• Journal of Science Education
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• v.47 no.3
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• pp.238-250
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• 2023

This study aims to explore the effect of an appropriate technology program related to water acquisition and purification on scientific attitudes and creative problem-solving skills in elementary school students. Thus, this study developed a learning program related to the appropriate technology composed of 8 sessions, and some were for exploring water acquisition-related scientific principles and the appropriated technology of Warka Tower, and the others were for conducting water purification-related inquiry experiments, such as Life Straw and Drinkable Book, and the last two sessions were for presenting practical tasks through creative ideas and designs and carrying out the relevant campaign activities. For research subjects, this study selected 51 students from two sixth-grade classes, and after modifying the scientific attitude questionnaire and the creative problem-solving skill questionnaire fit for the environment and situation, this study conducted a paired-sample t-test by applying both the questionnaires before and after this program. In addition, while looking into the correlation between scientific attitudes and creative problem-solving skills, based on the post-test results, this study examined relationships between sub-domains perceived by the students after this program was applied. The results can be summarized as below. Out of all the scientific attitudes, curiosity, openness, cooperation, and creativity showed statistically significant results with an increase in the average value when their overall averages of the pre-test were compared with those of the post-test. With creative problem-solving skills, the domain of mastering a specific area and the domain of divergent thinking showed statistically significant results. The correlation analysis results showed that cooperation out of the scientific attitudes had a significant correlation with all the domains of creative problem-solving skills, especially showing the highest correlation coefficient with such sub-domains as critical and logical thinking. All the four domains of creative problem-solving skills showed a number of significant correlations with the sub-domains of scientific attitudes. Through the research results above, this study has several implications on how and where to apply such appropriate technology-related topics in the future and various responses from students.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Korean Journal of Agricultural Science
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• v.6 no.1
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• pp.69-95
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• 1979

The study was conducted to search developmental process of plant protection science from review of forty-three hundreds literatures presented since 1900 in Korea and to forecast future statues of the science to be done. About 80 percent of literatures related to plant protection science such as plant pathology, applied entomology, weed science and agricultural pharmacology were collected from publications of agricultural and forestry reseach organizations attached to Office of Rural Development and Office of Forestry. The rest of literatures were mainly collected from Korean Journal of Plant Protection Society and small number of literatures were also collected from publications of the other journals of crop science and thesis collection of agricultural colleges. In Korea, research organizations of plant protection science are divided into two main groups such as exclusive agricultural research organizations and agricultural colleges. It is pointed out that the former contributions to plant protection science are very great compared to those of the latter since 1900. From periodical consideration of developmental process of the science since 1900, the history or the science are divided into three eras such as introduction and sprout of modern plant protection science during the first forty years, distress of the science during the following twenty years including the Second World War and the Korean War and rapid growth of the science after 1961. In spite of long time distress of the science during the Second World War and the Korean War, the researches on plant protection science in post-war have been done twice as many as pre-war. From consideration of the subject plants in researches of plant protection, it is shown that a great many researches on protection of rice plant have been done and occupy 37 percent of plant protection researches since 1900. And also researches on protection of fruit-trees and cash-crops are not so many as those of rice plant but have been done in noticeable numbers. In fact, researches on protection of fruit-trees and cashcrops were the most important subjects of plant protection researches in pre-war while those of rice plant were the most important subjects after 1930, particulary in post-war. From consideration of contents of plant protection researches, it is said that more fundamental researches than applied ones such as practical control methods of diseases, insect pests and weeds were done in pre-war while more applied researches than fundamental ones were done in post-war, Among applied researches, those of chemical control were the most important subjects. Researches on disease and insect-pest resistance have been done in both pre-war and post-war while researches on forecasting of disease and insect-pest and race of plant pathogens have been done in post-war. And also researches on weed control mainly have been done after 1960. Researches on agricultural chemicals for control of diseases, insect pests and weeds still belong to a new field which must be expected in future, and there is nothing to notice with the exception of practical application of agricultural chemicals introduced from foreign countries. Some of important researches on diseases and insect pests were discussed in relation to developmental process of plant protection science in Korea since 1900. In future, researches on plant protection will be develop to the direction supporting importance of integrated control for plant protection. Therefore, it is pointed out that security of highly educated and trained scientists with enlargement of reseach fields of plant protection science are necessary and role of agricultural colleges for future development of the science must be emphasized.

