step in effective knowledge management. Most firms continue to make an effort to realize the benefits of knowledge management by using various knowledge sources effectively. Appropriate knowledge sourcing strategies enable organizations to create, acquire, and access knowledge in a timely manner by reducing search and transfer costs, which result in better firm performance. In response, the knowledge management literature has devoted substantial attention to the analysis of knowledge sourcing strategies. Many studies have categorized knowledge sourcing strategies into intemal- and external-oriented. Internal-oriented sourcing strategy attempts to increase firm performance by integrating knowledge within the boundary of the firm. On the contrary, external-oriented strategy attempts to bring knowledge in from outside sources via either acquisition or imitation, and then to transfer that knowledge across to the organization. However, the extant literature on knowledge sourcing strategies focuses primarily on large organizations. Although many studies have clearly highlighted major differences between large and small firms and the need to adopt different strategies for different firm sizes, scant attention has been given to analyzing how knowledge sourcing strategies affect firm performance in small firms and what are the differences between small and large firms in the patterns of knowledge sourcing strategies adoption. This study attempts to advance the current literature by examining the impact of knowledge sourcing strategies on small firm performance from a holistic perspective. By drawing on knowledge based theory from organization science and complementarity theory from the economics literature, this paper is motivated by the following questions: (1) what are the adoption patterns of different knowledge sourcing strategies in small firms (i,e., what sourcing strategies should be adopted and which sourcing strategies work well together in small firms)?; and (2) what are the performance implications of these adoption patterns? In order to answer the questions, this study developed three hypotheses. First hypothesis based on knowledge based theory is that internal-oriented knowledge sourcing is positively associated with small firm performance. Second hypothesis developed on the basis of knowledge based theory is that external-oriented knowledge sourcing is positively associated with small firm performance. The third one based on complementarity theory is that pursuing both internal- and external-oriented knowledge sourcing simultaneously is negatively or less positively associated with small firm performance. As a sampling frame, 700 firms were identified from the Annual Corporation Report in Korea. Survey questionnaires were mailed to owners or executives who were most erudite about the firm s knowledge sourcing strategies and performance. A total of 188 companies replied, yielding a response rate of 26.8%. Due to incomplete data, 12 responses were eliminated, leaving 176 responses for the final analysis. Since all independent variables were measured using continuous variables, supermodularity function was used to test the hypotheses based on the cross partial derivative of payoff function. The results indicated no significant impact of internal-oriented sourcing strategies while positive impact of external-oriented sourcing strategy on small firm performance. This intriguing result could be explained on the basis of various resource and capital constraints of small firms. Small firms typically have restricted financial and human resources. They do not have enough assets to always develop knowledge internally. Another possible explanation is competency traps or core rigidities. Building up a knowledge base based on internal knowledge creates core competences, but at the same time, excessive internal focused knowledge exploration leads to behaviors blind to other knowledge. Interestingly, this study found that Internal- and external-oriented knowledge sourcing strategies had a substitutive relationship, which was inconsistent with previous studies that suggested complementary relationship between them. This result might be explained using organizational identification theory. Internal organizational members may perceive external knowledge as a threat, and tend to ignore knowledge from external sources because they prefer to maintain their own knowledge, legitimacy, and homogeneous attitudes. Therefore, integrating knowledge from internal and external sources might not be effective, resulting in failure of improvements of firm performance. Another possible explanation is small firms resource and capital constraints and lack of management expertise and absorptive capacity. Although the integration of different knowledge sources is critical, high levels of knowledge sourcing in many areas are quite expensive and so are often unrealistic for small enterprises. This study provides several implications for research as well as practice. First this study extends the existing knowledge by examining the substitutability (and complementarity) of knowledge sourcing strategies. Most prior studies have tended to investigate the independent effects of these strategies on performance without considering their combined impacts. Furthermore, this study tests complementarity based on the productivity approach that has been considered as a definitive test method for complementarity. Second, this study sheds new light on knowledge management research by identifying the relationship between knowledge sourcing strategies and small firm performance. Most current literature has insisted complementary relationship between knowledge sourcing strategies on the basis of data from large firms. Contrary to the conventional wisdom, this study identifies substitutive relationship between knowledge sourcing strategies using data from small firms. Third, implications for practice highlight that managers of small firms should focus on knowledge sourcing from external-oriented strategies. Moreover, adoption of both sourcing strategies simultaneousiy impedes small firm performance.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.131-145
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• 2010

