• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.85-97
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• 2010

Internet communities are a typical space for knowledge creation and use on the Internet as people discuss their common interests within the internet communities. When we define 'Knowledge Communities' as internet communities that are related to knowledge creation and use, they are categorized into 4 different types such as 'Search Engine,' 'Open Communities,' 'Specialty Communities,' and 'Activity Communities.' Each type of knowledge community does not remain the same, for example. Rather, it changes with time and is also affected by the external business environment. Therefore, it is critical to develop processes for practical use of such changeable knowledge communities. Yet there is little research regarding a strategic framework for knowledge communities as a source of knowledge creation and use. The purposes of this study are (1) to find factors that can affect knowledge creation and use for each type of knowledge community and (2) to develop a strategic framework for practical use of the knowledge communities. Based on previous research, we found 7 factors that have considerable impacts on knowledge creation and use. They were 'Fitness,' 'Reliability,' 'Systemicity,' 'Richness,' 'Similarity,' 'Feedback,' and 'Understanding.' We created 30 different questions from each type of knowledge community. The questions included common sense, IT, business and hobbies, and were uniformly selected from various knowledge communities. Instead of using survey, we used these questions to ask users of the 4 representative web sites such as Google from Search Engine, NAVER Knowledge iN from Open Communities, SLRClub from Specialty Communities, and Wikipedia from Activity Communities. These 4 representative web sites were selected based on popularity (i.e., the 4 most popular sites in Korea). They were also among the 4 most frequently mentioned sitesin previous research. The answers of the 30 knowledge questions were collected and evaluated by the 11 IT experts who have been working for IT companies more than 3 years. When evaluating, the 11 experts used the above 7 knowledge factors as criteria. Using a stepwise linear regression for the evaluation of the 7 knowledge factors, we found that each factors affects differently knowledge creation and use for each type of knowledge community. The results of the stepwise linear regression analysis showed the relationship between 'Understanding' and other knowledge factors. The relationship was different regarding the type of knowledge community. The results indicated that 'Understanding' was significantly related to 'Reliability' at 'Search Engine type', to 'Fitness' at 'Open Community type', to 'Reliability' and 'Similarity' at 'Specialty Community type', and to 'Richness' and 'Similarity' at 'Activity Community type'. A strategic framework was created from the results of this study and such framework can be useful for knowledge communities that are not stable with time. For the success of knowledge community, the results of this study suggest that it is essential to ensure there are factors that can influence knowledge communities. It is also vital to reinforce each factor has its unique influence on related knowledge community. Thus, these changeable knowledge communities should be transformed into an adequate type with proper business strategies and objectives. They also should be progressed into a type that covers varioustypes of knowledge communities. For example, DCInside started from a small specialty community focusing on digital camera hardware and camerawork and then was transformed to an open community focusing on social issues through well-known photo galleries. NAVER started from a typical search engine and now covers an open community and a special community through additional web services such as NAVER knowledge iN, NAVER Cafe, and NAVER Blog. NAVER is currently competing withan activity community such as Wikipedia through the NAVER encyclopedia that provides similar services with NAVER encyclopedia's users as Wikipedia does. Finally, the results of this study provide meaningfully practical guidance for practitioners in that which type of knowledge community is most appropriate to the fluctuated business environment as knowledge community itself evolves with time.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Food Science and Preservation
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• v.19 no.3
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• pp.376-384
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• 2012

