• Journal of Digital Convergence
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• v.15 no.7
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• pp.27-39
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• 2017

To grasp the current status of smart campus and look for future directions, this study investigated the usage rate and perceived usefulness of digital devices and services by conducting online survey of 580 university students. The main results are as follows. First, smartphones have the highest ownership rate, followed by laptops, desktops, and digital cameras. Purchase intention of virtual reality devices is highest followed by smart watches/bands, and tablets. Second, mobilization in campus life is almost realized, however the usage of desktops is still high in education and administration context. Digital devices have been perceived particularly useful when searching and sharing information. Third, students use digital services such as search engines, messengers, and online libraries in their learning, and they use messengers, music and video services in their lives. Service usage rate and perceived usefulness are not proportional.

• Journal of radiological science and technology
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• v.46 no.1
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• pp.53-61
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• 2023

The aim of this study analyzed the important level (IL) and understanding level (UL) including the Borich's need for students preparing of the national examination for radiological technologists at online open chatting room. A total of 254 survey were collected from a total of 1,016 students who used open chatting room from December 13 to December 16, 2022. A general characteristics were the age, gender, curriculum (3 or 4 years), grade and area. The IL, UL, learning satisfaction (LS), learning achievement (LA) and intention to continue using (ICU) were analyzed by using the 5 point Likert scale. There was no significant difference the LS, LA, and ICU according to general characteristics (p>0.05). There was a statistically significant difference a total of sixteen subjects based on the t-test results of the response values from the IL and UL (p<0.05). The total of ten subjects with the highest priority in the Locus for Focus models were the Ultrasonography, Human anatomy, Magnetic resonance imaging, Radiation therapy, Cardiovascular and intervention, Computed tomography, Human physiology, Radiographic imaging, Fluroscopic radiography, and Nuclear medicine) that the Borich's need was also the same as the top 10 ranked subjects. The LS (4.23±0.72), LA (4.18±0.73), and ICU (4.15±0.78) for open chatting room were high. This study identified the subjects most needed by college students by the Borich's need analysis. First, it is necessary to provide intensive education on subjects with high scores that are most needed by college students. Second, it is necessary to improve the teaching method for subjects with low need and low level of understanding.

• Journal of Information Technology Services
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• v.10 no.4
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• pp.1-19
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• 2011

Following the growth of e-Business, there has been a recent increase of interest in promoting Social Business (s-Business) based on Social Network Service(SNS). As the introduction of the Internet brought about the increasing number of its users followed by the growing market of e-Commerce, online games, and e-Learning, the increasing number of SNS users has opened the new markets combining the existing industrial fields with SNS, and it developed into a revenue model beyond the mere sharing of information. Despite such industrial and social environments, understanding of new social business technology from the aspect of business has been insufficient, and the empirical study on participation in the social business has been scant as well. Thus, the main purpose of this study is to investigate the s-Business in detail and to study the factors giving influence to the users' participation in s-Business. This study proposes six variables(Self-Empowerment, Job Relevance, Formation of Social Capital, Relative Advantage, Shared Value, Relationship Specified Investment) and the moderating effects of Psychological Contract as influential factors closely related with s-Business. A total of 362 data from a survey were analyzed by using Structural Equation Modeling(SEM). Result showed that all factors with the exception of Job Relevance have meaningful influence on the intention to participate in s-Business. The implication of the findings suggests to compliment limitations of the existing researches, and to prepare the theoretical foundation for promoting s-Business participation in addition to further suggesting directionality from the view point of the users of the social business-relevant studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1168-1188
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• 2018

Social Network Aggregators are used to maintain and manage manifold accounts over multiple online social networks. Displaying the Activity feed for each social network on a common dashboard has been the status quo of social aggregators for long, however retrieving the desired data from various social networks is a major concern. A user inputs the query desiring the specific outcome from the social networks. Since the intention of the query is solely known by user, therefore the output of the query may not be as per user's expectation unless the system considers 'user-centric' factors. Moreover, the quality of solution depends on these user-centric factors, the user inclination and the nature of the network as well. Thus, there is a need for a system that understands the user's intent serving structured objects. Further, choosing the best execution and optimal ranking functions is also a high priority concern. The current work finds motivation from the above requirements and thus proposes the design of a query processing system to retrieve information from social network that extracts user's intent from various social networks. For further improvements in the research the machine learning techniques are incorporated such as Latent Dirichlet Algorithm (LDA) and Ranking Algorithm to improve the query results and fetch the information using data mining techniques.The proposed framework uniquely contributes a user-centric query retrieval model based on natural language and it is worth mentioning that the proposed framework is efficient when compared on temporal metrics. The proposed Query Processing System to Retrieve Information from Social Network (QPSSN) will increase the discoverability of the user, helps the businesses to collaboratively execute promotions, determine new networks and people. It is an innovative approach to investigate the new aspects of social network. The proposed model offers a significant breakthrough scoring up to precision and recall respectively.

• Review of Culture and Economy
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• v.21 no.2
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• pp.111-139
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• 2018

This study is about classical music lovers who write a lengthy concert review on instagram. The intention and objective of writing a review is discussed in addition to inter-communication between those reviewers. For the analysis, an interview with 8 reviewers are mainly analyzed with their reviews. As a result, it is found that some affordances of Instagram, easiness, randomness, and friendliness affects them to use Instagram more than other social media. Hence, since Instagram is image-based platform, it helps writers to keep their reviews from getting an attention by other users. Because of their sense of inferiority that they are lacking in classical music knowledge, continuous writing and reading of reviews help them accumulating some amount of cultural capital needed for understanding classical music in a proper way.

• Journal of the Korean Society of Food Culture
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• v.27 no.6
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• pp.666-676
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• 2012

The purpose of this study was to propose effective marketing communication strategies for overseas Korean restaurants through a multilateral comparison analysis of American, Chinese, and Japanese consumers' attitudes towards communication media and Korean restaurants. The survey was written in English, Chinese, and Japanese, with guideline for surveyors, and conducted using both online and offline methods. Samples were collected from five major cities - Los Angeles, New York, Tokyo, Beijing and Shanghai, which are the foothold for the globalization of Korean food. When it comes to attitudes towards communication media, word-of-mouth showed a high mean value, indicating it as the most useful and reliable media recognized by consumers who visited Korean restaurants. Furthermore, the necessity of recognizing the importance of visual communication in the physical environment of Korean restaurants and specialized websites, featuring restaurants and gourmet food, was observed. Consumers in all three nations chose word-of-mouth as the most useful and reliable media for learning about Korean restaurants. In addition, American consumers highly depended on signage and restaurant exteriors. Chinese consumers highly recognized the usefulness and reliability of offline media, such as newspapers, magazines, and events, while Japanese consumers considered online media, such as gourmet websites, blogs and social networks, as useful and reliable sources. A significantly positive attitude and high value was observed in all who had visited Korean restaurants. American and Japanese consumers had a significantly higher rate of intention to visit Korean restaurants in the future and to tell others about their satisfaction with Korean restaurants. Meanwhile, the average rate of prior preference for Korean restaurants (when choosing restaurants) was the lowest in all three countries. This study is useful for both the Korean government and food enterprises abroad to plan and develop marketing communication strategies properly for overseas Korean restaurants.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.