The framework for making a coordinated decision for large-scale facilities has become an important issue in supply chain(SC) management research. The competitive business environment requires companies to continuously search for the ways to achieve high efficiency and lower operational costs. In the areas of production/distribution planning, many researchers and practitioners have developedand evaluated the deterministic models to coordinate important and interrelated logistic decisions such as capacity management, inventory allocation, and vehicle routing. They initially have investigated the various process of SC separately and later become more interested in such problems encompassing the whole SC system. The accurate quotation of ATP(Available-To-Promise) plays a very important role in enhancing customer satisfaction and fill rate maximization. The complexity for intelligent manufacturing system, which includes all the linkages among procurement, production, and distribution, makes the accurate quotation of ATP be a quite difficult job. In addition to, many researchers assumed ATP model with integer time. However, in industry practices, integer times are very rare and the model developed using integer times is therefore approximating the real system. Various alternative models for an ATP system with time lags have been developed and evaluated. In most cases, these models have assumed that the time lags are integer multiples of a unit time grid. However, integer time lags are very rare in practices, and therefore models developed using integer time lags only approximate real systems. The differences occurring by this approximation frequently result in significant accuracy degradations. To introduce the ATP model with time lags, we first introduce the dynamic production function. Hackman and Leachman's dynamic production function in initiated research directly related to the topic of this paper. They propose a modeling framework for a system with non-integer time lags and show how to apply the framework to a variety of systems including continues time series, manufacturing resource planning and critical path method. Their formulation requires no additional variables or constraints and is capable of representing real world systems more accurately. Previously, to cope with non-integer time lags, they usually model a concerned system either by rounding lags to the nearest integers or by subdividing the time grid to make the lags become integer multiples of the grid. But each approach has a critical weakness: the first approach underestimates, potentially leading to infeasibilities or overestimates lead times, potentially resulting in excessive work-inprocesses. The second approach drastically inflates the problem size. We consider an optimized ATP system with non-integer time lag in supply chain management. We focus on a worldwide headquarter, distribution centers, and manufacturing facilities are globally networked. We develop a mixed integer programming(MIP) model for ATP process, which has the definition of required data flow. The illustrative ATP module shows the proposed system is largely affected inSCM. The system we are concerned is composed of a multiple production facility with multiple products, multiple distribution centers and multiple customers. For the system, we consider an ATP scheduling and capacity allocationproblem. In this study, we proposed the model for the ATP system in SCM using the dynamic production function considering the non-integer time lags. The model is developed under the framework suitable for the non-integer lags and, therefore, is more accurate than the models we usually encounter. We developed intelligent ATP System for this model using genetic algorithm. We focus on a capacitated production planning and capacity allocation problem, develop a mixed integer programming model, and propose an efficient heuristic procedure using an evolutionary system to solve it efficiently. This method makes it possible for the population to reach the approximate solution easily. Moreover, we designed and utilized a representation scheme that allows the proposed models to represent real variables. The proposed regeneration procedures, which evaluate each infeasible chromosome, makes the solutions converge to the optimum quickly.

• Journal of The Korean Society of Grassland and Forage Science
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• v.12 no.3
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• pp.3-12
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• 1992

Forage grasses and legumes ar$\varepsilon$ the mam component of livestock diets in Canada. There are over 30 million ha of grassland in Canada and there is a large, undeveloped land base in fringe areas suitable for forage production. The short growing s season limits the grassland farming to the southern p parts of Canada. The win!er season is long and in most parts of Canada cold temperatures, fr$\varepsilon$ezmg, and thawing, and diseases exert sever$\varepsilon$ stress on overwintering forage plants. The development of persistent cultivars is essential for sustained production particularly in the fringe areas with short growmg s$\varepsilon$ason. The seasonality of dry matter production is a result of high growth rates in early summ$\varepsilon$r and low dry matter accumulation in late summer and fall. Innovative management practIces a and cultivars with improved regrowth capacity are n necessary to overcome such skewed production pattern and to extend effiectlVe grazmg season l Improved pasture production is an important part of reducing costs in livestock operations and remaining competitive. It is suggested that applying available technology would increase pasture productivity and reduce d$\varepsilon$pendence on stored feeds thus improving profitability of small producers in particeular. Reducing nutrient losses during harv$\varepsilon$stmg, s storage, and feeding is essential for improved production efficiency during confinement. The devclopment of low cost and labor saving methods of ensiling is critical for improved efficiency and profitability of forage based enterprises Livestock industries must respond to consumer preferences for low fat and cholesterol foods. Research and development of entire production systems is emphasized for dev$\varepsilon$loping viabl$\varepsilon$ enterprises. It is increasingly difficult to secure resources for r$\varepsilon$search, education, and extension, and alliane$\varepsilon$s and cooperation must expand among organizations with interests in forage based livestock systems.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.