• MISULJARYO - National Museum of Korea Art Journal
• /
• v.100
• /
• pp.82-110
• /
• 2021

This study specifically examined the date of the black glazed bowls marked with "Gongyu (供御)" or "Jinzhan (進琖)" of Jian ware, one of the key research topics related to the bowls. The results of this study can be summarized as follows. Jian Kiln produced various shapes of black glazed bowls, but almost all of the inscriptions of "Gongyu (供御)" or "Jinzhan (進琖)" are found only in two certain type bowls: Type I, the Shukou type bowls (束口碗), or Type II, the Piekou type bowls (撇口碗). Of these, there are significantly more of the former in existence. For Type I bowls marked with "Gongyu (供御)" or "Jinzhan (進琖)", the mouth of the bowls is slightly evaginated outwards, and the inclination angle of the side slope is about 50°. The shape feature, Shukou (束口) is formed which is slightly indented around the bowl about 0.3~0.5cm below the mouth of bowl. And the height of the bowls is relatively low compared to other Type I black glazed bowls produced by Jian Kiln, so the height divided by the diameter is 0.5 or less. There is little difference in shape between the black glazed bowls marked with "Gongyu (供御) and those with "Jinzhan (進琖)". However, taking into consideration the excavation situation of both type bowls, the former is considered to be ahead of the latter in terms of production date. On the other hand, the black glazed bowls of Jian ware, which have the same shape features as the Type I bowls marked with "Gongyu (供御)" or "Jinzhan (進琖)" have not been found in the tombs dating from the end of the 12th to the beginning of the 13th century from which typical Jian kiln black glazed bowls of the same type were excavated. For the Hakata site (博多遺址) in Japan, the black glazed bowls with such a shape feature were excavated from early 12th century sites, rather than from the late 12th to early 13th century sites at which the typical black glazed bowls of Jian kiln were found. Considering that the black glazed bowls from Fujian province were imported into Hakata with almost no time gap, it is very unlikely that the production time of Type I black glazed bowls marked with "Gongyu (供御)" or "Jinzhan (進琖)" will deviate from the early 12th century. In conclusion, it is considered that the black glazed bowls marked with "Gongyu (供御)" or "Jinzhan (進琖)" of Jian ware were produced in the early 12th century.

• Journal of Sericultural and Entomological Science
• /
• v.13 no.2
• /
• pp.81-94
• /
• 1971

This research is conducted to study the effect to rebbuding, death atop, yielding and occurrence of twig blight disease with the interemediate cutting periods of mulberry branch and at the picking levels of leaf remains in autumn. The results obtained are as follows: 1. Re-budding branches are decreased with delaying of interval cutting period, and that more leaves remained lesser both re-budding branches and buds are observed. Therefore, it is better that leaves remained are placed on the upper part of branch, practically with 3-5 leaf remains. It has decreased re-budding branches, in case cutting is conducted in Sept. 20 with picking leaving 3-5 leaf on. 2. With regard that all picking increases the percentage of death atop of the branch and upper half part picking increases slightly over the other treats. Although it seems unlikely to be different in the other treats with cutting period, exception of all picking, it is elucidated better that the all picking after cutting in Sept. 15 represents unusually high, seemingly effected by the temperature contition preferable to the life of twig blight disease along with the lack of branch nutrition caused by the all picking. 3. In view of yielding, it has no difference in autumn yielding with cutting period, but more picking levels of leaf remains, more yielding. In spring yield, both no picking and all picking is the lowest, in spite of cutting period. Each treat produces high yielding except the no picking if rutting is done in Sept. 15 and Sept. 20, respectively; otherwise it is done earlier or later, each treat produces low yielding. It is suggested that yielding ability in following spring affected by the autumn picking because all picking treats represent lower yielding ability than no picking ones except of cutting in Sept. 15 and Sept. 20. With respect to total yield in spring and autumn, it is represented that other treats, among which cutting in Sept. 15 and Sept. 20 is especially high, produce higher yielding than both no picking and all picking. But no difference seemed in leaf remained treats. In these respects, it may be concluded that 3-5 leaf remains after the interval cutting in Sept. 15 to Sept. 20 increases the yielding throughout two seasons and it is suggested that 3-5 leaf remains after cutting in Sept. 5 to Sept. 10 has no difference with no picking and cutting after that day. 4. Diseases in the branch remained are twig blight, massaria-bye, and Die-back, of which twig blight attacks tremendously and slight ouurence in messaria-byo and Die-back. In ouurence of twig blight, it is appeared much in all picking and seasonal occurence high in Sept. 15 with 92.9, and in Sept. 30 with 100 as index, respectively. Also it occurs ,considerably in upper part picking but little occurrence in no picing. 5. It is considered that negative correlation among re-budding percentage. No. of re-budding leaf, and spring yielding is found, seemingly without heavy correlation at -0.42, and -0.27, respectively. However, death atop of branch and occurence of twig blight has little correlation with spring yield. On the other hand, positive correlation highly appeared with the correlation coefficient at 0.8 between occurence of twig blight and death atop of branch.

