• Journal of the Korea Computer Industry Society
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• v.2 no.8
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• pp.1109-1116
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• 2001

This paper describes a mechanism and its aspects for monitoring user actions and behaviors on the web operated under the layered architecture that utilizes intelligent agents, and by which personalized information services, for instance one-to-one marketing, is easily facilitated and developed. Intelligent agent is one of techniques which enables to automate the whole process for providing personalized services that includes monitoring, logging a user actions and analyzing behaviors based on his or her profiles, and then selecting, organizing customizable contents which are at last delivered to the users browser or mail box also by intelligent agents. Monitoring technologies can utilize to help better construct the process in providing personalized services in that those services require intelligence in operating. As a result, implementing effective personalized services, however, depends on how well to define various users interests and needs, and how correctly to detect and log the actions when hey are done by users.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.2
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• pp.206-218
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• 2002

In this paper, we design and implement a system that presents a method for selecting and providing personalized services independently without unifying the existing system platform with shopping malls joined in the hub site. This system provides a mechanism for gathering information left behind by many clients visiting Web sites for analysis of customers property, vector model for selecting personalized services, and mechanism for providing them to customers who visited in a shopping mall joined to the hub site. In a position of shopping mall site, this kind of personalization system can provide target advertisement, point marketing, and point share service etc. without changing existing shopping mall's environment through wrapper web server. Hub site customers can get personalized services from many shopping mall sites with only once registration for the hub site.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.376-390
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• 2009

The objective of this study is to examine the factors affecting adolescents' intention to buy e-Learning web site, expecially focuses on the moderating effect of adolescents's conformity. The main results are as follows. First, teacher's ability, personalized service, easy for service search, interaction between students, service revival for joining e-Learning sites affect intention to buy e-Learning web site through perceptual usefulness, except for entertainment. Second, perceptual usefulness has positive effect on intention to buy. Third, According to conformity, personalized service has different effect on perceptual usefulness. The result shows higher in high conformity group than low conformity group. It means e-Learning companies should focus on reference group or special group to effect their marketing strategy on adolescents. Lately, preceded studies investigated using SERVQUAL or SERVERF which were suit to offline. But, this study found e-Learning factors which are suitable to online. So, the factors and the results are more useful to e-Learning companies.

• Journal of Digital Contents Society
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• v.19 no.3
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• pp.513-519
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• 2018

The objective of this study was to examine the trends on social network services. The abstracts of 308 articles were extracted from web of science database published between 1994 and 2016. Time series analysis and topic modeling of text mining were implemented. The topic modeling results showed that the research topics were mainly 20 topics: trust, support, satisfaction model, organization governance, mobile system, internet marketing, college student effect, opinion diffusion, customer, information privacy, health care, web collaboration, method, learning effectiveness, knowledge, individual theory, child support, algorithm, media participation, and context system. The time series regression results indicated that trust, support satisfaction model, and remains of the topics were hot topics. This study also provided suggestions for future research.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.2
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• pp.97-116
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• 2004

Recently, e portion of on-line stock brokerage has been rapidly increased to be more than 50%, on the basis of contracted money. The usage of wCTS(Web Based Cyber Trading Systems) has now got into the steady state over the initial diffusion stage, which means wCTS has got more-than-half customer base in on-line service. Therefore, brokerage service providers have their competitive strategic focus on customer retention through the enhancement of customer loyalty. This study provides framework and survey results on explanation of wCTS user's loyalty, what and how factors affect wCTS user's loyalty. We adopt the results of early studies on information technology acceptance and diffusion such as TAM(Technology Acceptance Model) and IDT(Innovation Diffusion Theory). We also referred loyalty theory of marketing area and studios on CTS usage. We categorized explanation factors as three groups characteristics of users, characteristics of system, social environment. And we assumed that these three factors could affect the loyalty through two parameters : customer satisfaction and trust to the system. This study firstly shows that the ease of use and usefulness, the major factors of TAM. can also be applied to the loyalty of wCTS with resulting that the usefulness is more important than the ease of use In wCTS. Secondly, it shows that the innovative and risk-sensitive user has the lower degree of loyalty. Thirdly, it shows that the satisfaction and trust impact the loyalty simultaneously, the trust particularly impacts more strongly than the loyalty, due to the characteristics of monetary transaction in wCTS. This study provides meaningful results to the other on-line EC service fields as a first empirical research regarding the loyalty to wCTS which is a typical on-line EC service.

