• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.157-175
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• 2013

Since Korean government announced 'Smartwork promotion strategy' in 2010, Korean firms and government organizations have started to adopt smartwork. However, the smartwork has been implemented only in a few of large enterprises and government organizations rather than SMEs (small and medium enterprises). In USA, both Yahoo! and Best Buy have stopped their flexible work because of its reported low productivity and job loafing problems. In addition, according to the literature on smartwork, we could draw obstacles of smartwork adoption and categorize them into the three types: institutional, organizational, and technological. The first category of smartwork adoption obstacles, institutional, include the difficulties of smartwork performance evaluation metrics, the lack of readiness of organizational processes, limitation of smartwork types and models, lack of employee participation in smartwork adoption procedure, high cost of building smartwork system, and insufficiency of government support. The second category, organizational, includes limitation of the organization hierarchy, wrong perception of employees and employers, a difficulty in close collaboration, low productivity with remote coworkers, insufficient understanding on remote working, and lack of training about smartwork. The third category, technological, obstacles include security concern of mobile work, lack of specialized solution, and lack of adoption and operation know-how. To overcome the current problems of smartwork in reality and the reported obstacles in literature, we suggest a novel smartwork service model based on NFC(Near Field Communication). This paper suggests NFC-based Smartwork Service Model composed of NFC-based Smartworker networking service and NFC-based Smartwork space management service. NFC-based smartworker networking service is comprised of NFC-based communication/SNS service and NFC-based recruiting/job seeking service. NFC-based communication/SNS Service Model supplements the key shortcomings that existing smartwork service model has. By connecting to existing legacy system of a company through NFC tags and systems, the low productivity and the difficulty of collaboration and attendance management can be overcome since managers can get work processing information, work time information and work space information of employees and employees can do real-time communication with coworkers and get location information of coworkers. Shortly, this service model has features such as affordable system cost, provision of location-based information, and possibility of knowledge accumulation. NFC-based recruiting/job-seeking service provides new value by linking NFC tag service and sharing economy sites. This service model has features such as easiness of service attachment and removal, efficient space-based work provision, easy search of location-based recruiting/job-seeking information, and system flexibility. This service model combines advantages of sharing economy sites with the advantages of NFC. By cooperation with sharing economy sites, the model can provide recruiters with human resource who finds not only long-term works but also short-term works. Additionally, SMEs (Small Medium-sized Enterprises) can easily find job seeker by attaching NFC tags to any spaces at which human resource with qualification may be located. In short, this service model helps efficient human resource distribution by providing location of job hunters and job applicants. NFC-based smartwork space management service can promote smartwork by linking NFC tags attached to the work space and existing smartwork system. This service has features such as low cost, provision of indoor and outdoor location information, and customized service. In particular, this model can help small company adopt smartwork system because it is light-weight system and cost-effective compared to existing smartwork system. This paper proposes the scenarios of the service models, the roles and incentives of the participants, and the comparative analysis. The superiority of NFC-based smartwork service model is shown by comparing and analyzing the new service models and the existing service models. The service model can expand scope of enterprises and organizations that adopt smartwork and expand the scope of employees that take advantages of smartwork.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Journal of Chest Surgery
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• v.39 no.4 s.261
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• pp.269-274
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• 2006

Background: Tetralogy of Fallot (TOF) with pulmonary atresia and major aortopulmonary collateral arteries (MAPCAS) is complex lesion with marked heterogeneity of pulmonary blood supply and arborization anomalies. Patients with TOF with PA and MAPCAS have traditionally required multiple staged unifocalization of pulmonary blood supply before undergoing complete repair. In this report, we describe recent change of strategy and the results in our institution. Material and Method: We established surgical stratagies: early correction, central mediastinal approach, initial RV-PA conduit interposition, and aggressive intervention. Between July 1998 and August 2004, 23 patients were surgically treated at our institution. We divided them into 3 groups by initial operation method; group I: one stage total correction, group II: RV-PA conduit and unifocalization, group III: RV-PA conduit interposition only. Result: Mean ages at initial operation in each group were $13.9{\pm}16.0$ months (group 1), $10.4{\pm}15.6$ months (group II), and $7.9{\pm}7.7$ months (group III). True pulmonary arteries were not present in f patient and the pulmonary arteries were confluent in 22 patients. The balloon angioplasty was done in average 1.3 times (range: $1{\sim}6$). There were 4 early deaths relating initial operation, and 1 late death due to incracranial hemorrhage after definitive repair. The operative mortalities of initial procedures in each group were 25.0% (1/4: group I), 20.0% (2/10: group II), and 12.2% (1/9: group III). The causes of operative mortality were hypoxia (2), low cardiac output (1) and sudden cardiac arrest (1). Definitive repair rates in each group were 75% (3/4) in group I, 20% (2/10, fenestration: 2) in group II, and 55.0% (5/9, fenestration: 1) in group III. Conclusion: In patients of TOF with PA and MAPCAS, RV-PA connection as a initial procedure could be performed with relatively low risk, and high rate of definitive repair can be obtained in the help of balloon pulmonary angioplasty. One stage RV-PA connection and unifocalization appeared to be successful in selected patients.