• Journal of Distribution Research
• /
• v.17 no.4
• /
• pp.55-80
• /
• 2012

I. Introduction Developing the relationships between companies is very important issue to ensure a competitive advantage in today's business environment (Bleeke & Ernst 1991; Mohr & Spekman 1994; Powell 1990). Partnerships between companies are based on having same goals, pursuing mutual understanding, and having a professional level of interdependence. By having such a partnerships and cooperative efforts between companies, they will achieve efficiency and effectiveness of their business (Mohr and Spekman, 1994). However, it is difficult to expect these ideal results only in the B2B corporate transaction. According to agency theory which is the well-accepted theory in various fields of business strategy, organization, and marketing, the two independent companies have fundamentally different corporate purposes. Also there is a higher chance of developing opportunism and conflict due to natures of human(organization), such as self-interest, bounded rationality, risk aversion, and environment factor as imbalance of information (Eisenhardt 1989). That is, especially partnerships between principal(or buyer) and agent(or supplier) of companies within supply chain, the business contract itself will not provide competitive advantage. But managing partnership between companies is the key to success. Therefore, managing partnership between manufacturer and supplier, and finding causes of conflict are essential to improve B2B performance. In conclusion, based on prior researches and Agency theory, this study will clarify how business hazards cause conflicts on supply chain and then identify how developed conflicts have been managed by two control mechanisms. II. Research model III. Method In order to validate our research model, this study gathered questionnaires from small and medium sized enterprises(SMEs). In Korea, SMEs mean the firms whose employee is under 300 and capital is under 8 billion won(about 7.2 million dollar). We asked the manufacturer's perception about the relationship with the biggest supplier, and our key informants are denied to a person responsible for buying(ex)CEO, executives, managers of purchasing department, and so on). In detail, we contact by telephone to our initial sample(about 1,200 firms) and introduce our research motivation and send our questionnaires by e-mail, mail, and direct survey. Finally we received 361 data and eliminate 32 inappropriate questionnaires. We use 329 manufactures' data on analysis. The purpose of this study is to identify the anticipant role of business hazard (environmental dynamism, asset specificity) and investigate the moderating effect of control mechanism(formal control, social control) on conflict-performance relationship. To find out moderating effect of control methods, we need to compare the regression weight between low versus. high group(about level of exercised control methods). Therefore we choose the structural equation modeling method that is proper to do multi-group analysis. The data analysis is performed by AMOS 17.0 software, and model fits are good statically (CMIN/DF=1.982, p<.000, CFI=.936, IFI=.937, RMSEA=.056). IV. Result V. Discussion Results show that the higher environmental dynamism and asset specificity(on particular supplier) buyer(manufacturer) has, the more B2B conflict exists. And this conflict affect relationship quality and financial outcomes negatively. In addition, social control and formal control could weaken the negative effect of conflict on relationship quality significantly. However, unlikely to assure conflict resolution effect of control mechanisms on relationship quality, financial outcomes are changed by neither social control nor formal control. We could explain this results with the characteristics of our sample, SMEs(Small and Medium sized Enterprises). Financial outcomes of these SMEs(manufacturer or principal) are affected by their customer(usually major company) more easily than their supplier(or agent). And, in recent few years, most of companies have suffered from financial problems because of global economic recession. It means that it is hard to evaluate the contribution of supplier(agent). Therefore we also support the suggestion of Gladstein(1984), Poppo & Zenger(2002) that relational performance variable can capture the focal outcomes of relationship(exchange) better than financial performance variable. This study has some implications that it tests the sources of conflict and investigates the effect of resolution methods of B2B conflict empirically. And, especially, it finds out the significant moderating effect of formal control which past B2B management studies have ignored in Korea.