This study was conducted to investigate the food purchasing management of school food services. The subjects consisted of 271 school dietitians in the Daegu and Gyeongbuk area. The percentages of ready-to-use vegetables actually being used were as follows: root of balloon flowers, 88.4%; garlic, 87.8%; blanched bracken, 80.1%; raw lotus root, 65.7%; burdock, 63.5%; small green onion, 63.5%; stem of taro, 57.6%; ginger, 35.1%; radish root, 30.6%; blanched asterscaber, 29.2%; large type welsh onion, 25.8%; carrot, 25.5%; onion, 21.4%; and potato, 8.9%. The percentages of HACCP-certified products being used were as follows: meat, 75.9%; eggs, 66.7%; soybean curds, 65.5%; ready-to-use seafood, 55.1%; starch jellies, 49.9%; spice, 44.9%; kimchi, 30.9%; ready-to-use vegetables, 22.7%; and fruits, 6.9%. The percentages of environment-friendly food items being used were as follows: eggs, 31.0%; meat, 28.7%; soybean curds, 22.1%; and fruits, 17.7%. Of these food items, meat and ready-to-use seafood were being used the most in the elementary schools. The percentages of imported food items being used were as follows: starch jelly, 29.2%; ready-to-use seafood, 24.7%; soybean curds, 20.5%; spice, 15.9%; and fruits, 10.1%. The food items requiring HACCP certification were as follows: beef and pork, 81.5%; chicken, 80.1%; ready-to-use seafood, 78.6%; frozen dumplings, 73.8%; soybean curds, 71.6%; peeled eggs, 70.8%; fish paste, 69.4%; starch jelly, 65.7%; milk, 63.1%; kimchi, 54.6%; spice, 50.6%; frozen noodle, 45.4%; ready-to-use vegetables, 44.3%; and bean sprouts, 29.5%. It was confirmed that 8.1% of the sanitation monitoring results were intentionally misreported. Therefore, to supply good and safe foods to schools, active management is needed in schools and food manufacturing and delivery companies.

• International Commerce and Information Review
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• v.13 no.4
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• pp.51-79
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• 2011

Korea has accomplished the establishment of the National Single Window for Paperless Trade. Since 1991, it has developed Trade Automation Service System based on EDI technology. In 2003, Korean government and private sectors jointly began to set up National Paperless Trade Service( e-Trade Service) as one of the e-government projects. In 2008, they commenced the uTradeHub Service which was equipped with Internet based e-B/L and e-Nego service systems for the first time in the world To facilitate the service Korea amended its e-Trade facilitation Act and Law by 2007. At the end of 2011, Korea historically recorded its trade volume of 1 trillion US dollars and joined '$1 trillion trade club' as the 9the member country since the country had started international trade less than five decades ago. A rolling out of the e-B/L and e-Nego service will 'ally reduce the transaction costs of trading businesses and accelerate the activation e-trade services. The purposes of the study are to examine 'e-B/L Korea' service and its facilitation strategies as well as identify obstacles to utilize the 'e-B/L Korea' service. The paper reviewed and analyzed Korea's Paperless trade system and distinctive characteristics of the 'e-B/L Korea Service. Parts of the fOWld distinctive characteristics of the Korea's e-B/L service are as follows; It is well equiped with IT and legal system. It also has more that 30,000 potential users who are already uTradeHub service users. The paper indicated several weaknesses of the current system such as global KPI issues, circulation of the electronic documents not only in the domestic market but also among economies, development of the electronic Bill of Exchange. As resolution measures, the paper recommended the introduction of mutual recognition system of PKI among trade partner counties, setting up e-trade solution for small and medium companies, and special attention to raise users' awareness of the e-B/L service.

• Korean Business Review
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• v.17 no.2
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• pp.63-87
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• 2004

To create and maintain comparative supremacy as a strategic tool of business, many organizations have introduced informational technology and system. By using this system, Some companies got a beneficial value for achieving organizational goals but others could not obtain their effectiveness and efficiency. In particular, a lot of organizations that tried to make strategic supremacy with e-commercial trade are under hard condition because of poor profit. It implies that it is essential to identify and analyse the consumer who uses e-commercial trade. This paper, therefore, focusing on internet shopping malls between business and consumer as one of areas of e-commercial trades, shows the difference between consumer expectation and performance. The results of this study are as follows: First, as for the significant difference of influencing factors to consumer satisfactions according to the types of internet shopping malls, there is a meaningful difference in consumer anxiety and internet usefulness, but not in consumer service. Prior to verify the differences in detail on consumer's anxiety and internet usefulness, we examined that there is any difference between expectation and performance. T-test was used for the variants of consumer anxiety and internet usefulness, and its meaningful probability was 0.000, which means that both showed statistically significant difference. Based on the results, we also found that regardless of the types of internet shopping malls, consumer expectation was greater than performance. although the difference between expectation and performance was not equal according to the internet shopping malls. Second, a regression analysis was performed to understand the relation between consumer service, internet usefulness, consumer anxiety, and consumer satisfaction, it was found that consumer service, internet usefulness, consumer anxiety had significantly effected on consumer satisfaction. Third, To verify the relation between consumer satisfaction and repurchase-intentions, intentions to spread out, Pearson correlation analysis was used. it was found that consumer satisfaction had positive effect on both intentions. This study has some limitations because of the shorts of money and time. since the sample of this study was consumers who have ever bought one or more products via internet shopping mall, this sample was appropriate. but the major parts of sample were college students, and the sample size was so small. therefore this results should carefully be generalized. For further study, it is required to select more precise samples and to include more variables.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.183-192
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• 2004

