• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.163-178
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• 2014

Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Asia Marketing Journal
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• v.12 no.2
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• pp.111-133
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• 2010

Marketing financial services used to be easier. Today, the competition in financial services is fierce. Not only has the competition become more intense, financial services have also changed structurally. In an environment with various customer needs and severe competitions, the marketing in financial services industry is getting more difficult and more important than before. However, there are still not enough studies on financial services marketing in Korea whereas lots of research papers have been published frequently in some international journals. The purpose of this paper is (1)to review the literature on financial services marketing, (2)to investigate current marketing activities based on in-depth interview with financial marketing managers in Korea, and (3)to suggest some implications for future research on the financial services marketing. Financial products are not consumer products. In fact, they are not products at all in the way product marketing is usually described. Nor are they altogether like services. The financial industry operates in a unique way, and its marketing tasks are correspondingly complex. However, the literature review shows that there has been a lack of basic studies which dealt with inherent characteristics of financial services marketing compared to the research on marketing in other industries. Many studies in domestic marketing journals have so far focused only on the general customer behaviors and the special issues in some financial industries. However, for more effective financial services marketing, we have to answer following questions. Is there any difference between financial service marketing and consumer packaged goods marketing? What are the differences between the financial services marketing and other services marketing such as education and health services? Are there different ways of marketing among banks, securities firms, insurance firms, and credit card companies? In other words, we need more detailed research as well as basic studies about the financial services marketing. For example, we need concrete definitions of financial services marketing, bank marketing, securities firm marketing, and etc. It is also required to compare the characteristics of each marketing within the financial services industry. The products sold in each market have different characteristics such as duration and degree of risk-taking. It means that there are sub-categories in financial services marketing. We have to consider them in the future research on the financial services marketing. It is also necessary to study customer decision making process in the financial markets. There have been little research on how customers search and process information, compare alternatives, make final decision, and repeat their choices. Because financial services have some unique characteristics, we need different understandings in the customer behaviors compared to the behaviors in other service markets. And also considering the rapid growth in financial markets and upcoming severe competition between domestic and global financial companies, it is time to start more systematic and detailed research on financial services marketing in Korea. In the second part of this paper, I analyzed the results of in-depth interview with 20 marketing managers of financial services companies in Korea. As a result, I found that the role of marketing departments in Korean financial companies are mainly focused on the short-term activities such as sales support, promotion, and CRM data analysis although the size and history of marketing departments to some extent show a sign of maturity. Most companies established official marketing departments before 2001. Average number of employees in a marketing department is about 58. However, marketing managers in eight companies(40% of the sample) still think that the purpose of marketing is only to support and manage general sales activities. It shows that some companies have sales-oriented concept rather than marketing-oriented concept. I also found three key words which marketing managers think importantly in financial services markets. They are (1)Trust in customer relationship, (2)Brand differentiation, and (3)Rapid response to customer needs. 50% of the sample support that "Trust" is the most important key word in the financial services marketing. It is interesting that 80% of banks and securities companies think that "Trust" is the most important thing, whereas managers in credit card companies consider "Rapid response to customer needs" as the most important key word in their market. In addition, there are different problems recognition of marketing managers depending on the types of financial industries they belong to. For example, in the case of banks and insurance companies, marketing managers consider "a lack of communication with other departments" as the most serious problem. On the other hand, in the case of securities firms, "a lack of utilization of customer data" is the most serious problem. These results imply that there are different important factors for the customer satisfaction depending on the types of financial industries, and managers have to consider them when marketing financial products in more effective ways. For example, It will be necessary for marketing managers to study different important factors which affect customer satisfaction, repeat purchase, degree of risk-taking, and possibility of cross-selling according to the types of financial industries. I also suggested six hypothetical propositions for the future research.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.59-77
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• 2012

