• Journal of Society of Preventive Korean Medicine
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• v.12 no.1
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• pp.19-48
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• 2008

In order to verify the risk of onset of the illnesses based on gender, age, and monthly income 1,739 subjects from Hongcheon county, Gangwon province were selected. Questionnaire on demographic sociology, health condition, existence of illnesses(cancer, hypertension, stroke, diabetes, arthritis, cardiac disorders), and usage of public health services was surveyed from October 1, 2006 to October 20, 2006. Following conclusions were reached on the basis of the questionnaire : - For demographic sociological peculiarities, gender, age, occupation, and education level were evenly distributed. Most were under normal marriage(67.38%), health insurance(86.39%), 494(36.0%) individuals with less than monthly income of 1 million won, 494(36.0%) individuals with monthly income between 1 and 2 million won, 219(16.0%) with monthly income between 2 and 3 million won, and 164(12.0%) individuals with more than 3 million won, thus showing relatively low income. - For health status, 1,199(70.28%) individuals are non-smokers, 209(45.63%) individuals smoke $10{\sim}20$ cigarettes a day, 754(44.02%) individuals exercise less than twice a week are the major sector of the population. 1,518(88.10%) individuals have regular checkup more than once and 1,131(65.49%) stated their health condition less than average. - For comparison of existence of illnesses between genders, there was no statistical significance on cancer, stroke, and diabetes. But statistical significance was shown on hypertension(P value 0.025), arthritis(P value 0.000), and cardiac disorders(P value 0.016). Statistical significance was seen in the age comparison, and OR(confidence interval) drastically increased with increase in age. - There was no difference between the primary health clinic(P value 0.000), most visited clinic(P value 0.000), selection criteria(P value 0.000), and satisfaction on efficacy(P value 0.000). There was a tendency preferring hospital than public health center with increase in income. - For correlation between the existence of illnesses among different income levels, except for cancer(P value 0.172), statistical significance was seen in hypertension(P value 0.000), stroke(P value 0.003), diabetes (P value 0.001), arthritis(P value 0.000), and cardiac disorders(P value 0.000). The number of individuals suffering from illnesses and ratio all decreased for all illnesses with increase in income. - After adjusting confounding factors(gender, age, income, marriage, occupation, education) and male (1) as the standard, OR (confidence interval) of cancer, hypertension, stroke, diabetes, arthritis, cardiac disorders were 0.47(0.11${\sim}$2.05), 1.27(0.89${\sim}$1.81), 0.58(0.21${\sim}$1.59), 0.71(0.41${\sim}$1.23), 1.79(1.34${\sim}$2.39, P<0.01), and 1.46(0.72${\sim}$2.96), respectively. Risk of arthritis is significantly high in female and 20's (1) as the standard, OR(confidence interval) of cancer, hypertension, stroke, diabetes, arthritis, cardiac disorders were 1.01(0.96${\sim}$1.07), 1.06(1.04${\sim}$1.07, P<0.01), 1.05(1.01${\sim}$1.10, P<0.01), 1.06(1.03${\sim}$1.08, P<0.01), 1.05(1.03${\sim}$1.06, P<0.01), and 1.06(1.04${\sim}$1.09, P<0.01), respectively. Risk of onset for illnesses significantly increased with yearly aging except for cancer. - For comparison between monthly income after adjusting confounding factors(gender, age, income, marriage, occupation, education), with less than 1 million won (1) as the standard, OR(confidence interval) of cancer for 1 to 2 million won, 2 to 3 million won, and more than 3 million won were 0.23(0.03${\sim}$2.16), 2.53(0.41${\sim}$15.43), and 1.73(0.15${\sim}$19.50), respectively. OR(confidence interval) of hypertension were 1.12(0.76 ${\sim}$1.66), 0.68(0.34${\sim}$1.34), and 2.04(1.08${\sim}$3.86, P<0.01), respectively. OR(confidence interval) of stroke were 0.96(0.30${\sim}$3.08) for 1 to 2 million won, and 0.80(0.08${\sim}$8.46) for 2 to 3 million won. OR(confidence interval) of diabetes were 0.73(0.38${\sim}$1.38), 0.65(0.24${\sim}$1.71), and 0.69(0.24${\sim}$2.01), respectively. The values were 0.76(0.55${\sim}$1.03), 1.14(0.75${\sim}$1.73), and 0.90(0.56${\sim}$1.46), respectively for arthritis. OR(confidence interval) of cardiac disorders were 1.15(0.53${\sim}$2.48), 0.63(0.13${\sim}$3.12), and 1.20(0.28${\sim}$5.14), respectively. Risks of cancer, hypertension, stroke, diabetes, arthritis, and cardiac disorders were dependent of monthly income, and stroke and diabetes decreased with increase in income. Summarizing above data, arthritis was significantly higher in women and increase in age by each year brought significant increase in the chance of onset in hypertension, stroke, diabetes, arthritis, and cardiac disorders except for cancer. Stroke and diabetes decreased with increase in income. Above findings can be applied and reflected in public health policies at the national level, and it can also be applied at the personal level for individual health maintenance and prevention.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.35 no.3
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• pp.13-21
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• 2017