Even in Korea the number of steel structure buildings that allow internal space and easy change of their layouts in accordance with the purpose of buildings and box-type steel bridges constructed with thick plates with thickness in a rage just from a few $\beta$AE to \$100\beta$AE is increasing these days and therefore, domestic fabrication and processing technology of members for steel structures is being improved at a pace faster than in the past to meet the growing requirements of consumers for high reliability on quality control on the related steel structures. However, most domestic fabricators os steel structures who are turning out their steel products in accordance with the designs prepared by engineering companies in their respective works for the sake of cost cut more than anything else, hesitating to introduce any advanced new technology into themselves. In the case of the steel structure design application for small and mid-size buildings in particular, it is quite meaningful not only for those who are involved in steel structure business, but also for the people working at construction work fields to review the result of the study on the connections of steel structure members deigned to obtain superb quality of steel structures within short period for steel fabrication and erection at fields in economical ways, as there is a glowing tendency seeking standardization of connection of steel structure members as well as whole structure together with the development on design of construction system of buildings including their exterior and interior decoration materials, manufacture of the related members and fabrication technique structure. This paper has been prepared with the aim to review the peculiar characteristics of buildings constructed with the main frames of steel structures and actual cases of the change made ing the connections between steel structure columns and between columns and girder members in order to reduce the work period necessary for fabrication and erection of steel structures at the maximum as well as the some examples of steel structures fabricated through automatic welding by robots for box-type columns in addition to the description of the problems found in the course of fabricating those steel structures, suggesting possible counter-measures to solve them.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Preventive Medicine and Public Health
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• v.35 no.2
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• pp.129-135
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• 2002

Objective : The primary objective of this study was to estimate the prevalence of HBsAg-positives in the late 1990's among Korean adults. In addition, we evaluated the association of age, a residential area, a vaccination rate, a family history of chronic liver diseases and a past history of acute liver disease with the seropositivity of HBsAg, and estimated the prevalence of chronic HBV infection by follow-up for 6 month or more. Methods : A total of 10 areas, six metropolitan and four small cities, were selected. In each cities, one health screening center was selected for recruitment of study subjects. The study subjects were enrolled from a general health examination program that is provided by medical insurance companies. Questionnaires on various risk factors were administered to the study subjects. Sera was drawn and tested for HBsAg by radioimmunoassay. HBeAg and ALT were also tested for those of HBsAg positive. The HBsAg positives was retest for HBsAg 6 months later Results : Among the study subjects (n= 1816), the seroprevalence of HBsAg was 5.5% (95% CI=4.5%-6.6%), 7.4% in men (95% CI=5.8-9.4) and 3.6% in women (95% CI=2.5-5.0). A past history of acute liver disease and a family history of chronic liver diseases was shown to be risk factors for HBsAg positivity. Among the 31 HBsAg-positives, negative seroconversion rate was estimated to be 3.2%, Thus, prevalence of chronic HBV infection was estimated to be 5.3% (95% CI=3.7-6.6). Conclusion : In this study, the HBsAg seroprevalence rate was lower than that of the other studies in 1980's, particularly in young adult and women. Considering the public health importance of liver cancer and chronic liver diseases, the further effort is needed to prevent and reduce the HBV infection.