• Childhood Kidney Diseases
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• v.7 no.2
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• pp.166-173
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• 2003

Purpose : The cause and pathogenesis of $Henoch-Sch\"{o}nlein$ purpura has been studied for many years but the results are disappointing. Recently the hypothesis that abnormalities involving the glycosylation of the hinge region of immunoglobulin Al(IgAl) may have an important role in the pathogenesis of $Henoch-Sch\"{o}nlein$ purpura is being approved. $Henoch-Sch\"{o}nlein$ purpura is the most common vasculitis Ihat affects children and the prognosis is good. But if kidney invovement occurs, the course may be chronic and troublesome. So we evaluated children with $Henoch-Sch\"{o}nlein$ purpura especially from the point of epidemiology and clinical manifestations. Methods : Investigation of 124 children who were diagnosed with $Henoch-Sch\"{o}nlein$ purpura at Inje University Ilsan Paik Hospital from December 1999 to July 2003 was performed retrospectively through chart review. Efforts were made to get informations about the profile, epidemiology, clinical manifestations, progress of the disease and recurrence rate of patients. Results : The patients were 69 boys and 55 girls, with a mean age of $6.1{\pm}2.7$ years at the time of data collection. The male to female ratio was 1.25 : 1. The occurrence rate was much higher in autumn(from September to November, 31.5%) and winter(from December to February, 28.2%) than in spring and summer, with a peak in November. Joint involvement was shown in 66.9% of patients mostly on the foot/ankle(75.9%), knee(39.8%). Seventy(56.5%) out of 124 patients had abdominal pain and 10 patients(8.1%) showed bloody stools. Renal involvement was observed in 24 patients(19.4%) after 21.1 days on the average. IgA was elevated in 10 of 21 patients(47.6%). $C_3$ and $C_4$ levels were normal in 40 of 49 patients (81.7%) and 47 of 48 patients(97.9%), respectively Antistreptolysin-O(ASO) titer was elevated over 250 Todd units in 29 of 62 Patients(46.8%). Mycoplasma antibody titer was elevated in 21 of 49 patients(42.9%) equal or greater than 1:80. Radiologic studies were peformed in 23 patients. Seven patients(30.4%) showed bowel wall thickening and one of them received intestinal resection and anastomosis operation due to terminal ileum necrosis. Eighty four patients took steroid 1.4 mg/kg/day in average. Recurrence rate was 2.5 in 37 patients(29.8%). Conclusion : $Henoch-Sch\"{o}nlein$ purpura in childhood appears most in about 6 years of age. The occurrence rate is much higher in autumn and winter relatively. Diagnosis can be made through the perspective history taking and the inspection of clinical manifestations, but the laboratory findings are not of great help. A small portion of the patients might show abdominal pain or arthritis before purpura develops, therfore various diagnosis can be made. Radiologic evaluation should be performed to avoid surgical complications in cases accompanying abdominal pain, and long term follow up should be needed especially in patients suffering from kidney involvement. In about 30% of the patients $Henoch-Sch\"{o}nlein$ purpura would recur. Steroid can be used safely without side effects.

• Asia pacific journal of information systems
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• v.23 no.4
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• pp.53-84
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• 2013