This study focuses on predicting which firms will increase capital by issuing new stocks in the near future. Many stakeholders, including banks, credit rating agencies and investors, performs a variety of analyses for firms' growth, profitability, stability, activity, productivity, etc., and regularly report the firms' financial analysis indices. In the paper, we develop predictive models for rights issues using these financial analysis indices and data mining techniques. This study approaches to building the predictive models from the perspective of two different analyses. The first is the analysis period. We divide the analysis period into before and after the IMF financial crisis, and examine whether there is the difference between the two periods. The second is the prediction time. In order to predict when firms increase capital by issuing new stocks, the prediction time is categorized as one year, two years and three years later. Therefore Total six prediction models are developed and analyzed. In this paper, we employ the decision tree technique to build the prediction models for rights issues. The decision tree is the most widely used prediction method which builds decision trees to label or categorize cases into a set of known classes. In contrast to neural networks, logistic regression and SVM, decision tree techniques are well suited for high-dimensional applications and have strong explanation capabilities. There are well-known decision tree induction algorithms such as CHAID, CART, QUEST, C5.0, etc. Among them, we use C5.0 algorithm which is the most recently developed algorithm and yields performance better than other algorithms. We obtained data for the rights issue and financial analysis from TS2000 of Korea Listed Companies Association. A record of financial analysis data is consisted of 89 variables which include 9 growth indices, 30 profitability indices, 23 stability indices, 6 activity indices and 8 productivity indices. For the model building and test, we used 10,925 financial analysis data of total 658 listed firms. PASW Modeler 13 was used to build C5.0 decision trees for the six prediction models. Total 84 variables among financial analysis data are selected as the input variables of each model, and the rights issue status (issued or not issued) is defined as the output variable. To develop prediction models using C5.0 node (Node Options: Output type = Rule set, Use boosting = false, Cross-validate = false, Mode = Simple, Favor = Generality), we used 60% of data for model building and 40% of data for model test. The results of experimental analysis show that the prediction accuracies of data after the IMF financial crisis (59.04% to 60.43%) are about 10 percent higher than ones before IMF financial crisis (68.78% to 71.41%). These results indicate that since the IMF financial crisis, the reliability of financial analysis indices has increased and the firm intention of rights issue has been more obvious. The experiment results also show that the stability-related indices have a major impact on conducting rights issue in the case of short-term prediction. On the other hand, the long-term prediction of conducting rights issue is affected by financial analysis indices on profitability, stability, activity and productivity. All the prediction models include the industry code as one of significant variables. This means that companies in different types of industries show their different types of patterns for rights issue. We conclude that it is desirable for stakeholders to take into account stability-related indices and more various financial analysis indices for short-term prediction and long-term prediction, respectively. The current study has several limitations. First, we need to compare the differences in accuracy by using different data mining techniques such as neural networks, logistic regression and SVM. Second, we are required to develop and to evaluate new prediction models including variables which research in the theory of capital structure has mentioned about the relevance to rights issue.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.11-20
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• 2018

The Q&A board is widely used as a means of communicating service enquiries, and the need for efficient management of the enquiry system has risen because certain questions are being repeatedly and frequently registered. This study aims to construct a student-centered FAQ, centered on the unstructured data posted on the university homepage's Q&A board. We extracted major keywords from 690 postings registered in the recent 3 years, and conducted the semantic network analysis to find the relationship between the keywords and the centrality analysis in order to carry out network visualization. The most central keywords found through the analysis, in order of centrality, were application, curriculum, credit point, completion, graduation, approval, period, major, portal, department. Also, the major keywords were classified into 8 groups of course, register, student life, scholarship, library, dormitory, IT and commute. If the most frequent questions are organized into these areas to form the FAQ, based on the results above, it is expected to contribute to user convenience and the efficiency of administration by simplifying the service enquiry process for repeated questions, as well as enabling smooth two-way communication among the members of the university.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.4
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• pp.100-110
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• 2008

The purposes of the study were to analyze the effects of determinants and persuasive messages on the willingness-to-pay cultural & heritage assets' admission fees. Recently visitors have responded to a nationwide boycott of the fees within national parks due to feelings of disapproval and resentment. Data were collected through onsite surveys of 302 visitors in the Mt. Gyeryong National Park. Regression analysis and two-way ANOVA were employed to obtain the results. The results indicate that credit card payment was the most prominent predictor of willingness-to-pay at the .05 level. The second highest coefficient was obtained in the condition levying of admission fees and parking fees at the same time, providing temple interpretive services, followed by free days for everyone on special days each month. In addition, the most persuasive message was the descriptive content, which stated that fees were profoundly committed to the protection of the cultural heritage for future generations. As a result, it is effective to continually persuade visitors to use posters or reminders that stress the preservation of cultural assets at the entrance gate.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.64-72
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• 2009

AMR(Automatic Meter Reading), which means that it reads the meter of electricity, gas, or water, etc at a remote place automatically through wired or wireless communication, has been studied in terms of Power Line Communication method and Local Area Wireless Communication method, etc. In this paper, we designed and implemented JCA(Java Card for AMR) capable of AMR, which is based on java Card technology indispensable to the ubiquitous world. In this paper, JCA follows standard transactional procedures offered by power supply company and manages power usage log and billing data, and is designed in order to satisfy EMV multi-functional specifications. Because JCA is a multi-functional smart card capable of post-issuance applets as an open platform, it is installed into other applications of affiliated concerns as well as credit card and traffic card applications. Not only the proposed JCA is a low cost system, compared to other AMR systems, but is capable of paying rates in advance or later by applying authentication and security function of java Card. In addition the proposed JCA system can create value added services such as affiliated services with corporate alliance.

