• Journal of Information Technology Services
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• v.11 no.1
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• pp.93-107
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• 2012

Privacy-protective behavior can be classified into passive behavior and active behavior. Passive behavior includes refusal, misrepresentation, and removal, while word-of-mouth, complaint, and seeking for help belong to active behavior. Internet users in different countries may take different types of privacy-protective behavior because of cultural and social differences. This study analyzes the differences in Internet users' privacy-protective behavior between Korea and China. Korean Internet users take refusal, complaint, and seeking to protect their privacy information, while misrepresentation is not an option for Korean Internet users. Chinese Internet users take refusal, complaint, seeking, and misrepresentation to protect their privacy information. In Korea, passive behavior (refusal) is chosen more often than active behavior (complaint and seeking for help), while in China active behavior(complaint and seeking for help) is preferred to passive behavior (refusal and misrepresentation). The differences of privacy-protective behavior in the two countries may provide some implications for online companies, if they want to avoid the business risk due to privacy concerns and to take appropriate steps to deal with privacy-protective behavior by Internet users.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.2
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• pp.67-74
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• 2018

The purpose of this study was to analyze relationship between emotion and behavior with the color images of indoor space in hotels. The study methods evaluation experiments of emotion and behavior with computer graphic images. Study results are as follows: First, The color image according to the indoor space had a significant influence on the user's emotions. Lobby and restaurant had difference in pleasure arousal emotion by color image, and also guest room had difference in pleasure dominance emotion by color image. Second, The color image according to the indoor space had a significant influence on the user's behavior. Also lobby and restaurant had difference in movement hobby eating resting behavior by color image, and guest room had difference in hobby eating resting behavior by color image. Third, As a result of analyzing the effect of user's emotions on the behavior according to the indoor space: In the lobby, the more un-arousal increasing of users, the more hobby resting behavior increasing. And the more dominance increasing of users, the more movement hobby eating resting behavior increasing. In the restaurant, the more dominance increasing of users, the more movement eating hobby behavior increasing. The more arousal increasing of users, the more movement resting behavior increasing. The more un-arousal increasing of users, the more hobby eating behavior increasing. In the guest room, the more un-arousal dominance increasing of users, the more hobby eating resting behavior increasing. And also the more arousal increasing of users, the more movement behavior increasing.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.29-37
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• 2015

Nowadays, the user-centric application based web 2.0 has replaced the web 1.0. The users gain and provide information by interactive network applications. As a result, traditional approaches that only extract and analyze users' local document operating behavior and network browsing behavior to build the users' preference profile cannot fully reflect their interests. Therefore this paper proposed a preference analysis and indicating approach based on the users' communication information from MicroBlog, such as reading, forwarding and @ behavior, and using the improved PersonalRank method to analyze the importance of a user to other users in the network and based on the users' communication behavior to update the weight of the items in the user preference. Simulation result shows that our proposed method outperforms the ontology model, TREC model, and the category model in terms of 11SPR value.

• International journal of advanced smart convergence
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• v.6 no.3
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• pp.29-37
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• 2017

The current behavior recognition system don't match data formats between sensor data measured by user's sensor module or device. Therefore, it is necessary to support data processing, sharing and collaboration services between users and behavior recognition system in order to process sensor data of a large capacity, which is another formats. It is also necessary for real time interaction with users and behavior recognition system. To solve this problem, we propose fog cloud based behavior recognition system for human body sensor data processing. Fog cloud based behavior recognition system solve data standard formats in DbaaS (Database as a System) cloud by servicing fog cloud to solve heterogeneity of sensor data measured in user's sensor module or device. In addition, by placing fog cloud between users and cloud, proximity between users and servers is increased, allowing for real time interaction. Based on this, we propose behavior recognition system for user's behavior recognition and service to observers in collaborative environment. Based on the proposed system, it solves the problem of servers overload due to large sensor data and the inability of real time interaction due to non-proximity between users and servers. This shows the process of delivering behavior recognition services that are consistent and capable of real time interaction.

• Nutrition Research and Practice
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• v.4 no.1
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• pp.51-57
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• 2010

We performed this study to examine lifestyle patterns and dietary behavior based on the level of Internet addiction of Korean adolescents. Data were collected from 853 Korean junior high school students. The level of Internet addiction was determined based on the Korean Internet addiction self-scale short form for youth, and students were classified as high-risk Internet users, potential-risk Internet users, and no risk Internet users. The associations between the students' levels of Internet addiction and lifestyle patterns and dietary behavior were analyzed using a chi-square test. Irregular bedtimes and the use of alcohol and tobacco were higher in high-risk Internet users than no risk Internet users. Moreover, in high-risk Internet users, irregular dietary behavior due to the loss of appetite, a high frequency of skipping meals, and snacking might cause imbalances in nutritional intake. Diet quality in high-risk Internet users was also worse than in potential-risk Internet users and no risk Internet users. We demonstrated in this study that high-risk Internet users have inappropriate dietary behavior and poor diet quality, which could result in stunted growth and development. Therefore, nutrition education targeting high-risk Internet users should be conducted to ensure proper growth and development.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.3
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• pp.3-12
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• 2019