With rapid development of ICT (Information and Communications Technology), new services by the convergence of mobile network and application technology began to appear. Today, smart phone with new ICT convergence network capabilities is exceedingly popular and very useful as a new tool for the development of business opportunities. Previous studies based on Technology Acceptance Model (TAM) suggested critical factors, which should be considered for acquiring new customers and maintaining existing users in smart phone market. However, they had a limitation to focus on technology acceptance, not value based approach. Prior studies on customer's adoption of electronic utilities like smart phone product showed that the antecedents such as the perceived benefit and the perceived sacrifice could explain the causality between what is perceived and what is acquired over diverse contexts. So, this research conceptualizes perceived value as a trade-off between perceived benefit and perceived sacrifice, and we need to research the perceived value to grasp user's continuous intention to use of smart phone. The purpose of this study is to investigate the structured relationship between benefit (quality, usefulness, playfulness) and sacrifice (technicality, cost, security risk) of smart phone users, perceived value, and continuous intention to use. In addition, this study intends to analyze the differences between two subgroups of smart phone users by the degree of personal innovativeness. Personal innovativeness could help us to understand the moderating effect between how perceptions are formed and continuous intention to use smart phone. This study conducted survey through e-mail, direct mail, and interview with smart phone users. Empirical analysis based on 330 respondents was conducted in order to test the hypotheses. First, the result of hypotheses testing showed that perceived usefulness among three factors of perceived benefit has the highest positive impact on perceived value, and then followed by perceived playfulness and perceived quality. Second, the result of hypotheses testing showed that perceived cost among three factors of perceived sacrifice has significantly negative impact on perceived value, however, technicality and security risk have no significant impact on perceived value. Also, the result of hypotheses testing showed that perceived value has significant direct impact on continuous intention to use of smart phone. In this regard, marketing managers of smart phone company should pay more attention to improve task efficiency and performance of smart phone, including rate systems of smart phone. Additionally, to test the moderating effect of personal innovativeness, this research conducted multi-group analysis by the degree of personal innovativeness of smart phone users. In a group with high level of innovativeness, perceived usefulness has the highest positive influence on perceived value than other factors. Instead, the analysis for a group with low level of innovativeness showed that perceived playfulness was the highest positive factor to influence perceived value than others. This result of the group with high level of innovativeness explains that innovators and early adopters are able to cope with higher level of cost and risk, and they expect to develop more positive intentions toward higher performance through the use of an innovation. Also, hedonic behavior in the case of the group with low level of innovativeness aims to provide self-fulfilling value to the users, in contrast to utilitarian perspective, which aims to provide instrumental value to the users. However, with regard to perceived sacrifice, both groups in general showed negative impact on perceived value. Also, the group with high level of innovativeness had less overall negative impact on perceived value compared to the group with low level of innovativeness across all factors. In both group with high level of innovativeness and with low level of innovativeness, perceived cost has the highest negative influence on perceived value than other factors. Instead, the analysis for a group with high level of innovativeness showed that perceived technicality was the positive factor to influence perceived value than others. However, the analysis for a group with low level of innovativeness showed that perceived security risk was the second high negative factor to influence perceived value than others. Unlike previous studies, this study focuses on influencing factors on continuous intention to use of smart phone, rather than considering initial purchase and adoption of smart phone. First, perceived value, which was used to identify user's adoption behavior, has a mediating effect among perceived benefit, perceived sacrifice, and continuous intention to use smart phone. Second, perceived usefulness has the highest positive influence on perceived value, while perceived cost has significant negative influence on perceived value. Third, perceived value, like prior studies, has high level of positive influence on continuous intention to use smart phone. Fourth, in multi-group analysis by the degree of personal innovativeness of smart phone users, perceived usefulness, in a group with high level of innovativeness, has the highest positive influence on perceived value than other factors. Instead, perceived playfulness, in a group with low level of innovativeness, has the highest positive factor to influence perceived value than others. This result shows that early adopters intend to adopt smart phone as a tool to make their job useful, instead market followers intend to adopt smart phone as a tool to make their time enjoyable. In terms of marketing strategy for smart phone company, marketing managers should pay more attention to identify their customers' lifetime value by the phase of smart phone adoption, as well as to understand their behavior intention to accept the risk and uncertainty positively. The academic contribution of this study primarily is to employ the VAM (Value-based Adoption Model) as a conceptual foundation, compared to TAM (Technology Acceptance Model) used widely by previous studies. VAM is useful for understanding continuous intention to use smart phone in comparison with TAM as a new IT utility by individual adoption. Perceived value dominantly influences continuous intention to use smart phone. The results of this study justify our research model adoption on each antecedent of perceived value as a benefit and a sacrifice component. While TAM could be widely used in user acceptance of new technology, it has a limitation to explain the new IT adoption like smart phone, because of customer behavior intention to choose the value of the object. In terms of theoretical approach, this study provides theoretical contribution to the development, design, and marketing of smart phone. The practical contribution of this study is to suggest useful decision alternatives concerned to marketing strategy formulation for acquiring and retaining long-term customers related to smart phone business. Since potential customers are interested in both benefit and sacrifice when evaluating the value of smart phone, marketing managers in smart phone company has to put more effort into creating customer's value of low sacrifice and high benefit so that customers will continuously have higher adoption on smart phone. Especially, this study shows that innovators and early adopters with high level of innovativeness have higher adoption than market followers with low level of innovativeness, in terms of perceived usefulness and perceived cost. To formulate marketing strategy for smart phone diffusion, marketing managers have to pay more attention to identify not only their customers' benefit and sacrifice components but also their customers' lifetime value to adopt smart phone.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.9
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• pp.3856-3868
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• 2011

