• Asia pacific journal of information systems
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• v.18 no.1
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• pp.145-162
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• 2008

One of the big concerns in e-society is privacy issue. In special, in developing robust ubiquitous smart space and corresponding services, user profile and preference are collected by the service providers. Privacy issue would be more critical in context-aware services simply because most of the context data themselves are private information: user's current location, current schedule, friends nearby and even her/his health data. To realize the potential of ubiquitous smart space, the systems embedded in the space should corporate personal privacy preferences. When the users invoke a set of services, they are asked to allow the service providers or smart space to make use of personal information which is related to privacy concerns. For this reason, the users unhappily provide the personal information or even deny to get served. On the other side, service provider needs personal information as rich as possible with minimal personal information to discern royal and trustworthy customers and those who are not. It would be desirable to enlarge the allowable personal information complying with the service provider's request, whereas minimizing service provider's requiring personal information which is not allowed to be submitted and user's submitting information which is of no value to the service provider. In special, if any personal information required by the service provider is not allowed, service will not be provided to the user. P3P (Platform for Privacy Preferences) has been regarded as one of the promising alternatives to preserve the personal information in the course of electronic transactions. However, P3P mainly focuses on preserving the buyers' personal information. From time to time, the service provider's business data should be protected from the unintended usage from the buyers. Moreover, even though the user's privacy preference could depend on the context happened to the user, legacy P3P does not handle the contextual change of privacy preferences. Hence, the purpose of this paper is to propose a mutual P3P-based negotiation mechanism. To do so, service provider's privacy concern is considered as well as the users'. User's privacy policy on the service provider's information also should be informed to the service providers before the service begins. Second, privacy policy is contextually designed according to the user's current context because the nomadic user's privacy concern structure may be altered contextually. Hence, the methodology includes mutual privacy policy and personalization. Overall framework of the mechanism and new code of ethics is described in section 2. Pervasive platform for mutual P3P considers user type and context field, which involves current activity, location, social context, objects nearby and physical environments. Our mutual P3P includes the privacy preference not only for the buyers but also the sellers, that is, service providers. Negotiation methodology for mutual P3P is proposed in section 3. Based on the fact that privacy concern occurs when there are needs for information access and at the same time those for information hiding. Our mechanism was implemented based on an actual shopping mall to increase the feasibility of the idea proposed in this paper. A shopping service is assumed as a context-aware service, and data groups for the service are enumerated. The privacy policy for each data group is represented as APPEL format. To examine the performance of the example service, in section 4, simulation approach is adopted in this paper. For the simulation, five data elements are considered: $\cdot$ UserID $\cdot$ User preference $\cdot$ Phone number $\cdot$ Home address $\cdot$ Product information $\cdot$ Service profile. For the negotiation, reputation is selected as a strategic value. Then the following cases are compared: $\cdot$ Legacy P3P is considered $\cdot$ Mutual P3P is considered without strategic value $\cdot$ Mutual P3P is considered with strategic value. The simulation results show that mutual P3P outperforms legacy P3P. Moreover, we could conclude that when mutual P3P is considered with strategic value, performance was better than that of mutual P3P is considered without strategic value in terms of service safety.

• Journal of Engineering Education Research
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• v.9 no.4
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• pp.28-45
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• 2006

As society has changed to being more knowledge-based, it is indispensable that Internet usage is incorporated into education. Therefore, the e-learning system is being developed in order to provide a proper environment. However, many LCMS that were developed, currently are not based on SCORM, the world e-learning standard, nor KEM, the Korea Educational Metadata of Korea Education & Research Information Service(KERIS), and hence, it is difficult to share learning contents developed from such varied environments. National Science Museum, a non-educational institution, also provides the educational science exhibits in reality or in cyber space, which cannot be produced by elementary schools, and secondary schools. Consequently, new systems are necessary, whose modules should be divided into four, for example, 'teachers', 'learners', 'managers', and 'instructors', and be associated with each other so that they are able to integrate and manage such systems, and be used in school education as well. Therefore, in this study, more advanced LMS and LCMS, which are the web-portal sites used for a cyber science class at the National Science Museum, were designed and established. These sites were surely based on the KEM, and the SCORM.

• 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.

• Asia pacific journal of information systems
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• v.22 no.4
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• pp.125-149
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• 2012

As the smart phone is propagating rapidly, the importance of mobile advertisement has also grown. One of the main characteristics of the Internet and smart phone advertising is that they can deliver personalized advertisements to each customer. The smart phone enables the identification of additional personalized information such as the customer's location and the accessibility to the site at any place any time. As the Internet platform becomes richer, firms that offer the ad services via the wired PC Internet and wireless smart phone are seeking various types of personalized ads. However, their service platform and Information and Communication Technology (ICT) platform should be suitable to the characteristics of personalized ads. This research explores various types of personalized ad methods and evaluates their adequacy encompassing four types of ad service platforms (such as search portal, news portal, e-mall servers, and SNS) and two types of ICT platforms (PC Internet and smart phone). To this end, we classified the personalized ads into seven types: three basic types and four composite types. The basic types of ad methods are identified by considering the current activity that the customer is engaged, the individual profile and log history, and the customer's current location or planning location. Four composite types of ad methods are constructed as the combination of these basic types. For those types of ad methods, we evaluate whether each ad method adequately maps with four types of ad service platforms and two types of ICT platforms. We proposed a metric of evaluation and demonstrated the concept with illustrative numbers. Specifically, we analyze and compare personalized ad methods in three ways. Firstly, the possibility of implementing a personalized ad method on the platform is analyzed to confirm the degree of suitability. Secondly, the value of personalized ad method is analyzed based on the customer accessibility. Lastly, expected effectiveness for each personalized ad method is computed by multiplying the possibility and the value. Through this kind of analysis, the ad service providers as well as advertising companies can evaluate what kinds of personalized ad methods and platforms are possible and suitable to maximize their ad effectiveness on the Internet and smart phone platforms.

