• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.123-132
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• 2014

Inflation uncertainty is known to have deleterious effects on facilities investment by disturbing the corporate decision on the opportunity cost of investment. In this paper, we test the validity of this hypothesis in Korea by estimating the inflation uncertainty with both a time-varing parameter model with GARCH disturbances and the relative price volatility and then, estimate the facilities investment equation which includes those uncertainty indicators. The uncertainty indexes estimated by the above-mentioned methods continue to fluctuate even after the inflation rate has dropped dramatically reflecting the structural changes of Korea's economy since the financial crisis in 1997. As a result of estimation of the investment equation by both OLS and GMM, we find the inflation uncertainty has a negative effect on facilities investment with a statistical significance. Moreover, by means of Markov-switching regression model utilized to verify the non-linearity of this relationship, we draw a conclusion that this negative effect of inflation uncertainty heightens asymmetrically during the downturn periods of business cycle.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.156-165
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• 2007

The concepts of static seat allocation model has been used widely in the air transportation industry, and proven as a good concepts for managing perishable assets. The paper analyzed, in realistic environment, the volume of Accept Demand and Reject Demand through several times' simulation experiments at each fare level by using C-Program analyzing process applied to upward and downward models of demand, to analyze the change of fare level when upward and downward shifts of fare levels' demand happen at once. As a consequence, I concluded that the revenue of the case to consider the both shifts of demand at each fare level is bigger than that of the case to consider the single shift of demand at each fare level, except the case to downsize the seat allotment at very low price when supply is bigger than demand, with developing a general model concerned with plural fare levels.

• Health Policy and Management
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• v.18 no.4
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• pp.85-110
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• 2008

In this study, we explore the long-term demand forecasting of high-price medical equipments based on logistic and Bass diffusion model. We analyze the specific pattern of each equipment's diffusion curve by interpreting the parameter estimates of Bass diffusion model. Our findings are as follows. First, ultrasonic imaging system, CT are in the stage of maturity and so, the future demands of them are not too large. Second, medical image processing unit is between growth stage and maturity stage and so, the demand is expected to increase considerably for two or three years. Third, MRI is in the stage of take-off and Mammmography X-ray system is in the stage of maturity but, estimates of the potential number of adopters based on logistic model is considerably different to that based on Bass diffusion model. It means that additional data for these two equipments should be collected and analyzed to obtain the reliable estimates of their demands. Fourth, medical image processing unit have the largest q value. It means that the word-of-mouth effect is important in the diffusion of this equipment. Fifth, for MRI and Ultrasonic system, q/p values have the relatively large value. It means that collective power has an important role in adopting these two equipments.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.842-854
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• 2001

Today\`s first generation shopping agent is limited to comparing merchant offerings usually on price instead of their full range of attributes. Even in the full range comparison, there is not a good model which considers the overall features in the negotiation process. Therefore, the negotiation model needs to be extended to include negotiations over the more attributes. In this paper, we propose a negotiation model in the agent-mediated electronic commerce to negotiate over prices, product features, warranties and service policies based on utility theory and simple heuristics. We will describe a prototype agent-mediated electronic commerce framework called Pmart. This framework provides the software reuse and the extensibility based on the object-oriented technology. It is implemented on Windows-based platforms using Java and CORBA for the network transparency and platform independence.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• The Journal of Fisheries Business Administration
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• v.5 no.1
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• pp.9-42
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• 1974

Korea is a peninsular country surrounded by seas on three sides, and the fishing industry has carried out the service of suppling to the people with important anima protein. The distribution of fishery products has very complicated structures, because the production is in charge of small producers scattering along the coast all over the country, while consumpstion is made by separate homes in areas away from producing district. The relation between these two factors the structures make very complicated. The most typical and special structures of fishery distridution are distinguished in two, that is, one is landing market, the other is inland market. Landing markets have been monopolized by fishermen's cooperatives, providing with landing facilities and building sites. Fish markets played not only an important role in the landing, but distribution and price determination of catches by auction or tender. Inland markets are two types of wholesale market in consuming center, one is the terminal market for urban consumers, the other type is the local market for rural consumers. Fundamental functions of landing markets are gathering, assessment, and distribution functions. Gathering function is in charge of wholesaler in fishery cooperative. Gathering amounts are equal to gathering capacity of wholesaler and transact ability of licensed dealers as shown below model. Gathering amount=f.gathering capacity(=pre price.landing facility.account of wholesaler.distance of fishing ground.conveniency purchasing.home port)=fㆍ transact ability of licensed dealers≒f.population or port, and table 1 indicates these relationship. Assessment and distribution functions are in charge of licensed dealers in consumption side. Assessment function should bring the value in production activity through the auction between the cooperative seller and the licensed dealer as buyer. For fair trade transaction in auction, the free competition is supposed to be a prerequisite among the licensed dealers. The ideal condition for free competition is sameness in the scale of buying amount by licensed delaers, but it is almost impossible to attain its goal in actual marketing.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.311-321
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• 2012