Until recently, research trend in real estate has been focused on real estate market and the market analysis. But the studies on real estate training program development for real estate agents to improve their job performance are relatively short in numbers. Thus, this study shows empirical analysis of the needs for the training programs for real estate agents in Cheonan to improve their job performance. The results are as follows. First, in the survey of asking what educational contents they need in order to improve real estate agents' job performance, most of the respondents show their needs for the analysis of house's value, legal knowledge, real estate management, accounting, real estate marketing, and understanding of the real estate policy. This is because they are well aware that the best way of responding to the changing clients' needs comes from training programs. Secondly, asked about real estate marketing strategies, most of respondents showed their awareness of new strategies to meet the needs of clients. This is because new forms of marketing strategies including internet ads are needed in the field as the paradigm including Information Technology changes. Thirdly, asked about the need for real estate-related training programs, 92% of the respondents answered they need real estate education programs run by the continuing education centers of the universities. In addition, the survey showed their needs for retraining programs that utilize the resources in the local universities. Other than this, to have effective and efficient training programs, they demanded running a training system by utilizing the human resources of the universities under the name of the department of 'Real Estate Contract' for real estate agents' job performance. Fourthly, the survey revealed real estate management(44.2%) and real estate marketing(42.3%) is the most chosen contents they want to take in the regular course for improving real estate agents' job performance. This shows their will to understand clients' needs through the mind of real estate management and real estate marketing. The survey showed they prefer the training programs as an irregular course to those in the regular one. Despite the above results, this study chose subjects only in Cheanan and thus it needs to research more diverse areas. The needs of programs to improve real estate agents job performance should be analyzed empirically targeting the real estate agents not just in Cheonan but also cities like Pyeongchon, Ilsan and Bundang in which real estate business is booming, as well as undergraduate and graduate students whose major is real estate studies. These studies will be able to provide information to help develop the customized training programs by evaluating elements that real estate agents need in order to meet clients satisfaction and improve their job performance. Many variables of the program development learned through these studies can be incorporated in the curriculum of the real estate studies and used very practically as information for the development of the real estate studies in this fast changing era.

• Journal of Korean Medical classics
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• v.20 no.3
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• pp.121-141
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• 2007

