• Journal of Digital Convergence
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• v.6 no.4
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• pp.157-163
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• 2008

Despite the increase internet use rate, there still appears a big difference in web usage rates depending on demographic variables, web usage environment variables. This study aimed to improve our understanding of perceived usage, attitude, affected factors related Web usage for schoolwork and research. This result will facilitate further understanding of perceived usage, attitude, affected factors related Web usage, thereby enabling researchers, practitioners, and policy makers to better design appropriate strategies to promote the Web usage.

• International Commerce and Information Review
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• v.9 no.1
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• pp.119-148
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• 2007

The purpose of this research is to study whether environments of participating firms of electronic marketplace(e-MP) have an influence on usage factors which are supplying from e-MP and usage factors affect usage performances. Based on the existing researches we found variables and executed a empirical study of environment-usage-performance model. Through this research we suggested useful factors for the performance of trade enterprises. Usage factors of e-MP will overcome geographical limitation and acquire new sales areas and simultaneously widen the relationships of global enterprises. Those firms could be accessible into global market promptly. To enhance usages of e-MP, service quality which can satisfy both buyer and seller at the same time should be strengtened. Finally, the usage of e-trade information should also heighten through usage factors.

• Journal of the Korean Society of School Health
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• v.31 no.3
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• pp.135-145
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• 2018

Purpose: The study aimed to investigate the factors associated with long hours of smartphone usage and to identify the characteristics of the high-risk group among female middle school students in South Korea. Methods: The study analyzed the data of 13,648 female middle school students using their own smartphone extracted from the 13th Youth Health Behavior Online Survey (2017). The factors related to using smartphones for a long time was analyzed by binomial logistic regression. The characteristics of the high-risk group was defined by a decision tree analysis. Results: The average hours spent on smartphone usage was 269.54 minutes per day. The significant factors associated with the long hours of smartphone usage were grade, living with parents, perceived household economic status, perceived academic achievement, stress, sadness and hopelessness, the main purpose of smartphone usage, drinking, body mass index, breakfast, and satisfaction with sleep quality. The subjects showing low academic performance and having breakfast four times a week or less were more likely to use their smartphone for a long time. Conclusion: Based on the results of the research, we need to establish intervention strategies focusing on the factors influencing long-time usage of smartphone. Particularly, the subjects who show poor academic performance and skip breakfast frequently should be considered as the high-risk group for spending long hours on smartphone usage.

• The Journal of Information Systems
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• v.26 no.1
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• pp.143-169
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• 2017

Purpose With the increase of the elderly population, the growth of its information system related market is increasing. However, empirical studies for the usage of elderly people's smartphones are still limited. This study aims to investigate the factors that affect the seniors' smartphone usage behaviors. Design/Methodology/Approach First, a preliminary study was conducted with targeting seniors who have visited Gwangju Senior Technology Center(GSTC) in order to understand the factors that affect the intention of utilizing smartphones. Next, based on the preliminary study results and literature reviews including the UTAUT model, performance expectancy, effort expectancy and social influence were considered for the major factors affecting the usage of elderly people's smartphones. Also, the moderate effects of personal innovativeness and usage function were discussed. A questionnaire survey of 181 seniors visiting GSTC was analyzed to empirically test the research model. Findings By the empirical tests, the performance expectancy and the effort expectancy of the seniors had significant impacts on their smartphone usage behavior. While the moderating effect of personal innovativeness was not significant, the moderating effect of the usage function was significant in the relationship between performance expectancy and the smartphone usage behavior. The results of this study are expected to provide guidelines to excavate the technical development and the niche market targeting the elderly people.