• Korean Journal of Agricultural Science
• /
• v.1 no.1
• /
• pp.91-116
• /
• 1974

Taiwan agricultural development in the last decade has not been changed much since the accomplishment of land reform program. This is mainly due to the rapid development taken place within industry that agricultural development can not keep pace with. The increasing gap of rural-urban income discrepancy has caused socio-psychological unstability among rural people and inspire wants of out-migration. From 1961 to 1970, population of the ten largest cities showed an annual growth rate of 4.05%, while the population of the remainder of Taiwan showed 2.06%. Assuming the natural increase rate of these two population sections are similar, the difference of rural and urban annual growth rate can be at tributed to the flow of people from rural to urban sectors. The main objective of this paper is to identify the amount of agricultural out-migration and its impact on agricultural development and agricultural extension programs. Specifically, the objectives are to examine (1) rural-urban population composition (2) rural out-migration estimation (3) changes of agricultural population, and (4) implications for agricultural development and extension programs Some of the important findings are listed below; (1) The average agricultural out migration of the period 1960-1969 is estimated at around 60,000 per year. Take Tainan prefecture for example, the Male-Female Migration Ratio is 0.39 for age 20-24, 0.55 for age 25-29, 0.90 for 30-34. It is understood between age 20 and 34, the rural female migration rate is higher than the rural male. (2) Based on the population growth rate of 1950-1969, agricultural population is projected for the period of 1953 to 1989. By 1978, the agricultural population will reach its peak and begin to dedaine from 1980. The projected agricultural population in 1989 is 5,847,566 which occupies 29% of the Taiwan total population. (3) Assuming area of cultivated land keep unchanged as 905,263 ha. in 1970, and tif we can eliminate all 72% of part-time farms, then the average farm acreage for hose full-time farms will be increased to 3.6 hactares. This is unlikely to happen before 1989 without the government interference. (4) Less than 10% of adult farmer s of age 25-64 in 1969 enrolled in Farm Discussion Club, only 5% of adult farm women enrolled in Home Economics Club, and 5% of rural youth enrolled in 4-H Club. These statistics show a fact that only few farmers are reached by extension workers. Based on findings in this paper, some important suggestions are listed for future agricultural development. (1) Improve agricultural structure by decreasing agricultural population (a) Encourage farmers with less than 0.5 ha. of land to seek jobs outside of agriculture (b) Encourage joint cultivation and farm mechanization (c) Discourage rural migrants to Keep farm land (d) Provide occupational guidance program through extension education programs (2) Establish future farmers settlement project to assure rural youth have enough resources for farming. (3) An optimum Population policy should be integrated into rural socio-economic development and national development programs.