• Journal of Technologic Dentistry
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• v.31 no.4
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• pp.45-52
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• 2009

This study is analyzed to conduct better on-site practices with recognizing importance of the clinical practice of Dept. of dental technology and use it as a basic material in the clinical practice. Target people who are students studying dental technology in D college in Daegu were questioned by survey. Study results below 1. Average score of the survey about satisfaction of the operating method of clinical practice shows 3.26. In detail elements, 'credit assignment(10 credits)' is 3.65 as the highest score, 'execution period(vacation)' is 3.50, 'choice of the clinical practice organization' is 3.25, 'measures after practice' is 2.98 and 'pre-education' is 2.98 as the lowest score. 2. Through the real clinical practice, 'experience of new equipments and technology' is 3.64 as the highest score, 'choice of lecturer' is 3.61, 'guidance way' is 3.49, 'contents properness' is 3.44, 'environment of practice organization' is 3.36, 'evaluation way' is 3.35 and 'practical use of the evaluation material' is 3.18 as the lowest score. 3. The average score of survey about satisfaction after clinical practice of the participated students is 3.46 that is higher than both 'satisfaction about operating method(3.26)' about clinical practice of college and 'satisfaction about organization(3.44)' about environment of dental craft organizations and labs, guidance way of lecturer and evaluation. 4. In the improvement of distribution of the clinical practice evaluation, in the 'practice organization: college' viewpoint, '7:3' is 35.77% as the highest response, '6:4' is 25.20%, '8:2' is 22.76% and '4:6' is 16.26 in regular sequence. 5. In site evaluation reflection of clinical practice, 50% reflection is 32.93% as the highest percentage, 60% reflection is 26.83%, 20% reflection is 20.73% and 80% reflection is 6.10% in regular sequence. In attendance score, it shows percentage of reflecting 50% and 40% is 26.98%, students wanting to reflect 30% is 25.40%, reflecting 10% is 20.63% and no reflecting is 0%. In result of the analyzed data, clinical practice has to be studied more in considering that clinical practice is important point in education of Dept. of Dental Technology and also problems in college and on-site practice need improvements.

• KDI Journal of Economic Policy
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• v.13 no.4
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• pp.59-90
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• 1991

The purpose of this paper is to determine whether the rate schedule of the Korean income tax system embodies the theoretically desirable distribution of the tax burden by income classes. The paper follows the approach of Young (1990) who has estimated the utility function and calculated the magnitude of sacrifice, i.e., the tax burden. The main point of the study is to estimate the utility function. The estimation results may differ if different data sets are used. Therefore, this paper employs the effective as well as the nominal tax rate schedule. The findings derived in this paper are 1) that the effective rate schedule is more appropriate in estimating the utility function; 2) that the middle class has born the relatively heavier burden over time; 3) that the current income tax credit scheme curtails the tax burden on the middle class while intensifying the tax burden of the lower and upper income classes; 4) that reducing the amount of deduction moves the distribution of tax burdens by income classes closer to the theoretically desirable model; 5) that the rate schedule of the Korean income tax system, particularly in 1991, did not conform to the desired model as did the tax systems of developed countries such as the United States, Italy, Japan, and Germany.

• Journal of Distribution Science
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• v.14 no.12
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• pp.71-78
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• 2016

Purpose - This paper is for the Analysis on the Hindrance Factors and Activation Scheme by the Type of Distribution Channel in Direct transaction of Agricultural Products. As the distribution structure of agricultural products has become changable, farmers seem to use the type of direct distribution in order to enhance the receiving price. This study aims to explore the hindrance factors and income variation rate in direct transaction of agricultural produces, specifically focusing on the 167 farmers. Research design, data, and methodology - To ascertain the hindrance factors exactly by the type of distribution channel, the managements were classified by four subcategories, that is high sales percentage with shopping malls, SNS, shopping malls and SNS, and off-line direct transaction. Results - As a result of the hypothesis test, hinderance factors in online direct deal activation were found to be in the order of the difficulty in continuous content production, the difficulty in shopping mall operation and maintenance, and the difficulty in card commission problems, and in the order of the difficulties in continuous content production, the difficulty in continuous content production, the difficulty in shopping mall operation and maintenance, and the difficulty in branding for the SNS group. Thus, it can be seen that the difficulty in continuous content production, shopping mall operation and maintenance were found to be the biggest obstacles. In addition, hindering factors in online direct deal activation were found to be in the order of the difficulty in credit card settlement, the difficulty in publicity, and the difficulty in dealing with unsold goods. The group with high sales rate in shopping mall was found to be increased by 23.9% in the gross income compared to the previous year, the group with high SNS sales ratio increased by 56.5%, the group with direct offline transaction increased by 37.1%, among which the group with the highest increase rate of SNS sales ratio was found to be the highest from the rate of increase/decrease of the income, which was statistically significant. Conclusions - It can be suggested that government and local government may provide agricultural management with supporting plan which in turn can activate direct transaction in any possible ways.