The Cho-yeon Pavilion located in the Wangdae village in Samcheong-ri, Songgwang-myeon, Suncheon-si, was transformed into a place of refuge, a shrine, a vacation home, a lecture hall for kings. Based on the change, the current study has explored the periodic changing placeness and the transformation of cultural landscape and has figured out the meaning. The result of this study is as follows. First, "Cho-yeon", named by Yeonjae Song, Byeong-Seon, originated from Tao Te Ching of Lao Tzu. The concept is found not only in the Cho-yeon Pavilion in Suncheon but also in various places, such as, the Cho-yeon-dae in Pocheon, of the Cho-yeon-dae in Gapyeong, of the Cho-yeon-dae of the embankment behind the Gioheon of Changdeok-gung Garden, Cho-Yeon-Mul-Oe old buildings, including Jung(亭), Dae(臺), Gak(閣), of Ockriukag in Yuseong, etc. This shows that taoistic Poongrhu was naturally grafted onto confucian places, which is one of the examples of the fusion of Confucianism, Buddhism, and Taoism. Second, the placeness of the Cho-yeon Pavilion area is related to a legend that King Gong-min sought refuge here at the end of the Koryo Dynasty. The legend is based on the Wangdae village(king's region), Yu-Gyeong(留京)(the place where kings stayed), rock inscription of Wang-Dae-Sa-Jeok, Oh-Jang-Dae (the place where admiral flags were planted), and the Mohusan Mountain. Third, the Cho-yeon Pavilion not only has a base(the vacation home) that reflects confucian values from the rock inscription(趙鎭忠別業, 趙秉翼, 宋秉璿) of the beautiful rock walls and torrents but also has territoriality as taoistic Abode of the Immortals (there are places where people believe taoist hermits with miraculous powers live within 1km of the pavillion: Wol-Cheong(月靑), Pung-Cheong(風靑), Su-Cheong(水靑), Dong-Cheon(洞天). The Cho-yeon Pavilion also reflects the heaven of Neo-Confucianism for, pursuing study, and improving aesthetic sense by expanding its outer area and establishing the nine Gok: Se-Rok-Gyo(洗鹿橋)., Bong-Il-Dae(捧日臺), Ja-Mi-Gu(紫薇鳩), Un-Mae-Dae(雲梅臺), Wa-Ryong-Chong(臥龍叢), Gwang-Seok-Dae(廣石臺), Eun-Seon-Gul(隱仙窟), Byeok-Ok-Dam(碧玉潭), and Wa-Seok-Po(臥石布). In sum, the Cho-yeon Pavilion is a complex cultural landscape. Fourth, the usage of the Cho-yeon Pavilion was expanded and transformed: (1)Buddhist monastery${\rightarrow}$(2)Confucian vacation home${\rightarrow}$(3)Vacation home+Taoistic Poongrhu Place${\rightarrow}$(4)Vacation Home+Taoistic Poongrhu Place+Lecture Hall(the heaven of Neo-Confucianism). To illustrate, in 7978, the place served as Buddist Monk Kwang-Sa's monastery; in 1863, Cho, Jin-Choong established a vacation home by building a shrine in front of the tomb of his ancestor; in 1864, Cho, Jae-Ho expanded its usage to a vacation home to serve ancestors as a taoistic place by repairing the pavilion with roof tiles; and after 1890, Cho, Jun-Sup received the name of the pavilion, Cho-yeon, from his teacher Song, Byeong-Seon, and used the Pavilion for a lecture hall.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of Environmental Policy
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• v.13 no.4
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• pp.3-49
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• 2014

Growing interest of stakeholders on corporate responsibilities for environment and tightening environmental regulations are highlighting the importance of environmental management more than ever. However, companies' awareness of the importance of environment is still falling behind, and related academic works have not shown consistent conclusions on the relationship between environmental performance and economic performance. One of the reasons is different ways of measuring these two performances. The evaluation scope of economic performance is relatively narrow and the performance can be measured by a unified unit such as price, while the scope of environmental performance is diverse and a wide range of units are used for measuring environmental performances instead of using a single unified unit. Therefore, the results of works can be different depending on the performance indicators selected. In order to resolve this problem, generalized and standardized performance indicators should be developed. In particular, the performance indicators should be able to cover the concepts of both environmental and economic performances because the recent idea of environmental management has expanded to encompass the concept of sustainability. Another reason is that most of the current researches tend to focus on the motive of environmental investments and environmental performance, and do not offer a guideline for an effective implementation strategy for environmental management. For example, a process improvement strategy or a market discrimination strategy can be deployed through comparing the environment competitiveness among the companies in the same or similar industries, so that a virtuous cyclical relationship between environmental and economic performances can be secured. A novel method for measuring eco-efficiency by utilizing Data Envelopment Analysis (DEA), which is able to combine multiple environmental and economic performances, is proposed in this report. Based on the eco-efficiencies, the environmental competitiveness is analyzed and the optimal combination of inputs and outputs are recommended for improving the eco-efficiencies of inefficient firms. Furthermore, the panel analysis is applied to the causal relationship between eco-efficiency and economic performance, and the pooled regression model is used to investigate the relationship between eco-efficiency and economic performance. The four-year eco-efficiencies between 2010 and 2013 of 23 companies are obtained from the DEA analysis; a comparison of efficiencies among 23 companies is carried out in terms of technical efficiency(TE), pure technical efficiency(PTE) and scale efficiency(SE), and then a set of recommendations for optimal combination of inputs and outputs are suggested for the inefficient companies. Furthermore, the experimental results with the panel analysis have demonstrated the causality from eco-efficiency to economic performance. The results of the pooled regression have shown that eco-efficiency positively affect financial perform ances(ROA and ROS) of the companies, as well as firm values(Tobin Q, stock price, and stock returns). This report proposes a novel approach for generating standardized performance indicators obtained from multiple environmental and economic performances, so that it is able to enhance the generality of relevant researches and provide a deep insight into the sustainability of environmental management. Furthermore, using efficiency indicators obtained from the DEA model, the cause of change in eco-efficiency can be investigated and an effective strategy for environmental management can be suggested. Finally, this report can be a motive for environmental management by providing empirical evidence that environmental investments can improve economic performance.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• Journal of Distribution Research
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• v.17 no.1
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• pp.37-63
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• 2012

