• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.145-154
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• 2003

Business environment is changing rapidly because of the introduction of the newest Technologies development and the newest management skills. With the development of Information Technology (IT) and the rapid growth of Internet based business, there have been great improvements of business processes and total costs of many firms. Many firms realize that they have to change their organizational structure and managerial skills in order to carry on their corporate goals(growth and development) according to business paradigm shift. The purpose of this dissertation is to watch how consumer product manufacturer(C corporation) could build effective SCM strategies under Electronic Commerce paradigm shift and how it can reform its organizational structure in order to perform its business goat. C corporation has been doing a groat role in logistics and distribution for the last 50 years with logistics know-how in domestic market, however there were many problems such as lack of shared information, demand Paradox, order batch, stock shortage and duplicated processes among vendors and chain members. Most of problems were based on lack of shared information and old business processes.

• The Journal of Information Technology
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• v.7 no.1
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• pp.43-56
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• 2004

The purpose of this paper is to study the send and receive of the message in the TEDI System. The TEDI System replaces a series of trade documents with electronic date, and it realizes secure and reliable transactions of data among parties by means of open networks, such as the Internet. The TEDI system is composed of Web browsers, TC Serves, a RSP Server, and Certification Servers. TEDI has development the system and legal frame work. Exporters, importers, carriers, banks insurance and companies those who engage in the trade releated business have tested TEDI system and evaluated the legal frame work from the practical point of view. TEDI is now refining the system and preparing for the service. A fundamental feature of the TEDI System is the attribution to participants of data messages through public key certificates issued by certification authorities that allow for verification of digital signatures. Access to servers maintained by such certification authorities also takes place through the internet. In principle, certificates used by any reputable certification authority may be employed as long as they are compatible with X.509 V3.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.103-115
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• 2017

Globally, frequency and scale of natural disasters are growing, also the damage is increasing. In view of the damage by natural disasters for several years, it is true that Korea is not free from such damages. In this paper, we propose a process to efficiently manage recovery resources in case of disaster damage. We utilize the IoT technology to detect the resource status in real time, and configure the process so that the state and movement of the recovery resource can be grasped in real time through the resource activity recognition module. In addition, we designed the database that is necessary to actualize it, and developed and experimented resource activity recognition module using smart-phone sensors. This will contribute to building a quick and efficient disaster response system.

• Journal of Internet Computing and Services
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• v.17 no.1
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• pp.109-118
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• 2016

As Internet technology further develops, a social networking service (SNS) also develops. But most studies on SNS are not appropriate for business purposes since they mainly focus on personal characteristics. Unlike previous studies, however, this study tries to understand the effect of SNS on performance in the perspective of business. As the result of analysis, SNSE(Social Networking Service Engagement) appears to have positive effect on TMC(Transactive Memory Capability) and PER(Performance), and TMC also seems to affect PER. On the assumption that there should be some parameters between SNSE and PER that earlier studies did not consider, this study has proved that a new way of memories, or TMC, forms the bridge between SNS and PER. It also found out that the time spent on SNS is positively controlled when SNSE affects TMC. These results are different from those of the previous studies arguing that SNS has nothing to do with PER.

• The Journal of Society for e-Business Studies
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• v.19 no.1
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• pp.15-42
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• 2014

Cloud storage service has the potential to be a core infrastructure for the future mobile and Internet service; thus related service providers have been investing in it and trying to attract as many users as possible. In addition, those need to find out what motivates the users to keep using their service not only to attract new customers but also to secure their subscribers. Therefore, this study will examine its relationship with user's motivation based on the extended TAM model with external variables for objective research about continuous use of cloud storage service. As a result, it was found that personal innovativeness, self efficacy, functional attributes, and psychological switching cost influence the continuous use of cloud storage service. Also, it is expected they can guide service providers to the right track when setting up their business strategy in the future.

• Journal of Korea Multimedia Society
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• v.7 no.1
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• pp.132-144
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• 2004

With the rapid development of internet technology, the number of internet users and the amount of multimedia information on the internet is ever increasing. Recently, the web sites, such as e-business sites and shopping mall sites, deal with lots of image information. As a result, it is required to support content- based image retrieval efficiently on such image data. This paper proposes an intelligent image retrieval system, which adopts XML, technology. To support object-based col)tent retrieval on product catalog images containing multiple objects, we describe a multi -level metadata structure which represents the local features, global features, and semantics of image data. To enable semantic-based and content-based retrieval on such image data, we design a XML-Schema for the proposed metadata and show how to represent such metadata using XML- documents. We also describe how to automatically transform the retrieval results into the forms suitable for the various user environments, such as web browser or mobile browser, using XSLT The proposed scheme can be easily implemented on any commercial platforms supporting XML technology. It can be utilized to enable efficient image metadata sharing between systems, and it will contribute in improving the retrieval correctness and the user's satisfaction on content-based e-catalog image retrieval.