• Asia pacific journal of information systems
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• v.23 no.2
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• pp.21-39
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• 2013

As the utilization of information technology and the turbulence of technological change increase in organizations, the adoption of IT outsourcing also grows to manage IT resource more effectively and efficiently. In this new way of IT management technique, service level management(SLM) process becomes critical to derive success from the outsourcing in the view of end users in organization. Even though much of the research on service level management or agreement have been done during last decades, the performance of the service level management process have not been evaluated in terms of final objectives of the management efforts or success from the view of end-users. This study explores the relationship between SLM maturity and IT outsourcing success from the users' point of view by a analytical case study in four client organizations under an IT outsourcing vendor, which is a member company of a major Korean conglomerate. For setting up a model for the analysis, previous researches on service level management process maturity and information systems success are reviewed. In particular, information systems success from users' point of view are reviewed based the DeLone and McLean's study, which is argued and accepted as a comprehensively tested model of information systems success currently. The model proposed in this study argues that SLM process maturity influences information systems success, which is evaluated in terms of information quality, systems quality, service quality, and net effect proposed by DeLone and McLean. SLM process maturity can be measured in planning process, implementation process and operation and evaluation process. Instruments for measuring the factors in the proposed constructs of information systems success and SL management process maturity were collected from previous researches and evaluated for securing reliability and validity, utilizing appropriate statistical methods and pilot tests before exploring the case study. Four cases from four different companies under one vendor company were utilized for the analysis. All of the cases had been contracted in SLA(Service Level Agreement) and had implemented ITIL(IT Infrastructure Library), Six Sigma and BSC(Balanced Scored Card) methods since last several years, which means that all the client organizations pursued concerted efforts to acquire quality services from IT outsourcing from the organization and users' point of view. For comparing the differences among the four organizations in IT out-sourcing sucess, T-test and non-parametric analysis have been applied on the data set collected from the organization using survey instruments. The process maturities of planning and implementation phases of SLM are found not to influence on any dimensions of information systems success from users' point of view. It was found that the SLM maturity in the phase of operations and evaluation could influence systems quality only from users' view. This result seems to be quite against the arguments in IT outsourcing practices in the fields, which emphasize usually the importance of planning and implementation processes upfront in IT outsourcing projects. According to after-the-fact observation by an expert in an organization participating in the study, their needs and motivations for outsourcing contracts had been quite familiar already to the vendors as long-term partners under a same conglomerate, so that the maturity in the phases of planning and implementation seems not to be differentiating factors for the success of IT outsourcing. This study will be the foundation for the future research in the area of IT outsourcing management and success, in particular in the service level management. And also, it could guide managers in practice in IT outsourcing management to focus on service level management process in operation and evaluation stage especially for long-term outsourcing contracts under very unique context like Korean IT outsourcing projects. This study has some limitations in generalization because the sample size is small and the context itself is confined in an unique environment. For future exploration, survey based research could be designed and implemented.

• Korean journal of food and cookery science
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• v.13 no.3
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• pp.272-277
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• 1997

To evaluate the quality of commercial anchovy sauces, 8 varieties (2 products from the Fishery Cooperation, 2 from small companies, and 4 well-known brands) were chosen and their physicochemical and sensory properties were examined. The salinity of anchovy sauces ranged from 19.8％ to 26%, where product E was the saltiest and followed by F> H > B > E > A> C = G > D. Product D with the least salinity was turbid, rancid, and high in ammonia content, suggesting that it is difficult to control the quality of anchovy source with a low salt content. Protein content of anchovy sauces ranged from 2.51％ to 2.64%. The unit price of anchovy source A was the highest, whereas B was the lowest. Sensory evaluation scores of anchovy sauces were in the order of B > G > A > F > E > C > H > D for color, B > G = C > H > E = F > G > D for odor, E > C > F > G > H > D > B > A for saltiness, and B > A > C > H > E = F > G > D for overall acceptability. Above results suggest that product B was the best in quality as well as the cheapest among all. Based on the above results, kimchies were prepared with product A, B, C with a high sensory quality and product H with a high market occupancy, and sensory evaluation was performed. The kimchi with product C got the highest sensory score in appearance and the one with product A and H in odor. Although the kimchi with product A generally had high scores throughout the fermentation period, there were no significant differences in texture, salty taste, and overall acceptability among kimchies with different varieties of anchovy sauces.