• Tuberculosis and Respiratory Diseases
• /
• v.44 no.2
• /
• pp.232-240
• /
• 1997

Background : Postprimary pulmonary tuberculosis is located mainly in upper lobes. The tuberculous lesion involving the lower lobes usually arises from the upper lobe cavity through endobronchial spread. When tuberculosis is confined to the lower lung field, it often masquerades as pneumonia, lung cancer, bronchiectasis, or lung abscess. Thus the correct diagnosis may be sometimes delayed for a long time. Methods : We carried out, retrospectively, a clinical study on 50 patients confirmed with lower lung field tuberculosis who visited the Department of Pulmonary Medicine at Hanyang University Hospital from January 1992 to December 1994. The following results were obtained. Results : Lower lung field tuberculosis without concomitant upper lobe disease occurred in fifty patients representing 6.9% of the total admission with active pulmonary tuberculosis over a period of 3 years. It occurred most frequently in the third decade but age distribution was relatively even. The mean age was 43 years old. Female was more frequently affected than male (male to female ratio 1 : 1.9). The most common symptom was cough(68%), followed by sputum(52%), fever(38%), and chest discomfort(30%). On chest X-ray of the 50patients, consolidation was the most common finding in 52%, followed by solitary nodule(22%) collapse(16%), cavitary lesion(10%), in decreasing order. The disease confined to the right side in 25 cases, left side 20 cases, and both sides 5 cases. Endobronchial tuberculosis (1) Endobronchial involvement was proved by bronchoscopic examination in 20 of 50patients. (2) Mean age was 44years old and female was more affected than man (male to female ratio 1 : 3). Sputum AFB stain and Mycobacterium tuberculosis culture were positive only in 50% of cases unlikely upper lobe tuberculosis, additional diagnostic methods were needed. In our study, bronchoscopic examination and percutaneous fine needle aspiration biopsy increased diagnostic yield by 18% and 32%, respectively. The most common associated condition was diabetes mellitus(18%) and others were anemia, anorexia nervosa, stomach cancer, and systemic steroid usage. Conclusion : When we find a lower lung field lesion, we should suspect tuberculosis if the patient has diabetes mellitus, anemia, systemic steroid usage, malignancy or other immune suppressed states. Because diagnostic yield of sputum AFB smear & Mycobacterium tuberculosis culture was low, additional diagnostic methods such as bronchoscopy and fine needle aspiration biopsy were needed.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.29-45
• /
• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.85-107
• /
• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.19-42
• /
• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.

• Asia pacific journal of information systems
• /
• v.20 no.3
• /
• pp.167-190
• /
• 2010