• Journal of agricultural medicine and community health
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• v.28 no.2
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• pp.15-29
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• 2003

Objectives: This study was done to find out fatigue and self-reported physical symptoms of Vinylhouse farmers. The results of this study could be used as a basic data to develop health promotion program for Vinylhouse farmers who are suffering from fatigue and physical symptoms. Methods: The 166 respondents, who were working in Vinylhouse and were living in a remoted area where the primary health post located, were participated in this study. Thirty: 30 items of self-reported fatigue scale was used to evaluate the farmers fatigue level which made by Japanese industrial and hygenic association(1988). Twenty four: 24 items of index used by researcher for self-reported physical symptoms was from Lee In Bae's(1999) modified Index which was originated from Cornell Medical Index(1949). Another questionnaires used in this study were developed by researcher through related documents. Results: The results of this study were as follows; Fatigue scores were high in accordance with women(t=-2.212, p<0.05), worse recognized health state(F=20.610, p<.001), lack of sleeping hours(F=3.937, p<0.05), eat irregularly(t=-3.883, p<0.001), don't take a bath after application of chemical(t=-2.950, p<0.01), working time per a day(F=5.633, p<0.01) & working time per a day in Vinylhouse(F=5.247, p<0.01) were long. Subjective physical symptoms were high in accordance with women(t=-3.176, p<0.01), worse recognized health state(F=35.335, p<0.001), and low education(F=3.467, p<0.05). eat irregularly(t=-3.384, p<0.01), alcohol drinking(t=-2.389, p<0.05). When farmers don't take a bath after application of chemical show high(t=-3.188, p<0.01). As a result, the factors affecting to Vinylhouse worker's health were irregular diet habit, scarce exercise, lack of proper rest, symptoms oriented from Vinylhouse work in contaminated environment with high temperature and humidity. Conclusions: Based on this study, health promotion program is necessary for Vinylhouse workers. Also, the development of continuously practical strategy of healthy life style including exercise and comprehensive health promotion program considered the country's social and cultural background are needed.

• 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 Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Journal of Food Hygiene and Safety
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• v.13 no.4
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• pp.441-447
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• 1998

This study was performed to investigate the changes of amount of S. typhimurium during cooking processes using pork and japchae (a Korean food which is made from meat, vegetables and noodles), and to support a practical application to develop a hazard analysis critical control point (HACCP) model. The pork was purchased in a retail shop, cut ($0.5\;cm\;{\times}\;10\;cm\;{\times}\;10\;cm$, 25 g), tested for Salmonella contamination (results: negative), inoculated with S. typhimurium ($10^{7}\;CFU/g$), then treated in various conditions related to cooking. Mter thawing for 24 hours in various conditions, the number of S. typhimurium was increased to $10^{10}\;CFU/g$ at a refrigerated temperature ($4~10^{\circ}C$), and to $10^{21}\;CFU/g$ at room temperature ($22~29^{\circ}C$). Mter thawing in a microwave oven for 40 seconds, the number of S. typhimurium increased to $10^{8}\;CFU/g$. During the thawing period, the number of S. typhimurium increased over time. At the refrigerated temperature, the number of the bacteria was $10^{10}\;CFU/g$ after 24 hours, $10^{13}\;CFU/g$ after 48 hours, and $10^{20}\;CFU/g$ after 72 hours. At room temperature the number of bacteria reached $10^{11}\;CFU/g$ in 2 hours, $10^{15}\;CFU/g$ in 4 hours, $10^{16}\;CFU/g$ in 8 hours, $10^{18}\;CFU/g$ in 12 hours, and $10^{21}\;CFU/g$ in 24 hours. Mter cooking in a frying pan (150{\pm}7^{\circ}C$) for 3 minutes, the bacterial count was $10^{16}\;CFU/g$. After cooking in hot water for 20 minutes, the bacterial count was $10^{7}\;CFU/g\;at\;60^{\circ}C,\;10^{6}\;CFU/g\;at\;63^{\circ}C,\;and\;10^{4}\;CFU/g\;at\;65^{\circ}C$. The fried pork was mixed with cooked vegetables, noodles, sesame oil, sesame seeds, and seasonings to make Korean japchae. This process took $10{\pm}2$ minutes. The bacterial count in the japchae increased to $10^{7}\;CFU/g$ from the count of $10^{6}\;CFU/g$ of the fried pork before it was mixed with the other ingredients. These results indicate that the amount of S. typhimurium is effected by various different cooking processes. This study can suggest that pork should be cooked in water at over $65^{\circ}C$ for 20 minutes in order to prevent food poisoning, if the pork is contaminated with S. typhimurium. The presence of S. typhimurium in the raw pork is identified in an HA for japchae, and the primary CCP for japchae is inadequate cooking (cooking method and time/temperature). We need to standardize time-temperature-size and amount of pork in cooking japchae, because pork is usually cooked in ordinary frying pans when we make this food.

