• The Journal of Korean Philosophical History
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• no.28
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• pp.183-212
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• 2010

The purpose of this study is to provide a theoretical base for making a character education program and to develop a school violence prevention program and analysis the effects of the program in elementary schools. The prevention program was designed to target students, teachers, parents and community residents and utilized the above groups as participants. This study is developed on the basis of Social Emotional Learning as well as Emotional Intelligence which put on the importance on the role of emotion in the problem solving. In concrete, school violence prevention program based on the social and emotional learning, development of integrative programs articulating three key domains directly and indirectly influencing students' character formation, maximum use of the educational institutes' moral education curriculums and potential curriculums in the surrounding environment. To do so, bibliographical study and analysis of the research materials are carried out, and also the professionals' advice is received. The study object is 113 elementary school students of 2 elementary schools in Seoul. For them, the preparatory program is carried out from September 2009 to November 2009. And then, the analysis for the satisfaction degree of participation in the program and for the descriptive results of the school violence prevention education is carried out.

• Asia Marketing Journal
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• v.13 no.3
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• pp.103-134
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• 2011

The recent economic recession and price rise reduces excessive consumption as a whole. So companies take more interest in and use discount coupons as a means of sales promotion to reinforce their competitiveness. The combination of Internet and mobile communication technology leads to an explosive increase in the use of mobile Internet service, which promotes commercialization of mobile coupons. Nevertheless, there are absolutely insufficient researches on mobile coupons than those on paper ones. In this context, this study tries to consider intention of accepting and using mobile coupons. The innovated Technology Acceptance Model (TAM) was used to see factors of using mobile coupons considered important by customers. Through the combination of characteristics of mobile coupon service and values obtained from mobile coupons, effects of variables to enhance intention of using mobile coupons were empirically analyzed. In particular, this study suggested importance of psychological as well as economic values of mobile coupons and emphasized good considerations of the psychological aspect, such as shame, stinginess, and reputation sensitivity, in using mobile coupons as an important factor for intention of using the coupons. Another empirical analysis was made of what moderating roles consumers' self-construalplayed in the effects of mobile coupon values perceived by consumers on intention of using coupons. As a result, immediate connectivity and situational provision among characteristics of mobile coupon service were found to affect ease and usability. It was also shown that perceived ease and usability had significant effects on both economic and psychological values, which then had significant effects on intention of using a mobile system. After testing moderating effects of self-construal, the degree of effects of perceived mobile coupon values on intention of using mobile coupons was greater among inter-dependent self-construal users than among independent ones. This study considered various schemes of improving intention to use mobile coupons and provided a foundation to help companies make a strategy for mobile coupons to be activated in the future.

• Journal of Korean Society of Forest Science
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• v.56 no.1
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• pp.1-25
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• 1982