In franchise business, exclusive sales territory (sometimes EST in table) protection is a very important issue from an economic, social and political point of view. It affects the growth and survival of both franchisor and franchisee and often raises issues of social and political conflicts. When franchisee is not familiar with related laws and regulations, franchisor has high chance to utilize it. Exclusive sales territory protection by the manufacturer and distributors (wholesalers or retailers) means sales area restriction by which only certain distributors have right to sell products or services. The distributor, who has been granted exclusive sales territories, can protect its own territory, whereas he may be prohibited from entering in other regions. Even though exclusive sales territory is a quite critical problem in franchise business, there is not much rigorous research about the reason, results, evaluation, and future direction based on empirical data. This paper tries to address this problem not only from logical and nomological validity, but from empirical validation. While we purse an empirical analysis, we take into account the difficulties of real data collection and statistical analysis techniques. We use a set of disclosure document data collected by Korea Fair Trade Commission, instead of conventional survey method which is usually criticized for its measurement error. Existing theories about exclusive sales territory can be summarized into two groups as shown in the table below. The first one is about the effectiveness of exclusive sales territory from both franchisor and franchisee point of view. In fact, output of exclusive sales territory can be positive for franchisors but negative for franchisees. Also, it can be positive in terms of sales but negative in terms of profit. Therefore, variables and viewpoints should be set properly. The other one is about the motive or reason why exclusive sales territory is protected. The reasons can be classified into four groups - industry characteristics, franchise systems characteristics, capability to maintain exclusive sales territory, and strategic decision. Within four groups of reasons, there are more specific variables and theories as below. Based on these theories, we develop nine hypotheses which are briefly shown in the last table below with the results. In order to validate the hypothesis, data is collected from government (FTC) homepage which is open source. The sample consists of 1,896 franchisors and it contains about three year operation data, from 2006 to 2008. Within the samples, 627 have exclusive sales territory protection policy and the one with exclusive sales territory policy is not evenly distributed over 19 representative industries. Additional data are also collected from another government agency homepage, like Statistics Korea. Also, we combine data from various secondary sources to create meaningful variables as shown in the table below. All variables are dichotomized by mean or median split if they are not inherently dichotomized by its definition, since each hypothesis is composed by multiple variables and there is no solid statistical technique to incorporate all these conditions to test the hypotheses. This paper uses a simple chi-square test because hypotheses and theories are built upon quite specific conditions such as industry type, economic condition, company history and various strategic purposes. It is almost impossible to find all those samples to satisfy them and it can't be manipulated in experimental settings. However, more advanced statistical techniques are very good on clean data without exogenous variables, but not good with real complex data. The chi-square test is applied in a way that samples are grouped into four with two criteria, whether they use exclusive sales territory protection or not, and whether they satisfy conditions of each hypothesis. So the proportion of sample franchisors which satisfy conditions and protect exclusive sales territory, does significantly exceed the proportion of samples that satisfy condition and do not protect. In fact, chi-square test is equivalent with the Poisson regression which allows more flexible application. As results, only three hypotheses are accepted. When attitude toward the risk is high so loyalty fee is determined according to sales performance, EST protection makes poor results as expected. And when franchisor protects EST in order to recruit franchisee easily, EST protection makes better results. Also, when EST protection is to improve the efficiency of franchise system as a whole, it shows better performances. High efficiency is achieved as EST prohibits the free riding of franchisee who exploits other's marketing efforts, and it encourages proper investments and distributes franchisee into multiple regions evenly. Other hypotheses are not supported in the results of significance testing. Exclusive sales territory should be protected from proper motives and administered for mutual benefits. Legal restrictions driven by the government agency like FTC could be misused and cause mis-understandings. So there need more careful monitoring on real practices and more rigorous studies by both academicians and practitioners.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

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

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.