• The Korean Journal of Air & Space Law and Policy
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• v.29 no.1
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• pp.127-160
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• 2014

The UN COPUOS was established in 1959 as a permanent committee of the UN General Assembly with the aims to promote international cooperation in peaceful uses of outer space, to formulate space-related programmes within the UN, to encourage research and dissemination of information on space, and to study legal problems arising from the outer space activities. Its members have been enlarged from 24 members in 1959 to 76 in 2014. The Legal Subcommittee, which has been established under COPUOS in 1962 to deal with legal problems associated with space activities, through its first three decades of work has set up a framework of international space law: the five treaties and agreements - namely the Outer Space Treaty, Rescue Agreement, Liability Convention, Registration Convention, Moon Agreement - and the five declarations and legal principles. However, some sceptical views on this legal framework has been expressed, concerning the applicability of existing international space law to practical issues and new kinds of emerging space activities. UNISPACE III, which took place in 1999, served as a momentum to revitalize the discussions of the legal issues faced by the international community in outer space activities. The agenda of the Legal Subcommittee is currently structured into three categories: regular items, single issue/items, and items considered under a multi-year workplan. The regular items, which deal with basic legal issues, include definition and delimitation of outer space, status and application of the five UN treaties on outer space, and national legislation relevant to the peaceful exploration and use of outer space. The single issues/items, which are decided upon the preceding year, are discussed only for one year in the plenary unless renewed. They include items related to the use of nuclear power sources in outer space and to the space debris mitigation. The agenda items considered under a multi-year work plan are discussed in working group. Items under this category deal with non-legally binding UN instruments on outer space and international mechanism for cooperation. In recent years, the Subcommittee has made some progress on agenda items related to nuclear power sources, space debris, and international cooperation by means of establishing non-legally binding instruments, or soft law. The Republic of Korea became the member state of COPUOS in 2001, after rotating seats every two years with Cuba and Peru since 1994. Korea's joining of COPUOS seems to be late, in considering that some countries with hardly any space activity, such Chad, Sierra Leone, Kenya, Lebanon, Cameroon, joined COPUOS as early as 1960s and 1970s and contributed to the drafting of the aforementioned treaties, declarations, and legal principles. Given the difficulties to conclude a treaty and un urgency to regulate newly emerging space activities, Legal Subcommittee now focuses its effort on developing soft law such as resolutions and guideline to be adopted by UN General Assembly. In order to have its own practices reflected in the international practices, one of the constituent elements of international customary law, Korea should analyse its technical capability, policy, and law related to outer space activities and participate actively in the formation process of the soft law.

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

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

• 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.