• The Journal of Society for e-Business Studies
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• v.15 no.3
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• pp.99-129
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• 2010

The objective of this research is to identify the factors which influence users' intention to use mobile Internet. There are lots of researches based on Technology Acceptance Model trying to identify the factors which have influence on accepting mobile Internet and its related services. These researches, however, have some limitation in the sense that they focus only on the features of mobile Internet itself while users make overall decision after the comparison of a new service channel with existing service channels in many directions. Therefore, we are going to analyze the impact of users' perception on the difference between mobile and stationary Internet toward their intention to use mobile Internet. We identified the features like ubiquitous availability, context awareness, compatibility, friendliness, and economic value from literature review and developed a structural model about the impact of users' perception on the differences of these features between mobile and stationary Internet toward their intention to use mobile Internet through mediate variables such as perceived ease of use, perceived playfulness, and perceived usefulness. After that, we conducted an experimental analysis for the model, and addressed a solution to rev up the usage of mobile Internet based on the results of the analysis.

• Journal of Korean Library and Information Science Society
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• v.55 no.1
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• pp.193-214
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• 2024

This study aimed to propose a method for collecting and applying media platform based materials at the National Library of Korea. Firstly, we analyzed the current status and limitations of data collection based on domestic media platforms, including the National Library of Korea. Secondly, a literature review method was used to investigate the current status and types of digital content based on media platforms. Thirdly, we identified the types of materials based on media platforms that are not currently included in the National Central Library's online material collection guidelines through the examination of cases from major overseas libraries. Fourthly, after reviewing technical and legal elements such as the definition of collection targets and scope for each new media, and collection methods, we established collection criteria. Fifthly, based on the research results, the policies proposed in this study are as follows: 1) there is a need to establish a clear legal basis for the collection of media platform based materials; 2) the development and presentation of collection guidelines for media platform based materials is necessary; 3) the development of collection tools and infrastructure for media platform based materials is required; 4) for the collection of media platform based materials, it is necessary to obtain permission for collection from targeted social media organizations, and to cooperate in linkage with organizations that produce and service extended reality content; 5) for the service activation of media platform based materials, it is necessary to improve accessibility for the usage activation of these materials, to enhance the content extensibility and ease of use of the e-deposit system including extended reality content, and to advance and construct spaces for reproducing extended reality content.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.105-135
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• 2022

As COVID-19 has led to a surge in e-commerce Buy Now Pay Later(BNPL) has become preferred choice among millennials. In Korea Coupang followed by Naver Pay offers a deferred payment, aiming to create customer lock-in effect, save credit card processing fee and lay the groundwork for entering into new financial services. However the literature related to the influential factors of customers' usage intention toward a deferred payment is scarce. For the study, a multi-group analysis was carried out to find differences between Naver shopping and Coupang. The results revealed that the important factors that affect a deferred payment adoption were compatibility, impulsive buying tendency in Naver shopping, whereas compatibility, relative advantage, additional value in Coupang(listed in order of most important). In addition, impulsive buying tendency had a positive effect on adoption intention in Naver shopping and on perceived risk in Coupang. The results imply that Naver shopping need to focus on managing delinquency while Coupang should provide sufficient information on how late fees and credit rating downgrade work and try not to make a deferred payment option stand out. In order to increase adoption rate it is recommendable to narrow down target segment of a deferred payment and expand it to a specialized vertical such as travel.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.113-123
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• 2023

This paper introduces the Cherry system, a user-independent blockchain donation system. This is a procedure that is delivered to the beneficiary's bank account through a virtual account when a donor makes a donation, so there is no difference from the existing donation delivery method from the user's point of view However, within the blockchain, Cherry Points, a virtual currency based on the user ID, are issued and delivered to the beneficiary, while all transactions and the beneficiary's usage history are managed on the blockchain. By adopting this method, there was an improvement in blockchain performance, with transaction processing exceeding 1,000 TPS in typical transaction condition and service completion within 21.3 seconds. By applying the automatic influence control algorithm to this system, the influence according to stake, which is an individual donation, is greatly reduced to 0.3 after 2 months, thereby concentrating influence could be controlled automatically. In addition, it was designed to enable micro tracking by adding a tracking function by timestamp to the donation ledger for each individual ID, which greatly improved the transparency in the use of donations. From a service perspective, existing blockchain donation systems were handled as limited donation delivery methods. Since it is a direct service in a user-independent method, convenience has been greatly improved by delivering donations in various forms.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.109-120
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• 2018

The smartphone is the communication device that is the most personal to the user, and it keeps a lot of information related to the user and makes information communication with other devices. With these characteristics, forensics on smartphones are one of the most basic methods of investigation in criminal investigations, and have actually contributed to the settlement of the case by providing many clues. However, recently, it is designed to encrypt data stored as a social issue related to the protection of user's personal information, or to delete deleted data or to delete log data together. So, any solutions? In this paper, I try to find the answer from cloud data stored by smartphone user account. Cloud forensics should approach complementary relationships rather than smartphone forensics. There are a lot of data stored in the cloud that can be meaningfully used in the investigation. Online activity information of users, such as Internet usage, YouTube view, and contents purchase information, cloud service such as e-mail, cloud drive, and location information are the most representative data. These data can be unvaluable, but here are some important clues in various types of criminal investigations. In this paper, I propose a method to extract data from the google cloud so that the data can be used for investigation, and to utilize the extracted data for investigation. And it explains the role of the extracted artifacts in the actual investigation business through virtual cases and proves its value.