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2003.10a
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• pp.108.2-109
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• 2003

The Gyeonggi-do Agricultural Research and Extension Services has developed a web-site (www.epilove.com) in collaboration with EPINET to provide information on agricultural weather and rice disease and insect pest management in Gyeonggi-do. Weather information includes near real-time weather data monitored by automated weather stations (AWS) installed at rice paddy fields of 11 Agricultural Technology Centers (ATC) in Gyeonggi-do, and weekly weather forecast by Korea Meteorological Administration (KMA). Map images of hourly air temperature and rainfall are also generated at 309m x 309m resolution using hourly data obtained from AWS installed at 191 locations by KMA. Based on near real-time weather data from 11 ATC, hourly infection risks of rice blast, sheath blight, and bacterial grain rot for individual districts are estimated by disease forecasting models, BLAST, SHBLIGHT, and GRAINROT. Users can diagnose various diseases and insects of rice and find their information in detail by browsing thumbnail images of them. A database on agrochemicals is linked to the system for disease and insect diagnosis to help users search for appropriate agrochemicals to control diseases and insect pests.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.19-45
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• 2005

Collaborative filtering is one of the most common methods that e-commerce sites and Internet information services use to personalize recommendations. Collaborative filtering has the advantage of being able to use even sparse evaluation data to predict preference scores for new products. To date, however, no in-depth investigation has been conducted on how the data sparsity effect in customers' evaluation data affects collaborative filtering-based recommendation performance. In this study, we analyzed the sparsity effect and used a hybrid method based on customers' evaluations and purchases collected from an online bookstore. Results indicated that recommendation performance decreased monotonically as sparsity increased, and that performance was more sensitive to sparsity in evaluation data rather than in purchase data. Results also indicated that the hybrid use of two different types of data (customers' evaluations and purchases) helped to improve the recommendation performance when evaluation data were highly sparse.

• Asia pacific journal of information systems
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• v.18 no.4
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• pp.105-130
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• 2008

Consumers of e-learning market differ from those of other markets in that they are replaced in a specific time scale. For example, e-learning contents aimed at highschool senior students cannot be consumed by a specific consumer over the designated period of time. Hence e-learning service providers need to attract new groups of students every year. Due to lack of information on products designed for continuously emerging consumers, the consumers face difficulties in making rational decisions in a short time period. Increased uncertainty of product purchase leads customers to herding behaviors to obtain information of the product from others and imitate them. Taking into consideration of these features of e-learning market, this study will focus on the online herding behavior in purchasing e-learning contents. There is no definite concept for e-learning. However, it is being discussed in a wide range of perspectives from educational engineering to management to e-business etc. Based upon the existing studies, we identify two main view-points regarding e-learning. The first defines e-learning as a concept that includes existing terminologies, such as CBT (Computer Based Training), WBT (Web Based Training), and IBT (Internet Based Training). In this view, e-learning utilizes IT in order to support professors and a part of or entire education systems. In the second perspective, e-learning is defined as the usage of Internet technology to deliver diverse intelligence and achievement enhancing solutions. In other words, only the educations that are done through the Internet and network can be classified as e-learning. We take the second definition of e-learning for our working definition. The main goal of this study is to investigate what factors affect consumer intention to purchase e-learning contents and to identify the differential impact of the factors between consumers with purchase experience and those without the experience. To accomplish the goal of this study, it focuses on herding behavior and perceived usefulness as antecedents to behavioral intention. The proposed research model in the study extends the Technology Acceptance Model by adding herding behavior and usability to take into account the unique characteristics of e-learning content market and e-learning systems use, respectively. The current study also includes consumer experience with e-learning content purchase because the previous experience is believed to affect purchasing intention when consumers buy experience goods or services. Previous studies on e-learning did not consider the characteristics of e-learning contents market and the differential impact of consumer experience on the relationship between the antecedents and behavioral intention, which is the target of this study. This study employs a survey method to empirically test the proposed research model. A survey questionnaire was developed and distributed to 629 informants. 528 responses were collected, which consist of potential customer group (n = 133) and experienced customer group (n = 395). The data were analyzed using PLS method, a structural equation modeling method. Overall, both herding behavior and perceived usefulness influence consumer intention to purchase e-learning contents. In detail, in the case of potential customer group, herding behavior has stronger effect on purchase intention than does perceived usefulness. However, in the case of shopping-experienced customer group, perceived usefulness has stronger effect than does herding behavior. In sum, the results of the analysis show that with regard to purchasing experience, perceived usefulness and herding behavior had differential effects upon the purchase of e-learning contents. As a follow-up analysis, the interaction effects of the number of purchase transaction and herding behavior/perceived usefulness on purchase intention were investigated. The results show that there are no interaction effects. This study contributes to the literature in a couple of ways. From a theoretical perspective, this study examined and showed evidence that the characteristics of e-learning market such as continuous renewal of consumers and thus high uncertainty and individual experiences are important factors to be considered when the purchase intention of e-learning content is studied. This study can be used as a basis for future studies on e-learning success. From a practical perspective, this study provides several important implications on what types of marketing strategies e-learning companies need to build. The bottom lines of these strategies include target group attraction, word-of-mouth management, enhancement of web site usability quality, etc. The limitations of this study are also discussed for future studies.