• Journal of Digital Convergence
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• v.7 no.2
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• pp.83-91
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• 2009

This study aimed at improving our understanding of education-related Web usage for schoolwork and research in universities. This study found out a list of factors that influence the usage of education-related Web sites by Korean and New Zealand university students and suggested the features of those factors. These findings will enhance further understanding of factors associated with Education-related Web usage and the relationship among attitude, intention to use, and performance, which could help web practitioners design and develop education-related Web sites to promote web usage and attract university students into their web sites.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.7
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• pp.27-34
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• 2018

The energy consumption of apartment houses is affected by various factors. The criteria for assessing current energy usage are area, region and purpose. The purpose of this study is to obtain the reliability of the method of evaluating the existing energy consumption certificate and to derive usable evaluation factors according to the correlation of factors affecting energy consumption. The research process collects energy usage data for apartment houses in Daegu and calculates statistical results through correlation analysis and multiple regression analysis. As a result, it was found that the power energy is influenced by the yearly factor of physical characteristics, and the heat energy and total energy usage are influenced by the energy source which is energy characteristic factor.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.179-186
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• 2019

While there have been a lots of studies on the use of cyber money, few researches proposed the results on relationships among quality factors, usage intention, and usage characteristics of cyber money in online business environment. Therefore, this study investigates the relationships between cyber money quality and usage intention of cyber money, and examines whether the usage characteristics(frequency, amount) of cyber money has moderating effect on the relationship between cyber money quality and usage intention of cyber money. Firstly, multiple regression analysis tells significant causal relationship between functional and emotional factors of cyber money quality and usage intention of cyber money. Secondly, dummy regression analysis shows usage characteristics of cyber money has the moderating effect on the relationship between cyber money quality and usage intention of cyber money. This paper concludes with some implications for both theory development and cyber money practice.

• Journal of Navigation and Port Research
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• v.30 no.8 s.114
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• pp.669-674
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• 2006

The purpose of this study is to examine the effects of the factors on the usage level of e-business in the shipping companies. In order to do empirical analysis, firstly, this study carried out reliability analysis and factor analysis. Secondly, this study examined the effects of the factors on the usage level of e-business in the shipping companies by multiple regression analysis. In conclusion, the analysis result revealed that 5 factors effect on the service business usage's level and 4 factors effect on the real transaction usage's level of e-business.

• Culinary science and hospitality research
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• v.23 no.1
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• pp.37-47
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• 2017

The number of delivery app users and their social impact have increased along with the number smartphone users. Accordingly, the present study attempted to suggest a method to improve the service quality of delivery apps for relevant businesses and researchers by determining the influences of delivery app usage factors on customer satisfaction and reuse intention. The present study distributed and collected questionnaires through on- and offline surveys targeting males and females in their 20s in the Daejeon area. The results of the regression analysis showed that the influence of delivery app usage factors on customer satisfaction was 43.8%, and informativeness, payment and safety, usefulness, and convenience were found to influence the increased satisfaction with the delivery apps. The influence of delivery app usage factors on customers' reuse intention was 37.3%, and among the four usage factors, informativeness and payment and safety were found to be the main factors for increasing the reuse intention. As providing more accurate information is a means to increase customer satisfaction and reuse intention by improving the service quality of the delivery apps, new menus and prices should be rapidly updated.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.41-57
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• 2023

This paper aims to analyse the factors influencing the implementation of smart factories and their performance after implementation, using the grounded theory analysis method based on interview data. The research subjects were 21 companies that were selected by the Smart Manufacturing Innovation Promotion Group under the SME Technology Information Promotion Agency in 2020-2021 as the best case smart factory implementation companies, and introduced the intermediate stage 1 or above. A total of 87 concepts were generated as a result of the analysis. We were able to classify them into 16 detailed categories, and finally derived six broad categories. These six categories are "motivation for adoption", "adoption context", "adoption level", "technology adoption", "usage effect" and "management effect". As a result of the overall structure analysis, it was found that the adoption level of smart factory is determined by the adoption motivation, the IT technology experience affects the adoption level, the adoption level determines the usage and usage satisfaction, internal and external training affects the usage and usage satisfaction, and the performance or results obtained by the usage and usage are reduced defect rate, improved delivery rate and improved productivity. This study was able to derive detailed variables of environmental factors and technical characteristics that affect the adoption of smart factories, and explore the effects on the usage effects and management effects according to the level of adoption. Through this study, it is possible to suggest the direction of adoption according to the characteristics of SMEs that want to adopt smart factories.