The outline and characteristics of the important doctors of the 'Zhe Zhong Pai'(折衷派) are as follows. Part 1. In the late Edo(江戶) period The 'Zhe Zhong Pai', which tried to take the theory and clinical treatment of the 'Hou Shi Pai (後世派)' and the 'Gu Fang Pai (古方派)' and get their strong points to make treatments perfect, appeared. Their point was 'The main part is the art of the ancients, The latter prescriptions are to be used'(以古法爲主, 後世方爲用) and the "Shang Han Lun(傷寒論)" was revered for its treatments but in actual use it was not kept at that. As mentioned above The 'Zhe Zhong Pai ' viewed treatments as the base, which was the view of most doctors in the Edo period, However, the reason the 'Zhe Zhong Pai' is not valued as much as the 'Gu Fang Pai' by medical history books in Japan is because the 'Zhe Zhong Pai' does not have the substantiation or uniqueness of the 'Gu Fang Pai', and also because the view of 'gather as well as store up' was the same as the 'Kao Zheng Pai', Moreover, the 'compromise'(折衷) point of view was from taking in both Chinese and western medical knowledge systems(漢蘭折衷), Generally the pioneer of the 'Zhe Zhong Pai' is seen as Mochizuki Rokumon(望月鹿門) and after that was Fukui Futei(福井楓亭), Wadato Kaku(和田東郭), Yamada Seichin(山田正珍) and Taki Motohiro(多紀元簡), Part 2. The lives of Wada Tokaku(和田東郭), Nakagame Kinkei(中神琴溪), Nei Teng Xi Zhe(內藤希哲), the important doctors of the 'Zhe Zhong Pai', are as follows First. Wada Tokaku(和田東郭, 1743-1803) was born when the 'Hou Shi Pai' was already declining and the 'Gu Fang Pai' was flourishing and learned medicine from a 'Hou Shi Pai' doctor, Hu Tian Xu Shan(戶田旭山) and a 'Gu Fang Pai' doctor, Yoshimasu Todo(吉益東洞). He was not hindered by 'the old ways(古方), and did not lean towards 'the new ways(後世方)' and formed a way of compromise that 'looked at hardness and softness as the same'(剛柔相摩) by setting 'the cure of the disease' as the base, and said that to cure diseases 'the old way' must be used, but 'the new way' was necessary to supplement its shortcomings. His works include "Dao Shui Suo Yan", "Jiao Chiang Fang Yi Je" and "Yi Xue Sho(醫學說)" Second. Nakagame Kinkei(中神琴溪, 1744-1833) was famous for leaving Yoshirnasu Todo(吉益東洞) and changing to the 'Zhe Zhong Pai', and in his early years used qing fen(輕粉) to cure geisha(妓女) of syphilis. His argument was "the "Shang Han Lun" must be revered but needs to be adapted", "Zhong jing can be made into a follower but I cannot become his follower", "the later medical texts such as "Ru Men Shi Qin(儒門事親)" should only be used for its prescriptions and not its theories". His works include "Shang Han Lun Yue Yan(傷寒論約言) Third. Nei Teng Xi Zhe(內藤希哲, 1701-1735) learned medicine from Qing Shui Xian Sheng(淸水先生) and went out to Edo. In his book "Yi Jing Jie Huo Lun(醫經解惑論)" he tells of how he went from 'learning'(學) to 'skepticism'(惑) and how skepticism made him learn in 'the six skepticisms'(六惑). In the latter years Xi Zhe(希哲) combines the "Shen Nong Ben Cao jing(神農本草經)", the main text for herbal medicine, "Ming Tang jing(明堂經)" of accupuncture, basic theory texts "Huang Dui Nei jing(黃帝內徑)" and "Nan jing(難經)" with the "Shang Han Za Bing Lun", a book that the 'Gu Fang Pai' saw as opposing to the rest, and became 'an expert of five scriptures'(五經一貫). Part 3. Asada Showhaku(淺田宗伯, 1815-1894) started medicine at Zhong Cun Zhong(中村中倧) and learned 'the old way'(古方) from Yoshirnasu Todo and got experience through Chuan Yue(川越) and Fu jing(福井) and received teachings in texts, history and Wang Yangmin's principles(陽明學) from famous teachers. Showhaku(宗伯) meets a medical official of the makufu(幕府), Ben Kang Zong Yuan(本康宗圓), and recieves help from the 3 great doctors of the Edo period, Taki Motokato(多紀元堅), Xiao Dao Xue GU(小島學古) and Xi Duo Cun Kao Chuang and further develops his arts. At 47 he diagnoses the general Jia Mao(家茂) with 'heart failure from beriberi'(脚氣衝心) and becomes a Zheng Shi(徵I), at 51 he cures a minister from France and received a present from Napoleon, at 65 he becomes the court physician and saves Ming Gong(明宮) jia Ren Qn Wang(嘉仁親王, later the 大正犬皇) from bodily convulsions and becomes 'the vassal of merit who saved the national polity(國體)' At the 7th year of the Meiji(明治) he becomes the 2nd owner of Wen Zhi She(溫知社) and takes part in the 'kampo continuation movement'. In his latter years he saw 14000 patients a year, so we can estimate the quality and quantity of his clinical skills Showhaku(宗伯) wrote over 80 books including the "Ju Chuang Shu Ying(橘窓書影)", "WU Wu Yao Shi Fang Han(勿誤藥室方函)", "Shang Han Biang Shu(傷寒辨術)", "jing Qi Shen Lun(精氣神論)", "Hunag Guo Ming Yi Chuan(皇國名醫傳)" and the "Xian Jhe Yi Hua(先哲醫話)". Especially in the "Ju Chuang Shu Ying(橘窓書影)" he says "the old theories are the main, and the new prescriptions are to be used"(以古法爲主, 後世方爲用), stating the 'Zhe Zhong Pai' way of thinking. In the first volume of "Shung Han Biang Shu(傷寒辨術) and "Za Bing Lun Shi(雜病論識)", 'Zong Ping'(總評), He discerns the parts that are not Zhang Zhong Jing's writings and emphasizes his theories and practical uses.