Since offline contact becomes a strong differentiator as online market expands, the shopping mall calls for more complex and diverse tenant combinations and deployment plan strategies. There is, however, few practical research and causal verification of Tenant Mix, i.e., the combination and placement of tenant and users' behavior, has been conducted which is a key factor in spatial configuration. In practice, Tenant Mix is limited in prediction of consumption behavior of customers by the MD planners's experience and depends only on qualitative arbitrary plan. The purpose of this study is to find out the interrelationship between the spatial configuration and the users' behavior of Tenant Mix in shopping mall, and to present an objective basis in MD planning. According to the analysis, it was possible to know that there are differences in the relationship between the spatial configuration and the users' behavior dependent on the Tenant Mix, which is the space planning of shopping mall. It was also possible to find out the characteristics and differences in the users' behavior which is dependent on the spatial configuration for each tenant. Through this study, it was possible to know the impact of space organization on the users' behavior and the interrelationship between the use's behavior and spatial configuration by tenant together with their characteristics. We prove that the current MD planning has limitation due to lack of objective research on the combination and arrangement of space in the commercial space and only done empirically. This analysis can show the practical plan of combination and placement of tenant which is emphasized in complex and larger shopping malls, and contribute to the revitalization of shopping mall by better use of tenant.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.719-745
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• 2015

Social networking services provide individuals with an easy approach for exchanging messages with others based on interpersonal relationships. However, why individuals spread marketer-generated content (MGC) in their online social circles remains unclear. Therefore, we develop a theoretical model to examine how social capital, intrinsic motivations, personal perceptions, past behavior, and personal traits influence MGC sharing behavior of social media users in micro-blogging context. Data collected from 319 social networking users support the proposed model. The results from partial least squares analyses show that enjoyment, perceived control, and outcome expectations are significant indicators of individual's MGC sharing intention in the social broadcasting environment. Results also suggest that social capital, users' intention, and past behavior positively influence the MGC sharing behavior of users. Moreover, individual prevention pride exhibits a significant interaction effect on the relationships between users' MGC sharing and its antecedents. Implications for research and practice are discussed.

• Fashion & Textile Research Journal
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• v.24 no.2
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• pp.195-205
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• 2022

This study examines the image management behavior according to self-monitoring, self-objectification of profile-based SNS users. Questionnaires were administered to 313 SNS users including both men and women in their 20s to 30s. The SPSS 25.0 package was utilized for data analysis, which included frequency analysis, factor analysis, Cronbach's ?, t-test, and regression analysis. The study analyzed self-monitoring in 2 groups (high, low), self-objectification for 2 factors (body surveillance, body shame), and image management behavior for 5 factors (fashion oriented, instrumentality, conformity, ostentation, interpersonal disposition). The results revealed: first, self-monitoring groups exhibited significant differences in self-objectification. The higher self-monitoring group was more influenced by body surveillance and body shame compared to the low self-monitoring group. Second, self-objectification had a positive influence on all the factors of image management behavior. Especially, body surveillance demonstrated a high influence on instrumentality and body shame showed a high influence on ostentation. Third, the self-monitoring groups showed significant differences in all the factors of image management behavior. The higher self-monitoring group demonstrated more influence of image management behavior compared to the low self-monitoring group. These results provide useful information in understanding the influence of social media on users' psychological attitude and consciousness toward their body and image management behavior.

• The Journal of Information Systems
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• v.28 no.2
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• pp.129-152
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• 2019

Purpose The purpose of this study is to empirically identify the risky behavior of mobile device users using the Internet of Things on a situational perspective. Design/methodology/approach This study made a design of the research model based on model of the determinants of risk behavior. Data were collected through a survey including hypothetical scenario. SmartPLS 2.0 was used for the structural model analysis and t-test was conducted to compare the between normal and situational behavior. Findings The results were as follows. First, the central roles of risk propriety and risk perception were verified empirically. Second, we identified the role of locus of control as a new factor of impact on risky behavior. Third, mobile risk propensity has been shown to increase risk perception. Fouth, it has been shown that risk perception does not directly affect risky behavior and reduce the relationship between mobile risk propensity and risk behavior. According to the empirical analysis result, Determinants of risk behavior for mobile users were identified based on a theoretical framework. And it raised the need to pay attention to the impact of locus of control on risk behavior in the IS security field. It provided direction to the approach to risky behavior of mobile device users. In addition, this study confirmed that there was a possibility of taking risky behavior in the actual decision-making.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.1
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• pp.5-28
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• 2010

This study analyzed the characteristics of library service users' information seeking behavior based on the grounded theory methodology. After interviewing twelve undergraduate students, the researcher coded the data based on the grounded theory methodology. As a result of the entire coding processes, this study constructed the library service users' information seeking behavior model. According to the model, the following ten factors are important when explaining library service users' information seeking behavior: the information users' environment, other people, users' experiences, recognition of information sources, information provided, memory, a need-creating environment, information gathering, information use, and satisfaction and/or dissatisfaction.