Plywood used for construction as a decorative inner material is inflammable and can cause fire accidents. causing destruction of human life and property. To diminish the fire disaster, fire retardant plywood is indeed required. In the methods of manufacturing the fire retardant plywood, a soaking method is occasionally used. However after soaking plywood into fire retardant chemical solutions redrying of soaked plywood is of the utmost importance. In this study 3.5mm and 5.0mm thickness plywoods were selected for fire retardant treatment. Treating solutions were prepared for 20% dilute solutions of ammonium sulfate, monoammonium phosphate, diammonium phosphate, borax-boric acid minalith, and water solution, 1-, 3-, 6-, and 9 hour-soaking treatments in borax-boric acid and minalith, and 6- and 9 hours in the other chemicals were applied and after the treatment hot drying was applied to treated plywoods at $90^{\circ}C$, $120^{\circ}C$ and $150^{\circ}C$ of press temperature. Drying rates, drying curves, water absorption rates of fire retardant chemicals, weight per volume and fire retardant degree of plywood were investigated. The results may be summarized as follows: 1) In the 9 hours-soaking treatment of fire retardants by hot and cold bath method, the chemical retentions of 3.5mm thickness plywood could be attained within the range ($1.125-2.25kg/(30cm)^3$) of minimum retention specification as follows: $1.353kg/(30cm)^3$ in monoammonium phosphate, $1.331kg/(30cm)^3$ in diammonium phosphate, $1.263kg/(30cm)^3$ in ammonium sulfate, $1.226kg/(30cm)^3$ in borax-boric acid. But the chemical retention, $0.906kg/(30cm)^3$, in minalith could not be attained within the range of minimum retention specification. And also in case of 5.0mm thickness plywood, chemical retentions, as $1.356kg/(30cm)^3$ and $1.166kg/(30cm)^3$ respectively, of ammonium sulfate and diammonium phosphate could be attained within the range minimum retention specification, but the other fire retardant chemicals could not. 2) In the 6- and - hours-soaking treatments of 3.5mm and 5.0mm thickness plywood, the drying curve sloped of chemical treated plywood was smaller than that of water treated. The drying rate related to thickness of treated plywood, was about three times as fast in 3.5mm thickness plywood compared with 5.0mm thickness plywood. 3) In the treatment at $120^{\circ}C$ of hot platen temperature, the drying rates of chemical-treated plywood showed the highest quantity in diammonium phosphate of 3.5mm and 5.0mm thickness plywood. But the drying rate of water treated plywood was highest during the 6- and 9 hours-soaking treatments. 4) The drying rate remarkably increased with proportion to increase of the platen temperature, and the values were respectively 1.23%/min., 6.54%/min., 25.75%/min. in hot platen temperature of $90^{\circ}C$, $120^{\circ}C$, $150^{\circ}C$ in 3.5mm thickness plywood and 0.55%.min., 2.49%/min., 8.19%/min. in hot platen temperature of $90^{\circ}C$, $120^{\circ}C$, $150^{\circ}C$ in 5.0mm thickness plywood. 5) In the fire retardant degree of chemical treated plywood, the loss in weight was the smallest in diammonium phosphate, next was in monoammonium phosphate and ammonium sulfate, and the greatest was in borax-boric acid and minalith. And the fire-retardant effect in burning time, flame-exhausted time and carbonized area were greatest in diammouniun phosphate, next were in monoammonium phosphate and ammonium sulfate, and the weakest were in borax-boric acid and minalith.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.123-138
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• 2017

Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.

• Journal of Distribution Research
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• v.17 no.2
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• pp.29-62
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• 2012

As distribution environment is changing rapidly and competition is more intensive in the channel of distribution, the importance of retailer image and retailer equity is increasing as a different competitive advantages. Also, consumers are not functionally oriented and that their behavior is significantly affected by the symbols such as retailer image which identify retailer in the market place. That is, consumers do not choose products or retailers for their material utilities but consume the symbolic meaning of those products or retailers as expressed in their self images. The concept of self-image congruence has been utilized by marketers and researchers as an aid in better understanding how consumers identify themselves with the brands they buy and the retailer they patronize. Although self-image congruity theory has been tested across many product categories, the theory has not been tested extensively in the retailing. Therefore, this study attempts to investigate the impact of self image congruence between retailer image and self image of consumer on retailer equity such as retailer awareness, retailer association, perceived retailer quality, and retailer loyalty. The purpose of this study is to find out whether retailer-self image congruence can be a new antecedent of retailer equity. In addition, this study tries to examine how four-dimensional retailer equity constructs (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) affect customers' repatronage intention. For this study, data were gathered by survey and analyzed by structural equation modeling. The sample size in the present study was 254. The reliability of the all seven dimensions was estimated with Cronbach's alpha, composite reliability values and average variance extracted values. We determined whether the measurement model supports the convergent validity and discriminant validity by Exploratory factor analysis and Confirmatory Factor Analysis. For each pair of constructs, the square root of the average variance extracted values exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the AMOS 18.0. As expected, the image congruence hypotheses were supported. The greater the degree of congruence between retailer image and self-image, the more favorable were consumers' retailer evaluations. The all two retailer-self image congruence (actual self-image congruence and ideal self-image congruence) affected customer based retailer equity. This result means that retailer-self image congruence is important cue for customers to estimate retailer equity. In other words, consumers are often more likely to prefer products and retail stores that have images similar to their own self-image. Especially, it appeared that effect for the ideal self-image congruence was consistently larger than the actual self-image congruence on the retailer equity. The results mean that consumers prefer or search for stores that have images compatible with consumer's perception of ideal-self. In addition, this study revealed that customers' estimations toward customer based retailer equity affected the repatronage intention. The results showed that all four dimensions (retailer awareness, retailer association, perceived retailer quality, and retailer loyalty) had positive effect on the repatronage intention. That is, management and investment to improve image congruence between retailer and consumers' self make customers' positive evaluation of retailer equity, and then the positive customer based retailer equity can enhance the repatonage intention. And to conclude, retailer's image management is an important part of successful retailer performance management, and the retailer-self image congruence is an important antecedent of retailer equity. Therefore, it is more important to develop and improve retailer's image similar to consumers' image. Given the pressure to provide increased image congruence, it is not surprising that retailers have made significant investments in enhancing the fit between retailer image and self image of consumer. The enhancing such self-image congruence may allow marketers to target customers who may be influenced by image appeals in advertising.

• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.9
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• pp.1265-1273
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• 2012

The purpose of this study was to investigate the BMI, intake of snacks, and perceptions and use of food and nutrition labels by middle school students (144 boys and 189 girls) in Chuncheon area. The average height and weight of boys were $171.0{\pm}6.4$ cm and $61.0{\pm}11.4$ kg, respectively, whereas those of girls were $160.0{\pm}4.8$ cm and $50.8{\pm}6.6$ kg, respectively. Average body mass index (BMI) of boys and girls were $20.8{\pm}3.3$ and $19.8{\pm}2.4$, respectively (p<0.01). Dietary intake attitude score of girls ($34.39{\pm}5.66$) was higher than that of boys ($33.92{\pm}5.40$) (p<0.05). Subjects bought and ate snacks 1 to 3 times per week (40.2%) by themselves, and most consumed snacks were cookies (23.1%), instant noodles (16.2%), ice cream (13.2%), and candy and chocolates (13.2%). The most important factor in purchasing of snacks was 'taste' ($4.49{\pm}0.67$). When subjects bought processed foods, the rates of reading food labels was 86.6%. The most important factor of the food labels was 'expiration date' (42.9%). The degree of reading food labels on processed foods by girls ($22.70{\pm}5.72$) was higher than that of boys ($20.96{\pm}5.35$) (p<0.01). Of the 13.2% of subjects that did not read food labels, the reason why was that they were not interested (50.0%). Of the 78.4% of subjects that read nutrition labels, the most important component of the nutrition labels was 'calories' (75.9%). The main reason for reading nutrition labels was 'to control weight' (45.6%). In general, use of food labels correlated positively with dietary intake attitude score (p<0.05) and use of nutrition labels (p<0.01). Using multiple regression analysis, we found that 'usefulness of dietary life' was the most significant variable that affects the importance of food and nutrition labels. Therefore, development of an educational program on food and nutrition labels for adolescents will be effective in improving dietary life.

• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.195-215
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• 2008