• Journal of Digital Convergence
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• v.13 no.9
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• pp.115-128
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• 2015

As generation of Web 2.0 comes in, enormous information of corporation from various platform are being produced. However, corporations should understand features of each platform and appropriate strategies in order to attract the public in the midst of such flood of information. Numerous studies have been conducted regarding SNS which has grown rapidly in recent but a study relating a specific medium is relatively in short. So this study analyzed how information of Instagram bulletin board is accepted in perspective of consumer in Korean and America, We examined the relationship between intention of acceptance and Word Of Mouth effect through meditating effect of information usefulness. To answer the research question, we conducted online survey with Korean and USA college students. The result showed that usefulness of the information was shown to the major intermediary variable between the information characteristics of bulletin board and the intention of acceptance intention and Word Of Mouth(WOM).

• Journal of Digital Convergence
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• v.17 no.11
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• pp.201-206
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• 2019

While many users searched for insurance information online, there were not many cases of contents recommendation researches on insurance companies' websites. Therefore, this study proposed a page recommendation system with high possibility of preference to users by utilizing page visit history of insurance companies' websites. Data was collected by using client-side storage that occurs when using a web browser. Collaborative filtering was applied to research as a recommendation technique. As a result of experiment, we showed good performance in item-based collaborative (IBCF) based on Jaccard index using binary data which means visit or not. In the future, it will be possible to implement a content recommendation system that matches the marketing strategy when used in a company by studying recommendation technology that weights items.

• Journal of the Korea Fashion and Costume Design Association
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• v.26 no.2
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• pp.57-72
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• 2024

Currently, Korea is on the verge of entering into an ultra-aged society and the associated market size is growing. In this regard, customer-centered design that understands the consumer needs of the new silver generation, which is emerging as a new consumer group, and reflects them in products is the key to the success of the high-value-added fashion industry. Therefore, this study reviewed the changes in physical, biological, social, and psychological characteristics of the new silver generation, through a review of related books and previous studies, and secured the direction for clothing product development for the new silver generation. The literature review was supplemented by group interviews to accurately identify the needs of silver consumers. In addition, the study conducted case analysis through web searches of fashion magazines, newspaper articles, brand web sites, and trend information sites to investigate the market trends of one-mile wear products that have emerged due to the COVID-19 pandemic, the characteristics of one-mile wear brands, and products for new silver women, including size specification analysis and sewing techniques that minimize skin irritation while reflecting the consumer's characteristics. Based on the results of this study, a competitive design and product development were proposed from an economic and industrial perspective that can enhance the product value and maximize the marketing effect by developing consumer-oriented one-mile comfort wear products with aesthetic, practical, functional, and economic values that satisfy the characteristics and needs of new silver women.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

• Journal of Global Scholars of Marketing Science
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• v.17 no.1
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• pp.101-122
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• 2007

Recently, as internet shopping mall users rapidly, a form of shopping changed from off line to on line. The rapid growth of customers and transaction volume through evolution of new media, internet, brings new problems to internet marketers. It is the most important task that how internet shopping mall operators obtain their customers trust and repeat buying. This empirical research investigates online shoppers for their trust dimensions for online retailers. The study aimed to determine whether e-trust antecedents(perceived reputation, perceived quality, perceived value) influence trust dimension and whether the multidimensional trust contributed differently to perceived risk and willingness to depend on e-retailers. Consequences of the research are as follows: First, it reveals that of reputation, web site quality of the internet shopping mall have influence upon trust dimension. Second, the higher level of trust consumers have, the higher level of willingness to depend and intent to revisit on the retailers they have. But level of perceive risk consumers have not influences on willingness to depend on the retailers. It is necessary for internet shopping mall to development its reputation and familiarity to obtain customer's trust. Accordingly, this research will be helping internet shopping mall insight for marketing strategies, constantly should study about action and mind of consumer.