The research conducted here focuses on the effect of factors that affect the behavior of UCC (User Created Content) website users, other than user's rational recognition of how useful a UCC website can be. Most discussions in the existing literature on information systems have focused on users' evaluation how a UCC website can help to attain the users' own goals. However, there are other factors and this research pays attention to an individual's 'personality,' which is stable and biological in nature. Specifically, I have noted here that 'extroversion' and 'neuroticism,' the two common personality factors presented in Eysenck's most representative 'EPQ Model' and 'Big Five Model,' are the two personality factors that affect a site's 'usefulness,' by this I mean how useful does the user consider the website and its content. How useful a site is considered by the user is the other factor that has been regarded as the antecedent factor that influences the adoption of information systems in the existing MIS (Management Information System) research. Secondly, as using or creating a UCC website does not guarantee the user's or the creator's extrinsic motivation, unlike when using the information system within an organization, there is a greater likelihood that the increase in user's activities in relation to a UCC website is motivated by emotional factors rather than rational factors. Thus, I have decided to include the relationship between an individual's personality and what they find pleasurable in the research model. Thirdly, when based on the S-O-R Paradigm of Mehrabian and Russell, the two cognitive factors and emotional factors are finally affected by stimulus, and thus these factors ultimately have an effect on an individual's respondent behavior. Therefore, this research has presented an assumption that the recognition of how useful the site and content is and what emotional pleasure it provides will finally affect the behavior of the UCC website users. Finally, the relationship between the recognition of how useful a site is and how pleasurable it is to useand UCC usage may differ depending on certain situational conditions. In other words, the relationship between the three factors may vary according to how much users are involved in the creation of the website content. Creation thus emerges as the keyword of UCC. I analyzed the above relationships through the moderating variable of the user's involvement in the creation of the site. The research result shows the following: When it comes to the relationship between an individual's personality and what they find pleasurable it is extroverted users who have a greater likelihood to feel pleasure when using a UCC website, as was expected in this research. This in turn leads to a more active usage of the UCC web site because a person who is an extrovert likes to spend time on activities with other people, is sensitive to new experiences and stimuli and thus actively responds to these. An extroverted person accepts new UCC activities as part of his/her social life, rather than getting away from this new UCC environment. This is represented by the term 'Foxonomy' where the users meet a variety of users from all over the world and contact new types of content created by these users. However, neuroticism creates the opposite situation to that created by extroversion. The representative symptoms of neuroticism are instability, stress, and tension. These dispositions are more closely related to stress caused by a new environment rather than this creatingcuriosity or pleasure. Thus, neurotic persons have an uneasy feeling and will eventually avoid the situation where their own or others' daily lives are frequently exposed to the open web environment, this eventually makes them have a negative attitude towards the web environment. When it comes to an individual's personality and how useful site is, the two personality factors of extroversion and neuroticism both have a positive relationship with the recognition of how useful the site and its content is. The positive, curious, and social dispositions of extroverted persons tend to make them consider the future usefulness and possibilities of a new type of information system, or website, based on their positive attitude, which has a significant influence on the recognition of how useful these UCC sites are. Neuroticism also favorably affects how useful a UCC website can be through a different mechanism from that of extroversion. As the neurotic persons tend to feel uneasy and have much doubt about a new type of information system, they actively explore its usefulness in order to relieve their uncomfortable feelings. In other words, neurotic persons seek out how useful a site can be in order to secure their own stable feelings. Meanwhile, extroverted persons explore how useful a site can be because of their positive attitude and curiosity. As a lot of MIS research has revealed that the recognition of how useful a site can be and how pleasurable it can be to use have been proven to have a significant effect on UCC activity. However, the relationship between these factors reveals different aspects based on the user's involvement in creation. This factor of creationgauges the interest of users in the creation of UCC contents. Involvement is a variable that shows the level of an individual's mental effort in creating UCC contents. When a user is highly involved in the creation process and makes an enormous effort to create UCC content (classed a part of a high-involvement group), their own pleasure and recognition of how useful the site is have a significantly higher effect on the future usage of the UCC contents, more significantly than the users who sit back and just retrieve the UCC content created by others. The cognitive and emotional response of those in the low-involvement group is unlikely to last long,even if they recognize the contents of a UCC website is pleasurable and useful to them. However, the high-involvement group tends to participate in the creation and the usage of UCC more favorably, connecting the experience with their own goals. In this respect, this research presents an answer to the question; why so many people are participating in the usage of UCC, the representative form of the Web 2.0 that has drastically involved more and more people in the creation of UCC, even if they cannot gain any monetary or social compensation. Neither information system nor a website can succeed unless it secures a certain level of user base. Moreover, it cannot be further developed when the reasons, or problems, for people's participation are not suitably explored, even if it has a certain user base. Thus, what is significant in this research is that it has studied users' respondent behavior based on an individual's innate personality, emotion, and cognitive interaction, unlike the existing research that has focused on 'compensation' to explain users' participation with the UCC website. There are also limitations in this research. Firstly, I divided an individual's personality into extroversion and neuroticism; however, there are many other personal factors such as neuro-psychiatricism, which also needs to be analyzed for its influence on UCC activities. Secondly, as a UCC website comes in many types such as multimedia, Wikis, and podcasting, these types need to be included as a sub-category of the UCC websites and their relationship with personality, emotion, cognition, and behavior also needs to be analyzed.