The scarcity is pervasive aspect of human life and is a fundamental precondition of economic behavior of consumers. Also, the effect of scarcity message is a power social influence principle used by marketers to increase the subjective desirability of products. Because valuable objects are often scare, consumers tend to infer the scarce objects are valuable. Marketers often do base promotional appeals on the principle of scarcity to increase the subjective desirability their products among consumers. Specially, advertisers and retailers often promote their products using restrictions. These restriction act to constraint consumers' ability th take advantage of the promotion and can assume several forms. For example, some promotions are advertised as limited time offers, while others limit the quantity that can be bought at the deal price by employing the statements such as 'limit one per consumer,' 'limit 5 per customer,' 'limited products for special commemoration celebration,' Some retailers use statements extensively. A recent weekly flyer by a prominent retailer limited purchase quantities on 50% of the specials advertised on front page. When consumers saw these phrase, they often infer value from the product that has limited availability or is promoted as being scarce. But, the past researchers explored a direct relationship between the purchase quantity and time limit on deal purchase intention. They also don't explored that all restriction message are not created equal. Namely, we thought that different restrictions signal deal value in different ways or different mechanism. Consumers appear to perceive that time limits are used to attract consumers to the brand, while quantity limits are necessary to reduce stockpiling. This suggests other possible differences across restrictions. For example, quantity limits could imply product quality (i.e., this product at this price is so good that purchases must be limited). In contrast, purchase preconditions force the consumer to spend a certain amount to qualify for the deal, which suggests that inferences about the absolute quality of the promoted item would decline from purchase limits (highest quality) to time limits to purchase preconditions (lowest quality). This might be expected to be particularly true for unfamiliar brands. However, a critical but elusive issue in scarcity message research is the impacts of a inferred motives on the promoted scarcity message. The past researchers not explored possibility of inferred motives on the scarcity message context. Despite various type to the quantity limits message, they didn't separated scarcity message among the quantity limits. Therefore, we apply a stricter definition of scarcity message(i.e. quantity limits) and consider scarcity message type(general scarcity message vs. special scarcity message), scarcity depth(high vs. low). The purpose of this study is to examine the effect of the scarcity message on the consumer's purchase intension. Specifically, we investigate the effect of general versus special scarcity messages on the consumer's purchase intention using the level of the scarcity depth as moderators. In other words, we postulates that the scarcity message type and scarcity depth play an essential moderating role in the relationship between the inferred motives and purchase intention. In other worlds, different from the past studies, we examine the interplay between the perceived motives and scarcity type, and between the perceived motives and scarcity depth. Both of these constructs have been examined in isolation, but a key question is whether they interact to produce an effect in reaction to the scarcity message type or scarcity depth increase. The perceived motive Inference behind the scarcity message will have important impact on consumers' reactions to the degree of scarcity depth increase. In relation ti this general question, we investigate the following specific issues. First, does consumers' inferred motives weaken the positive relationship between the scarcity depth decrease and the consumers' purchase intention, and if so, how much does it attenuate this relationship? Second, we examine the interplay between the scarcity message type and the consumers' purchase intention in the context of the scarcity depth decrease. Third, we study whether scarcity message type and scarcity depth directly affect the consumers' purchase intention. For the answer of these questions, this research is composed of 2(intention inference: existence vs. nonexistence)${\times}2$(scarcity type: special vs. general)${\times}2$(scarcity depth: high vs. low) between subject designs. The results are summarized as follows. First, intention inference(inferred motive) is not significant on scarcity effect in case of special scarcity message. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of general scarcity. Second, intention inference(inferred motive) is not significant on scarcity effect in case of low scarcity. However, nonexistence of intention inference is more effective than existence of intention inference on purchase intention in case of high scarcity. The results of this study will help managers to understand the relative importance among the type of the scarcity message and to make decisions in using their scarcity message. Finally, this article have several contribution. First, we have shown that restrictions server to activates a mental resource that is used to render a judgment regarding a promoted product. In the absence of other information, this resource appears to read to an inference of value. In the presence of other value related cue, however, either database(i.e., scarcity depth: high vs. low) or conceptual base(i.e.,, scarcity type special vs. general), the resource is used in conjunction with the other cues as a basis for judgment, leading to different effects across levels of these other value-related cues. Second, our results suggest that a restriction can affect consumer behavior through four possible routes: 1) the affective route, through making consumers feel irritated, 2) the cognitive making route, through making consumers infer motivation or attribution about promoted scarcity message, and 3) the economic route, through making the consumer lose an opportunity to stockpile at a low scarcity depth, or forcing him her to making additional purchases, lastly 4) informative route, through changing what consumer believe about the transaction. Third, as a note already, this results suggest that we should consider consumers' inferences of motives or attributions for the scarcity dept level and cognitive resources available in order to have a complete understanding the effects of quantity restriction message.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.27-55
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• 2008