This study derived from 5 variables(information, product diversity, communication possibility, responsiveness, price) of service quality on social commerce from literature studies and set up the research model and hypotheses. The 167 questionnaires are used in this analysis. The results were as follows: first, all the variables had positive influences upon satisfaction except responsiveness. Second, all the variables had positive influences upon repurchase intention except price. Third, the satisfaction of social commerce had a positive influence upon repurchase intention. This study suggested the strategic implications to induce customers satisfaction and repurchase intention after analyzing critical factors about service quality of social commerce.

• Journal of Environmental Policy
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• v.9 no.4
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• pp.53-76
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• 2010

This paper attempts to estimate and compare environmental Kuznets curves (EKC) for$CO_2$ emissions of five regions constituting South Korea. For this, panel data of $CO_2$ emission for these regions are constucted for the period 1990 - 2007. Close inter-dependency among these five regions is considered by using a seemingly unrelated regression (SUR) model. In addition to real per-capita income, price index of energy sources and population dens ity are included as control variables. Results of estimates show the robust existence of EKC's in all these regions. EKC turning points of five regions range between 13.7 and 21.6 million Korean Won, showing a large variation. This difference among regions should be conisidered for the effective implementation of policies targeting the reduction of $CO_2$ emmission. In addition, the increase of energy price is found help reduce the $CO_2$ emmision while the rise of population density seems to lead to the increase of $CO_2$ emission.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.5
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• pp.469-477
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• 2011

Nowadays, environmentally friendly technology is attracting considerable attention because of environmental pollution and the increasing price of raw materials. Korea has a high level of dependence on exports, and therefore it has stressed the development of environmentally friendly technologies. Bicycle manufacturing industry has a bright future because bicycles do not use fossil fuels, and cycling is good for one's health. We develop a management system for the effective development of next-generation environmentally friendly technology for bicycles. The goal is to promote the bicycle industry in Korea while keeping the product in the low to medium price range.

• Health Policy and Management
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• v.24 no.4
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• pp.342-348
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• 2014

Background: Due to lack of regular and systematic evaluation tool, Korea's tobacco control policy has not been examined its overall process of implementation including efficiency and adequacy of the policies. This study developed policy monitoring and evaluation model to assess policy implementation and effectiveness of tobacco control in Korea. Methods: Based on World Health Organization operational manual for assessment, MPOWER (monitor tobacco use and prevention policies, protect from tobacco smoke, offer help to quit tobacco use, warn about the dangers of tobacco, enforce bans on tobacco advertising promotion and sponsorship, and raise taxes on tobacco) related policies were reviewed by rating policy efforts, programme management, people (human resources and their development), provision of organization, provision of fund and partnerships (range, 0 to 5). Results: As a result of the experts' assessment, overall Korean tobacco control policies scored 2.61 points, which is poor. In relation to each 'MPOWER' policies, 'W' scored the highest points (2.93), followed by 'O' (2.91), 'M' (2.87), 'P' (2.86), and 'E' (2.23). 'R' scored the lowest points of 1.87, meaning government efforts in tobacco price policy is insufficient. Conclusion: This study concludes that Korean tobacco control policy should strengthen tax and price measures, while programme infrastructure, people, and funds for policy enforcement should be secured. Furthermore, rather than focusing on one specific measure, a balanced approach reflecting various aspects of tobacco controls should be considered in order to decrease smoking rates and prevent smoking initiation.