Due to the increasing and intensifying competition in the Internet shopping market, it has been recognized as very important to develop an effective policy and strategy for acquiring loyal customers. For this reason, web site designers need to know if a new Internet shopping mall(ISM) will be accepted. Researchers have been working on identifying factors for explaining and predicting user acceptance of an ISM. Some studies, however, revealed inconsistent findings on the antecedents of user acceptance of a website. Lack of consideration for individual differences in user ability is believed to be one of the key reasons for the mixed findings. The elaboration likelihood model (ELM) and several studies have suggested that individual differences in ability plays an moderating role on the relationship between the antecedents and user acceptance. Despite the critical role of user ability, little research has examined the role of user ability in the Internet shopping mall context. The purpose of this study is to develop a user acceptance model that consider the moderating role of user ability in the context of Internet shopping. This study was initiated to see the ability of the technology acceptance model(TAM) to explain the acceptance of a specific ISM. According to TAM. which is one of the most influential models for explaining user acceptance of IT, an intention to use IT is determined by usefulness and ease of use. Given that interaction between user and website takes place through web interface, the decisions to accept and continue using an ISM depend on these beliefs. However, TAM neglects to consider the fact that many users would not stick to an ISM until they trust it although they may think it useful and easy to use. The importance of trust for user acceptance of ISM has been raised by the relational views. The relational view emphasizes the trust-building process between the user and ISM, and user's trust on the website is a major determinant of user acceptance. The proposed model extends and integrates the TAM and relational views on user acceptance of ISM by incorporating usefulness, ease of use, and trust. User acceptance is defined as a user's intention to reuse a specific ISM. And user ability is introduced into the model as moderating variable. Here, the user ability is defined as a degree of experiences, knowledge and skills regarding Internet shopping sites. The research model proposes that the ease of use, usefulness and trust of ISM are key determinants of user acceptance. In addition, this paper hypothesizes that the effects of the antecedents(i.e., ease of use, usefulness, and trust) on user acceptance may differ among users. In particular, this paper proposes a moderating effect of a user's ability on the relationship between antecedents with user's intention to reuse. The research model with eleven hypotheses was derived and tested through a survey that involved 470 university students. For each research variable, this paper used measurement items recognized for reliability and widely used in previous research. We slightly modified some items proper to the research context. The reliability and validity of the research variables were tested using the Crobnach's alpha and internal consistency reliability (ICR) values, standard factor loadings of the confirmative factor analysis, and average variance extracted (AVE) values. A LISREL method was used to test the suitability of the research model and its relating six hypotheses. Key findings of the results are summarized in the following. First, TAM's two constructs, ease of use and usefulness directly affect user acceptance. In addition, ease of use indirectly influences user acceptance by affecting trust. This implies that users tend to trust a shopping site and visit repeatedly when they perceive a specific ISM easy to use. Accordingly, designing a shopping site that allows users to navigate with heuristic and minimal clicks for finding information and products within the site is important for improving the site's trust and acceptance. Usefulness, however, was not found to influence trust. Second, among the three belief constructs(ease of use, usefulness, and trust), trust was empirically supported as the most important determinants of user acceptance. This implies that users require trustworthiness from an Internet shopping site to be repeat visitors of an ISM. Providing a sense of safety and eliminating the anxiety of online shoppers in relation to privacy, security, delivery, and product returns are critically important conditions for acquiring repeat visitors. Hence, in addition to usefulness and ease of use as in TAM, trust should be a fundamental determinants of user acceptance in the context of internet shopping. Third, the user's ability on using an Internet shopping site played a moderating role. For users with low ability, ease of use was found to be a more important factors in deciding to reuse the shopping mall, whereas usefulness and trust had more effects on users with high ability. Applying the EML theory to these findings, we can suggest that experienced and knowledgeable ISM users tend to elaborate on such usefulness aspects as efficient and effective shopping performance and trust factors as ability, benevolence, integrity, and predictability of a shopping site before they become repeat visitors of the site. In contrast, novice users tend to rely on the low elaborating features, such as the perceived ease of use. The existence of moderating effects suggests the fact that different individuals evaluate an ISM from different perspectives. The expert users are more interested in the outcome of the visit(usefulness) and trustworthiness(trust) than those novice visitors. The latter evaluate the ISM in a more superficial manner focusing on the novelty of the site and on other instrumental beliefs(ease of use). This is consistent with the insights proposed by the Heuristic-Systematic model. According to the Heuristic-Systematic model. a users act on the principle of minimum effort. Thus, the user considers an ISM heuristically, focusing on those aspects that are easy to process and evaluate(ease of use). When the user has sufficient experience and skills, the user will change to systematic processing, where they will evaluate more complex aspects of the site(its usefulness and trustworthiness). This implies that an ISM has to provide a minimum level of ease of use to make it possible for a user to evaluate its usefulness and trustworthiness. Ease of use is a necessary but not sufficient condition for the acceptance and use of an ISM. Overall, the empirical results generally support the proposed model and identify the moderating effect of the effects of user ability. More detailed interpretations and implications of the findings are discussed. The limitations of this study are also discussed to provide directions for future research.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.